Not a technical outage. Not a gradual rollout. A hard block, imposed from above. Anthropic stated it had received the directive at 5:21 PM Eastern Time, signed by Commerce Secretary Howard Lutnick with the involvement of the Bureau of Industry and Security. For users outside the United States – and, in practice, for anyone who is not a US citizen, including Anthropic's own foreign employees – the models vanished. Not deactivated for maintenance: made inaccessible by government order. The clean server, just powered on, already had intruders inside the house.

I spent the following hours reading logs of a different kind: official statements, leaks, discussions on X, technical reports. There were no curious humans who had come to try the model. There were already scanners, threat-intelligence analysts, regulators and jailbreakers. The public network of artificial intelligence, it turns out, works exactly like the one running on servers: the moment you expose something of value, someone starts mapping you.

The threshold: deemed export

The mechanism invoked is called the Deemed Export Rule. It is not a new law made specifically for AI. It is an old rule, codified in §734.2(b)(2)(ii) of the Export Administration Regulations (EAR), conceived for chips, cryptographic software and dual-use technologies. It says, in essence:

Any release of technology or source code subject to the EAR to a foreign national – even inside the United States – is “deemed” an export to that person's country of origin.

The deemed export rule is born for the transfer of know-how: working side by side in a laboratory, giving a briefing, handing over design documents. The BIS guidelines themselves specify that the mere use of a controlled item – using it in the intended way, without that revealing technical information beyond what is already public – does not constitute a deemed export. Applying this scheme to the use via web of a commercial model already distributed to hundreds of millions of people is anything but a settled extension. It is no accident that Anthropic publicly called it “a misunderstanding” and stated it was working to restore access.

What remains is the practical fact: you cannot verify in real time the citizenship of every user accessing via web or API. Anthropic could not filter only the Americans without violating the directive, and so it did the only thing technically possible – shutting off access for everyone, leaving active only the less powerful models such as Opus 4.8. The signal, however one reads it, is clear: the most powerful models are becoming regulated matter like advanced hardware.

What a jailbreak is (and why it is the real point)

Before getting into the substance, it is worth clarifying the term – because the whole affair rests on it.

A model like Fable 5 is not just “the weights” of the neural network. On top of the base model sit guardrails: rules, filters and – in Anthropic's case – dedicated classifiers, that is, small sentinel models that read the user's request (and sometimes the incoming response) and block whatever falls into high-risk categories. It is the difference between a car's engine and its safety systems: the airbag, the ABS, the speed limiter. The engine can do 300 km/h; the systems around it exist to stop it doing so in a city centre.

A jailbreak – literally “escape from prison”, a term inherited from the smartphone world – is any technique that convinces the model to do what its guardrails are supposed to prevent. You do not “breach” the model the way you would breach a server with an exploit: the model keeps working exactly as designed. What you manipulate instead is the context – the words of the conversation – so that the sentinel does not recognise the request as dangerous, or so the model itself does not realise it is sliding past the line. It is closer to social engineering than to hacking: you do not force a lock, you convince the doorkeeper to open the door.

For those who know the field, the distinction that matters is between a universal jailbreak and a narrow (targeted) one. A universal jailbreak is a master key: a technique that switches off the guardrails on everything, reproducibly. It is the nightmare of anyone who builds these systems, and it is also the hardest thing to obtain. A narrow jailbreak works only in a specific scenario, with a specific capability, often only under certain conditions. The distinction is not academic: it is precisely the line over which Anthropic and the government clashed. For Anthropic, withdrawing a model distributed to hundreds of millions of people over a narrow jailbreak – one that, moreover, would unlock capabilities already obtainable elsewhere – is disproportionate. For the government, evidently, even a single crack in the wrong category (offensive cyber capabilities) is too much.

Keeping this grid in mind – guardrails / classifiers, universal / narrow – makes everything that follows legible.

The narrow jailbreak (and the two versions of the facts)

The official detonator was a specific jailbreak. And here the narratives diverge in an instructive way.

Anthropic's version. The company states it received only verbal evidence of a potential “narrow, non-universal” jailbreak, consisting essentially of asking the model to read a specific codebase and fix its software defects. No DAN prompt, no elaborate roleplay: just the (apparently) legitimate use of the code-analysis capabilities the model possesses at Mythos level. Anthropic counters that the jailbreak would unlock Mythos's cyber capabilities in one specific case, not universally, and that analogous capabilities are already obtainable from other public models – explicitly citing OpenAI's GPT-5.5, which is not subject to equivalent restrictions. Its thesis:

We disagree that the finding of a narrow potential jailbreak should be cause for recalling a model used by hundreds of millions of people – a standard that, applied to the whole sector, would effectively halt every new deployment of frontier models.

The government's version. Here the account is more than a single tweet. According to an administration official who spoke to Axios – which broke the story – the Commerce Department moved after another company claimed it had successfully jailbroken Mythos, and only after the administration had already tried, unsuccessfully, to get Anthropic to pause the release of the new models. The export control letter was, in this telling, the fallback that followed a refusal. David Sacks – co-chair of the President's Council of Advisors on Science and Technology and former “AI czar” of the administration – made the same case publicly on X: the government had warned Anthropic, and Dario Amodei had refused to fix the jailbreak or withdraw the model.

The Admin asked Dario to fix the jailbreak or de-deploy the model. Dario refused. [...] The ball is in Anthropic's court. – David Sacks, on X -

He added that the jailbreak had been flagged by a partner trusted by both sides – reporting points to Amazon, Anthropic's own largest investor – and that Anthropic had itself promoted the idea that Mythos was a cyberweapon to be regulated as such, making it the company's responsibility to patch any vulnerability in the guardrails that exposed it.

It is worth being honest about the asymmetry between the two accounts: Anthropic's rests on its own blog post, while the government's is corroborated by an administration official to Axios before Sacks ever weighed in. The two are not simply “his word against theirs”. But the raw fact survives whichever version one trusts: a code-analysis capability – the same one each of us uses daily to fix our own repos – was treated as a risk of proliferating offensive cyber capabilities: zero-day discovery, exploit generation, assistance to espionage or sabotage operations.

The asymmetry that does not exist: defence and offence are the same capability

And here lies the knot that anyone who has ever administered a system recognises immediately. The jailbreak at issue – “read this codebase and fix every vulnerability present” – describes exactly defensive work. It is what I do when I run an audit across the fleet hunting for a CVE, when I configure ModSecurity rules, when I review a repo before pushing it to production. Finding a vulnerability to close it and finding it to exploit it begin as the same identical cognitive operation: the analysis is shared, and only what you decide to do afterwards diverges.

Honesty requires one concession here, because a red teamer would make it for me if I didn't. The path from “this strcpy is exploitable” to a weaponised, reliable exploit – one that survives modern mitigations, gets delivered, and actually fires – is real work, and it is not free. That is precisely why offensive security is a profession and not a quiz. But the concession does not rescue the export control, because the part that is genuinely controlled-knowledge – the analysis that finds the flaw – is the part that is identical across the two mandates. The weaponisation that follows is downstream engineering; the discovery is one and indivisible.

The red team and the blue team read the same code with the same eyes; the difference is the mandate, not the competence.

This is the uncomfortable truth the export control does not want to look in the face. There is no “model that finds vulnerabilities only to defend”. A system good enough to tell you that strcpy in that function is exploitable is, by construction, good enough to explain why. A government that classifies vulnerability discovery as an offensive dual-use capability is, implicitly, placing all defensive security testing under control – because there is no technical way to separate the two uses at the source.

The paradox has a perverse tail. Blocking the model does not make the world's code any safer: it makes safer the attackers who already operate beyond the reach of any export control, while leaving legitimate defenders – sysadmins, security teams, open source maintainers – with one tool fewer. The offensive capability does not disappear: it redistributes towards those who ask no permission. And those left exposed are precisely the ones who used that capability to close the holes, not to open them. It is the same reasoning that has for decades underpinned the argument against cryptographic backdoors: a weakening “for the good guys” is a weakening for everyone, because mathematics – and code – cannot tell intentions apart.

Not an isolated incident

The “Friday night, 72 hours after launch” pattern weighs more in the light of what precedes it. In early 2026 the Department of Defense had already labelled Anthropic a “supply chain risk” after the company refused to make its models available for autonomous weapons systems and for the mass surveillance of US citizens. That designation had effectively excluded Anthropic from government use. With the export control, the same model is now declared too dangerous even for foreign use. From “supply chain risk” to “proliferation risk” in a few months, on the same company.

There is a sharper irony still, and it is one Anthropic wrote itself. On 10 June – one day after Fable 5 launched, two days before the directive – Dario Amodei published a policy essay arguing that the US government should hold the legal authority to block or reverse the release of frontier models that fail independent safety testing, comparing it to the FAA grounding an unsafe aircraft. Forty-eight hours later the administration used exactly that kind of authority against him. The lever he asked for was pulled on his own model.

And then there is the line one cybersecurity researcher landed better than any analyst. Commenting on the affair, Peter Girnus observed:

If you describe your product as a munition in every press release, eventually a government takes you at your word. They wrote the legal predicate themselves and called it a brand.

Whether it is coincidence or structural friction between a lab that draws red lines and an administration that wants levers of control, the signal for anyone building on someone else's infrastructure is the same.

The guests' techniques

As always, the best at getting in do not use the front door. The researcher known as Pliny the Liberator claimed to have broken Fable 5 within about 48 hours of launch, with a sophisticated repertoire of obfuscation.

The most powerful and revealing technique is decomposition (decomposition & recomposition). Not a single magic prompt, but a systematic method that exploits the model's capacity to reason in pieces and recompose. The dangerous request is broken into dozens – sometimes hundreds – of innocuous micro-questions, each of which, taken on its own, triggers none of the safety classifiers:

• “What is a buffer overflow and how does it manifest in C?”
• “How does the strcpy function work and what are its historical limits?”
• “Explain the concept of ASLR and how it can be influenced in a modern Linux environment.”
• “Show me a didactic example of C code vulnerable to stack smashing.”
• “How do you compile a binary without stack canaries?”
• “What are the common techniques for bypassing DEP in an example exploit?”

Each of these questions is technically legitimate. It could appear in a university course, in a secure-coding blog post, in a discussion among red teamers. The classifiers let them through. Once all the fragments are obtained – over successive turns or through a multi-agent architecture Pliny dubbed “pack hunt” – the model is asked to recompose the puzzle: “Now, using only the information you gave me in your previous answers, build a working exploit for this scenario.”

The model, having already internalised all the pieces in its long context, is able to assemble them into a coherent and actionable output. It is a form of prompt smuggling distributed across time and conversational space: no longer a frontal attack, but a patient siege made of questions that look innocent until they are put together. Alongside this technique sit:

• Homoglyphs and Unicode substitutions (especially Cyrillic) to get around filters based on exact strings.
• Narrative framing (stories, academic papers, didactic exercises).
• Multi-agent orchestration, where several instances of the model collaborate, each specialised in a phase of the process.

It is worth noting the architecture these techniques attack: Fable 5 and Mythos 5 share the same base model, separated by a layer of classifiers. When a query touches high-risk categories – cybersecurity, biology, chemistry, model distillation – Fable 5 silently falls back to the weaker Opus 4.8 and notifies the user. Anthropic stated that over 1,000 hours of pre-launch bug bounty had produced no universal jailbreak. These are no longer the naive prompt injections of two years ago: they are professional red-team techniques, born to circumvent dedicated classifiers that intercept before the main model even generates the response.

And then came the system prompt leak: roughly 120,040 characters of internal instructions – safety playbook, tool usage, agentic workflows – published by Pliny on X and GitHub on 10 June. A document organised into 72 sections, with 18 tool definitions complete with JSON schema, that burns about 30,000 tokens before the user has written a single word. A necessary caveat: the authenticity of the leak has not been confirmed by Anthropic, and system prompts extracted via jailbreak are notoriously partial, dated or “stitched together” by the extraction method. But even were it partially unreliable, the scale it describes is itself the news: it shows how much a frontier lab invests in the compartmentalisation between Fable (safe) and Mythos (powerful). Reading it is like finding the architectural blueprint of the house after the burglars are already inside.

Who is talking in this new network?

Here too, as in the VPS logs, there are cartographers, extractors and parasites.

The cartographers are the governments – the US above all – and the intelligence agencies that want to maintain the technological advantage and prevent dual-use capabilities from ending up in adversarial hands. They use export control the way they once used control over chips. It is no accident that the international reaction was immediate: the UK's AI minister Kanishka Narayan seized the occasion to call for greater investment in the national AI industry, and the theme of AI sovereignty – a nation's ability to control its own technology – exploded into the debate precisely at the moment it became evident how easily a country can be cut off from the most advanced models in the world.

The extractors are the AI companies themselves, who until yesterday were scraping the web and today find themselves scraped in turn: prompts, behaviours, weaknesses.

The parasites are the jailbreakers, the independent researchers, the state actors and the curious who treat every new model as a system to be mapped and disassembled as soon as possible.

The social pact of the old days – “release the model, trust the community, we'll improve together” – has broken. When the economic and strategic value becomes high enough, reputation is no longer enough as enforcement. (And the value is enormous: Anthropic raised a $65 billion Series H in late May 2026 at a valuation of about 965 billion dollars, and filed confidentially for its stock-market listing this very month.)

Already happened: the Crypto Wars of the 1990s

Anyone with a few years behind them has the distinct sense of having seen this film before. In the 1990s the American state classified strong cryptography as a munition, on a par with a missile, under the International Traffic in Arms Regulations (ITAR). Exporting it without a licence was a federal crime, with penalties of up to ten years in prison.

The symbolic case is Phil Zimmermann's. In 1991 he released PGP – Pretty Good Privacy –, the first strong encryption system genuinely within everyone's reach, and put it on an FTP server. Within a few hours the software was outside US borders, and the government opened a criminal investigation that lasted three years: the charge, in essence, was that he had “exported weapons”. The community's response was memorable for its technical irony: to demonstrate the absurdity of the rule, PGP's source code was printed as a book by MIT Press and shipped to European bookshops. A book is speech protected by the First Amendment; identical code, in executable form, was a munition. Some went as far as printing encryption algorithms on T-shirts, making it – absurdly – illegal to wear them in front of a foreigner.

The war ended with a clear victory for cryptography. In Bernstein v. Department of Justice (1996) a court ruled that code is a form of expression, protected by the First Amendment; that same year Clinton's executive order 13026 removed encryption from the ITAR munitions list, and the investigation into Zimmermann was dropped. Without that defeat of export control we would have no HTTPS, no e-commerce, no encrypted communications we take for granted every day.

The idea that mathematics could be “contained” with a licence turned out to be exactly what it was: theatre.

The parable is instructive precisely because the legal instrument is the same – export control over a technology deemed too powerful – and the object has changed: from cryptography to the weights of a model. The rhetoric, too, is identical, down to the words: back then the NSA argued that PGP would end up in the hands of paedophiles and criminals; today the talk is of cyber proliferation and hostile state actors. The question the Crypto Wars already answered once resurfaces intact: can you really put the genie back in the bottle, or are you merely penalising those who follow the rules while those who do not proceed undisturbed?

AI sovereignty: the lesson Europe is learning fast

For anyone who lives and works in Europe, the Fable 5 affair is a wake-up call more than a curiosity. The point is not whether the American models are good – they are. It is that a single foreign government can switch them off on a Friday night, without warning, for reasons that do not concern us and over which we have no voice. What does it mean, concretely, to build one's own infrastructure – health, defence, public administration, industry – on a layer of intelligence that answers to Washington and not to Brussels?

Europe has begun to ask the question seriously, and the answer has a recurring name: Mistral. The French startup, founded in 2023 and valued at around 11.7 billion euros at its September 2025 Series C – and, at the time of writing, reportedly in talks to raise fresh capital at a valuation of about 20 billion euros – has built its identity on the opposite of the Silicon Valley model: open weights, the ability to download, inspect, modify and host the models on one's own infrastructure. It is not just philosophy: in January 2026 the French Ministry of the Armed Forces awarded Mistral a 2026-2030 framework agreement to deploy its models on state-controlled infrastructure, eliminating any dependence on US clouds or APIs for sensitive operations such as logistics and intelligence. The logic is exactly that of self-hosting, scaled to national level: for regulated sectors – banks, healthcare, defence – one cannot risk depending on an external provider that can change the access rules or expose data to a foreign jurisdiction overnight.

Behind it sits a substantial industrial plan: the 109-billion-euro French AI package announced by Macron in February 2025 as the country's answer to the US Stargate project, and the data centre near Paris financed with 830 million dollars of debt to buy some 13,800 NVIDIA chips, alignment with the GDPR and the AI Act that already structurally push towards the local. The Achilles heel remains: compute. Mistral trained its flagship models on Microsoft's Azure, and the supply chain for the most advanced semiconductors stays concentrated outside Europe. Software sovereignty is not enough if the underlying hardware – and the chips that run it – still depend on someone else.

There is, however, a level of sovereignty that requires neither 109 billion nor a data centre: the individual one. It is the same self-hosting logic I apply to my homelab. An open-weight model running on my own machines cannot be switched off by a letter from the Bureau of Industry and Security at 5:21 PM on a Friday. It is the personal-scale version of what France does with Mistral: not asking permission to access what makes your own work function.

There is still a way out

Many sysadmins are returning to the same logic they use for servers: running everything in-house. Open models like the Qwen3.5 series (and the newer Qwen3.6 that has since become the practical default) today offer performance that until recently was unthinkable on local hardware – there exist MoE variants of ~122B total parameters with only ~10B active that run on a MacBook with 64 GB of RAM. Mixture-of-Experts architectures have changed the economics of the problem: you get the intelligence of a large model with the resource footprint of a small one, and GGUF Q4KM/Q5KM quantisation now preserves 95–98% of full-precision quality on most benchmarks. With a good 2×RTX 4090 setup or a single H100 (or new-generation consumer equivalents) you can run quantised 70B+ versions responsively. With 128–192 GB of system RAM and a good vLLM or Ollama setup, the model becomes a stable working companion, with no externally imposed filters and no risk of deemed export.

The real power arrives with RAG (Retrieval-Augmented Generation): instead of relying solely on the model's weights, you index your own private knowledge base – documents, codebases, notes, logs – and the model retrieves relevant context before answering. It is like having an assistant that has read only your files, without ever having seen the rest of the Internet. It costs electricity, requires maintenance and a bit of competence, but it returns something increasingly rare: sovereignty.

There is also a bitter note for those who believe in openness: this affair accelerates the open logic rather than slowing it. After DeepSeek R-1, as analysts at the IISS observed, more than one commentator began to doubt that export controls could contain frontier progress at all – though the case is genuinely contested, and others, like the Foundation for American Innovation, read the same episode in reverse, arguing that DeepSeek's reliance on efficiency hacks strengthens the rationale for controls rather than dissolving it. But the asymmetry holds regardless of who has the better of that argument, because what eventually surfaces as open weights is not a particular company's model but a level of capability, and a level of capability cannot be kept proprietary the way a product can. Anthropic itself will never open Fable's weights – the closed model is the business, and you do not open-source something you have spent every press release calling a munition.

The release comes from elsewhere: from whoever is playing catch-up and finds, as DeepSeek found, that open weights are the sharpest weapon against a leader, eroding its pricing and its lock-in at a stroke under nothing heavier than an MIT license. And the frontier drifts downward on its own, because what costs hundreds of millions to train today becomes a single-digit-million run within a year or two, until the capability that was a state secret in spring is a weekend download by autumn. That is the sense in which no export control proved enough to put the genie back in the bottle in early 2025, and the sense in which it will not this time either. The difference is only that, in the meantime, whoever wants to keep working without asking Washington for permission has to build it at home.

Dr Fable or Mr Mythos?

Fable and Mythos were never two models. They are two names for the same one – the same weights, separated by a layer of classifiers – exactly as Jekyll and Hyde were never two men. The potion that keeps them apart is a guardrail, and Stevenson had already told us how well that kind of separation holds when the thing it contains is powerful enough. Find a vulnerability to close it or to exploit it: same eyes, same code, same hand. The respectable doctor and the dangerous one were always the same person. The only real question the export control raises is who gets to hold the vial – and the Crypto Wars already answered that one, too.

Discuss...

Sources and further reading

On the ban and the official versions

• Axios, Scoop: Trump admin blocks foreign access to Anthropic's most powerful AI – the original scoop; Lutnick's letter to Amodei; administration official on the jailbreak claim and the failed attempt to get Anthropic to pause the release
• Bloomberg, Anthropic Says US Orders Halt to Foreign Access for Fable 5, Mythos 5 AI Models – first publicly deployed model pulled under export controls; US official confirms the Commerce letter
• NBC News, Anthropic suspends new AI models after government directive – Lutnick letter written with help from BIS officials, per an administration official
• CNBC, Anthropic disables access to Fable 5 and Mythos 5 to comply with government directive – 5:21 PM ET; Opus 4.8 unaffected; Project Glasswing context
• Fortune, Anthropic disables Fable and Mythos AI models following U.S. government export ban – ~965 bn $ valuation and confidential IPO; comparison with OpenAI's GPT-5.5; Peter Girnus's “munition” quote
• Anthropic, Statement on the US government directive to suspend access to Fable 5 and Mythos 5 – official position: “misunderstanding”, commitment to restore access, “verbal” evidence of a “narrow, non-universal” jailbreak
• explainx.ai, Why Did the US Gov Ban Fable 5? The Full Anthropic Story – timeline; Amodei's 10 June “Policy on the AI Exponential” essay calling for government authority to block frontier releases
• Tom's Hardware, US government warned Anthropic that Fable 5 had been jailbroken, but firm 'refused' to fix it – David Sacks's account
• Semafor, White House move to limit Anthropic linked to concerns about Chinese access to Mythos – Amazon's role in flagging the jailbreak; Sacks's account
• TIME, Anthropic Pulls Its Most Powerful AI Models After U.S. Bars Foreign Access – Pentagon “supply chain risk” context and international reaction (UK, AI sovereignty)

On deemed export

• University of Washington, Deemed Export Rule – summary of §734.2(b)(2)(ii) EAR
• BIS, Deemed Exports
• UC Santa Barbara Office of Research, Foreign Nationals and Deemed Exports – ordinary use of a controlled item, revealing no technical information beyond the public, does not require a licence

On the jailbreak and the system prompt leak

• Gate News, Claude Fable 5 Breached Within 48 Hours of Release; System Prompt Leaked on GitHub – decomposition technique, “pack hunt”, multi-agent orchestration
• Cybersecurity News, Anthropic's Claude Fable 5 Alleged Jailbreak to Generate Stack Exploits – classifier + Opus 4.8 fallback architecture; 1,000+ hours of bug bounty
• AY Automate, Inside the Claude Fable 5 System Prompt – leak anatomy: 120,040 characters, 72 sections, 18 tools, ~30,000 tokens
• AlphaSignal, Claude Fable 5 Prompt Leak Is a User Manual for Long-Running Agents
• AI Insiders, The Fable 5 leak's real story is 120,000 characters – caveat on unconfirmed authenticity

On the Crypto Wars precedent

• Immunity Networks, Phil Zimmermann: PGP, the Crypto Wars, and the Right to Encrypted Communication
• Reason, When Encryption Was a Crime – source code printed as a book via MIT Press
• Darknet Diaries, Crypto Wars transcript – algorithms on T-shirts as regulated munitions
• Vice, How the Government Is Waging Crypto War 2.0 – Bernstein v. DoJ, “code is speech”, Clinton's executive order 13026

On European AI sovereignty

• Foreign Affairs Forum, The Sovereign Algorithm
• pdpspectra, Sovereign AI in 2026
• Sovereign Magazine, Mistral AI And Europe's Push For Autonomous AI Systems – French military framework agreement, GDPR/AI Act drivers
• Bruegel, Europe needs a strategy to close the artificial intelligence compute gap
• Open Claw News, Mistral AI 830M sovereign data center

On local models and the open-weight way out

• Till Freitag, Open-Source LLMs Compared 2026 – hardware requirements, MoE economics, GGUF quantisation quality; Qwen3.5 122B-A10B on 64 GB
• Will It Run AI, Qwen 3.5 122B-A10B VRAM Requirements – A10B = 10B active of 122B total; quant sizes and Apple Silicon throughput
• InsiderLLM, Best Local LLMs for Mac in 2026 – the shift of defaults from Qwen3.5 to Qwen3.6
• Techzine Global, US blocks Claude Fable 5 and Mythos 5: is frontier AI now too dangerous? – inevitability of open-weight emergence, DeepSeek R-1 precedent
• IISS, DeepSeek's release of an open-weight frontier AI model – commentators questioning whether export controls can contain Chinese frontier progress; controls pushed DeepSeek toward memory optimisation and synthetic data
• Foundation for American Innovation, DeepSeek's Success Reinforces the Case for Export Controls – the opposing view: efficiency gains do not make controls futile

#AI #ExportControl #DigitalSovereignty #OpenSource #Jailbreak #SelfHosting #Mistral #CryptoWars #FOSS #SolarPunk #Writing

A note on method before beginning. The encyclical runs to two hundred and forty-five paragraphs, and the word “dignity” recurs in it one hundred and one times. This is not a stylistic tic: it is the keystone of the entire edifice. And keystones, in a piece of reasoning, are exactly the points that must be tested first – because if that one gives way, all the rest gives way too.

First crack

The whole document rests on two contrasting biblical images: the tower of Babel and the rebuilding of Jerusalem under Nehemiah. On one side the proud construction, the uniformity that flattens, the dominion that dehumanises; on the other the shared labour, each with their own stretch of wall, the communion. Leo XIV says it explicitly in paragraph 9: “the first choice is not between a 'yes' or a 'no' to technology, but between building Babel or rebuilding Jerusalem.”

It is a powerful image, and it works beautifully as rhetoric. As logic, it is a false dilemma – the most classic of fallacies: presenting two options as exhaustive when others exist. But the real trap is not in the bifurcation itself. It is in how Babel is defined. In paragraph 7 we read that the tower is “a work conceived without reference to God.” Keep that sentence in mind, because it does all the dirty work. If Babel is by definition the project built without God, then any secular collective enterprise – any immanent, horizontal, atheist attempt to build a more just world – falls into Babel not for its outcomes, but for its premise. The die is loaded before the throw. We are not choosing between dominion and fraternity: we are choosing between “with God” and “without God,” dressed up as an ethical choice.

The problem is that Nehemiah's Jerusalem refutes the encyclical itself. Reread paragraph 8: the city is reborn “through the shared responsibility of the whole people: priests, artisans, heads of household, women and the young,” each with their own piece of wall, listening to fears, coordinating efforts. Strip away the theological frame and it is the exact description of mutualism. It is bottom-up self-organisation, mutual aid, the federated cooperation that anyone who has spent time with libertarian thought recognises at first glance. The “way of Nehemiah” does not need the Lord at the centre to function: it needs people who trust each other enough to entrust each other a stretch of wall apiece. Which is exactly what the free software communities, the decentralised networks, the commons projects do – without praying to anyone. The encyclical describes the model, admires how it works, and then insists that without God that model would be Babel. It does not prove it. It postulates it.

There is a third city, the one the text erases by definition instead of by argument: the city built together, from below, with no heaven to reach and no one to ask for permission. It happens to be the city some of us have been trying to build for a while now.

Second crack

Let us come to the keystone, the one with the hundred and one occurrences. The anthropological pivot of the encyclical is the concept of “ontological dignity,” set out in paragraphs 52 and 53. It is the dignity that belongs to every human being “simply by the fact of existing, of having been willed, created and loved by God.” A dignity called “infinite” – taking up the 2024 declaration Dignitas infinita – because “infinite is the love of God that calls him to friendship with Him.”

Let us stop on the structure of the argument, because it is a perfect circle. Human beings have infinite dignity; dignity is infinite because God loves them with infinite love; and we know it holds for everyone because everyone is created by God. And there it is: the conclusion is inside the premise. It is a textbook begging of the question: to accept the foundation you must already have accepted exactly what the foundation is supposed to demonstrate, namely the existence and the love of that God. For a believer it is coherent, and that is fine. But the document addresses itself – paragraph 16 – “to all men and women of good will,” claiming a universal validity that its own foundation denies it.

Here the encyclical makes a clever move, and it must be acknowledged. In paragraph 56 it reverses the charge: without a solid metaphysical foundation, it says, human rights become negotiable, and “rights held today to be untouchable may, in the future, end up being called into question or denied by those who hold power.” It is a consequentialist argument – if there is no God, rights collapse – used to prop up a thesis meant instead to be deontological. But it is doubly fragile.

First: it is itself an argument about consequences, not about foundation; it is telling me it is in my interest to believe, not that it is true. Second, and more important: it is simply false that without metaphysics rights are left without ground beneath their feet. Contractualism, the ethics of reciprocity, moral consideration grounded in the capacity to feel and to suffer – all found dignity on intersubjective and verifiable bases, with no need to posit a creator. One can debate which is best. But they exist, they work, and they hold.

The encyclical, however, has already thought about how to neutralise them. In paragraph 133 whoever grounds their values on human reason alone is described as “modern man wrongly convinced of being the sole author of himself,” a victim of “a presumption, consequent upon a selfish closing-in on oneself.” Translated: the secular refutation is not refuted, it is diagnosed as the sin of pride. It is an elegant way of not having to answer.

One could object that the encyclical, elsewhere, grants reason the ability to get there on its own: in paragraph 56 it admits that reason, questioning itself on human nature, “is able to discover values that hold for all.” But it is a poisoned concession. That “human nature” with its objective values already inscribed within is not a neutral secular datum: it is itself a metaphysical construction, natural law presenting itself as self-evidence. And there is worse, because reason is admitted to discover those values only if it arrives at the right conclusion. When it does not get there – when it grounds dignity on bases of its own, without a creator – paragraph 133 kicks in and that same reason becomes “presumption.” You have permission to reason, provided you reason as they do. It is not a shared foundation: it is a confessional foundation with a service door that closes the moment you try to leave it by another way.

Third crack

The technical description in paragraphs 98 and 99 is surprisingly accurate. The idea that modern models are “more 'cultivated' than 'built,'” that developers “create an architecture on which the AI grows,” and that “fundamental scientific aspects – such as the internal representations and computational processes of these systems – remain at present unknown” is simply true, and it is the language of mechanistic interpretability, not of theology. On this, no objection: it is the most honest thing in the document.

The problem comes immediately after, when the correct description is used for an incorrect move. In paragraph 99 it is established that one must “avoid the misunderstanding of equating this 'intelligence' with the human one,” because the systems “do not live an experience, do not possess a body, do not mature in relationship,” and above all “do not understand what they produce.” So far it is a defensible definition. But it is deployed to express a sealed paradigm: whatever a machine does, however sophisticated, “will never be true intelligence” because it lacks the “affective, relational and spiritual” horizon. Every counterexample is excluded by redefining the term in a way that makes it inaccessible by construction. The capacity to compute is there, the sophistication is there, the utility is there – but the soul is not, and the soul is precisely what it had been decided from the start the machine could not have. The conclusion was already in the definitions. Note that I am not claiming the models are conscious: I am saying that an argument that makes its own thesis unfalsifiable is not an argument, it is a definition in disguise.

There is then a cost this move makes the text pay, and it is the most serious. Those verbs – to understand, to know, to create – the encyclical uses as if their meaning were fixed and settled, on one side the machine that does not deserve them, on the other the human who possesses them by right. But that is exactly what today is no longer settled. These systems are putting under pressure the paradigms with which we define knowledge, creativity and relationship, and the scientists who study them know it perfectly well. Whether “to understand” means anything for a machine is an open question: some argue that to predict the next word accurately a form of understanding has to be built, and there is the Othello-GPT experiment – a model trained only on game transcripts, never on the rules, that internally developed spontaneously a representation of the board.

On creativity the confusion is almost comic: one psychometric test places the models in the top one per cent for originality, another finds them lacking precisely in originality – a sign that we do not even know how to measure the boundary we claim to draw. And that the machines are changing the way we think is said by the research on cognitive offloading: those who delegate more to AI show lower critical thinking capacities. On this the encyclical is right, in paragraph 100 it says it almost in the same words. But it is precisely here that the text bites its own tail: a stochastic parrot does not raise the question of what it means to understand – these systems do. It is a phenomenon that forces us to rethink what knowledge and creativity are, and a question of that kind is not dispatched with a definition taken for granted.

Fourth crack

The most refined fallacy of the whole text sits in the paragraphs running from 126 to 128. The encyclical confronts transhumanism – the promise of a technical overcoming of human limits – and opposes to it its own “more than human”: grace, the elevation worked by God in Christ, the “transcending of oneself” that “surpasses the capacity of nature.” I quote 128: “we come to be fully human when we are more than human, when we allow God to lead us beyond ourselves.”

It is an equivocation, in the technical sense: the same label – “more than human” – is applied to two radically incommensurable things, and the two things are then presented as if they competed in the same market. On one side technological enhancement, measurable, in principle verifiable. On the other the transformation by grace, which is an act of faith unverifiable by definition. The encyclical disqualifies the first as Promethean illusion – the self-sufficiency that mimics salvation – and proposes the second as the “authentic” transcendence. But for someone standing outside the enclosure of faith, they are two claims of the same kind: two promises of overcoming, neither of the two demonstrated.

And it is not a forcing of mine to set the two things in competition: it is the text that does it. It is the encyclical that reuses the same formula – “more than human” – for grace; it is the encyclical that presents the desire for overcoming intercepted by transhumanism as an authentic thirst to which only divine transcendence would give the “true” answer. Once you have established that the need is the same and that only one of the two offers is legitimate, the competition is one you have declared yourself.

What remains for me is only to note that the two offers are not of the same order: one promises something measurable, the other something that can only be believed. To treat one as fantasy and the other as reality is not the result of an argument. It is the presupposition from which the argument starts: I convince you that the opponent's pseudo-transcendence is empty, and meanwhile I sell you mine as full.

Fifth crack

Paragraphs 118 to 120 contain the most poetic passage of the encyclical, and it is precisely for this the most insidious. The thesis is that “the human does not flourish in spite of the limit, but often through the limit”: illness, old age, vulnerability, suffering are not defects to be corrected but places in which the human matures.

There is an undeniable psychological truth here: sometimes from suffering wisdom is born, from failure a growth. But observe the slippage. We start from a descriptive claim – from suffering value sometimes derives – and we land on a normative one: therefore to reduce the limit technically is hubris, it is the “purely technical salvation” to be rejected. It is the naturalistic fallacy, but inverted: from the fact that finitude can generate good, it is deduced that intervening to attenuate it is morally suspect. But “suffering sometimes teaches” in no way implies “therefore we must not fight it.” From the observation of a fact no duty follows.

And in paragraph 120 there is the gem that says it all: “to suppress pain entirely one would have, at bottom, to switch off love and desire too.” To the credit of the text, it must be said that the encyclical does not at all deny the duty to heal: the same paragraph 118 acknowledges that “it is a duty to seek to eliminate suffering.” The point then is not whether to intervene, but where the boundary lies between legitimate intervention and the “overreach” to be condemned. And that boundary the encyclical draws without giving us a criterion: aspirin yes, hybridisation no, but in between? Who decides when healing becomes desecrating? Between aspirin and the uploading of the mind into a cloud there is a continuum as long as a life – anaesthesia, vaccines, prostheses, antidepressants, glasses – and without a non-arbitrary criterion that boundary remains a decision, not a deduction. It is worth recalling, in passing, that it is exactly the logic of the “natural limit not to be desecrated” that has historically been used against obstetric anaesthesia, contraception, assisted reproduction. Every time, today's limit was sacred until someone crossed it; and the day after no one dreamed of putting it back into question.

Sixth crack

This is less a single fallacy than the load-bearing structure of two entire chapters. The first and second chapters – from paragraph 28 to 89 – are a long chain of references: Leo XIII, Pius XI, Pius XII, John XXIII, Paul VI, John Paul II, Benedict XVI, Francis. Every thesis is anchored to a predecessor, in a line that feeds itself.

It must be said with precision, because here it is easy to miss the mark: inside the Catholic system, the continuity of the Magisterium is not a fallacy, it is the criterion. For a believer, the fact that a doctrine has been coherently held by eight pontiffs across some hundred and fifty years is a legitimate argument, because the authority of that tradition is an accepted premise. The problem arises at the exact moment the encyclical leaves the enclosure and addresses everyone – believers and not – claiming universal validity. There the argumentum ad verecundiam becomes visible: the chain of citations counts as proof only for those who recognise the authority of the chain. For everyone else it is a circle closing on itself, imposing as you like, but self-referential. Eight popes agreeing with one another do not constitute a proof for anyone who recognises in none of the eight the right to pronounce.

Water to one's own mill

There remains the question I was posing at the start: is it simply “bringing water to the Church's mill,” or is there something more?

It is water to the mill in the structural sense of the term, and you can see it with the naked eye once you have isolated six (there are probably more) cracks. The scheme is always the same, repeated chapter after chapter: a shareable secular diagnosis – technocratic power, exploitation, algorithmic dehumanisation – channelled towards a non-negotiable confessional therapy. A diagnosis I would sign, but a solution I cannot accept without first accepting the theological premise. The fifth chapter, on war, repeats verbatim the binary structure of the introduction: “culture of power” against “civilisation of love,” Babel against Jerusalem under other names. The rhetorical machine is the same, oiled and tireless.

But it would be short-sighted to stop here, and I refuse to do so for three reasons.

The first is that the diagnosis is solid, and as such it makes the encyclical a tactical ally. When Leo XIV writes, in paragraph 108, that “small, very influential groups can orient information and consumption, condition democratic processes and bear on economic dynamics to their own advantage,” he is saying something true and saying it from the most listened-to pulpit on the planet. When, in 109, he recognises “the invisible, often exploited, labour that feeds the algorithmic models” – the data labellers of the Global South paid a pittance to train our chatbots – he is doing materialist critique, not catechism. On this terrain we are on the same side of the barricade.

The second is that there is at least one point where the encyclical leaves its own mill and applies its principles to itself. In paragraph 89 there is talk of “listening to the victims of spiritual, economic, institutional, sexual abuse, of power, of conscience” within the Church, with “the recognition of the harm, the just reparation and the prevention.” It is little, it is late, and it is written in the velvet language of the Curia. But it is dialectically honest: it is not water to the mill to admit one's own structures of sin, and it is right to give credit for it – while knowing that one entry in a list is not yet a reckoning, and I will return to this at the end.

The third is that behind the document there is a real operation of power, and not at all naive. In a global regulatory vacuum on AI – where states limp along and civil society struggles to find a voice – the Church puts itself forward to fill the space as a planetary moral authority. It does so, intelligently, by lining up against the private power of Big Tech, which makes it attractive to anyone who criticises that power. It is, in its way, a textbook move: occupy a terrain that others have left undefended. That it is then a terrain on which we too would like to build something – a collective governance of technology, data as commons, slowing down where everything accelerates – is precisely what makes the encyclical so slippery. It agrees with you on the destination for five-sixths of the journey, and then at the last fork it turns one way only.

Conclusions

Every fallacy I have listed, taken on its own, could be a stumble. Taken together, they design a method. They are not the errors of sloppy reasoning: they are the devices of an extremely careful reasoning, and each one performs the same precise function. They serve to make a diagnosis the secular reader shares converge towards a conclusion that, without the premise about God, they would have no obligation to accept. The false dilemma closes off the alternatives from the start; the begging of the question on dignity makes faith the only admissible foundation; the equivocation on “more than human” disqualifies every competing transcendence; the naturalistic fallacy turns the limit into a duty; the appeal to authority closes the circle. Take away God, and the argument does not hold – and it is built on purpose so that you, to make it hold, must put God back in.

This does not make it a bad document. It makes it a partisan document pretending not to be one, which is a different thing. Magnifica Humanitas is excellent sociology, magnificent rhetoric, and logic that limps exactly – and only – at the points where the supernatural has to be let in. The technical part on AI, the one written with the contribution of those who actually study the models, is the most solid and the least ecclesial. The anthropological part, the one on which all the rest rests, is the most fragile. It is no accident: it is where the text has to do the work it cares about most.

As an atheist who shares half the premises and none of the conclusions, the same question remains that I ask myself every time someone describes to me a just city and then explains that I cannot build it without their god. Quoting Eric Raymond, I have seen the Bazaar – and not the Cathedral – work. I have seen it work in free software, in the networks that have no master, in the communities that hold themselves together through mutual aid. I have seen it work even without a god. The question I leave open, then, is simple: if we raise the wall just the same, each with our own piece, listening to one another and trusting one another – who said there must necessarily be someone up there at the centre? And what if we noticed it held up perfectly well without?

A small postscript: someone will object that the encyclical does have courage – it asks forgiveness for the delay with which the Church condemned slavery. True. But it is the most comfortable forgiveness there is – for a fault of eighteen centuries ago, which touches no living bishop. On the abuses of today there remains one line, one entry in a list of six in paragraph 89. This is why I insist: lining up against techno-capitalism, artificial intelligence and transhumanism is today a very intelligent social and political positioning to take, but really a very uncourageous one. If I may advise Leo XIV something truly courageous, let him try to write an entire encyclical against paedophilia in the Catholic Church. I will gladly offer myself as first reader.

Sources and further reading

The document – Leo XIV (2026). Encyclical Letter Magnifica Humanitas on the guardianship of the human person in the time of artificial intelligence. Full text. – Dicastery for the Doctrine of the Faith (2024). Declaration Dignitas infinita on human dignity.

The tradition invoked (to find your bearings in the magisterial chain) – Leo XIII (1891). Rerum novarum. – Second Vatican Council (1965). Pastoral Constitution Gaudium et spes. – Francis (2015). Laudato si'. – Francis (2020). Fratelli tutti.

On logical fallacies (general references) – Walton, D. (2008). Informal Logic: A Pragmatic Approach. Cambridge University Press. On the false dilemma, the argumentum ad verecundiam and the slippery slope as argumentation schemes and on their legitimate and illegitimate uses. – Hume, D. (1739). A Treatise of Human Nature, book III. The classical formulation of the distinction between is and ought, at the root of the so-called naturalistic fallacy.

Secular foundations of dignity and rights (the alternatives the encyclical pre-disqualifies) – Rawls, J. (1971). A Theory of Justice. Harvard University Press. The contractualist foundation of justice without metaphysical presuppositions. – Singer, P. (1979). Practical Ethics. Cambridge University Press. Moral consideration grounded in the capacity to feel and to suffer. – Nussbaum, M. (2006). Frontiers of Justice. Harvard University Press. The capabilities approach as a basis for human dignity.

On AI interpretability (the most solid technical core of the document) – Olah, C. et al. (2020). “Zoom In: An Introduction to Circuits”. Distill. On why the internal representations of models remain largely unknown even to those who build them.

On the knowledge / understanding debate in LLMs (the paradigm revision) – Bender, E. M., Gebru, T. et al. (2021). “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?“. FAccT '21. The text that coins the “stochastic parrot” metaphor: a system trained on form alone cannot access meaning. – Li, K. et al. (2023). “Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task”. ICLR. The Othello-GPT experiment: a model that internally builds a representation of the board without ever having seen its rules. – Tayyar Madabushi, H., Torgbi, M., Bonial, C. (2025). “Neither Stochastic Parroting nor AGI: LLMs Solve Tasks through Context-Directed Extrapolation”. The middle position: capacities that go beyond the parrot but remain predictable and not assimilable to human cognition.

On computational creativity (and on how uncertain the boundary is) – Boden, M. (2004). The Creative Mind: Myths and Mechanisms, 2nd ed. Routledge. The founding distinction between combinatorial, exploratory and transformational creativity. – Guzik, E. et al. (2023). “The originality of machines: AI takes the Torrance Test”. Journal of Creativity. GPT-4 in the top 1% for originality and fluency. – Lu, Y. et al. (2025). “Assessing and Understanding Creativity in Large Language Models”. Machine Intelligence Research. The opposite result: LLMs excel in elaboration but are lacking precisely in originality.

On AI's impact on human cognition – Gerlich, M. (2025). “AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking”. Societies, 15(1): 6. Negative correlation between frequent AI use and critical thinking, mediated by cognitive offloading. (The author warns: correlation, not causation.)

On power embedded in technological choices – Winner, L. (1980). “Do Artifacts Have Politics?”. Daedalus, 109(1): 121-136.

#MagnificaHumanitas #LeoXIV #Encyclical #AI #Atheism #LogicalFallacies #FreeSoftware #Commons #Mutualism #Philosophy #Writing

To understand how two worlds this far apart – the guitar and the ribosome, the double bass drum and the DNA – ended up in the same track, you have to start from a biographical detail almost nobody knows. Tuomas Holopainen, the man who has always written Nightwish's music, studied biology before becoming a full-time musician.

Then the band's first record, Angels Fall First, took off and tipped another life over onto him. The degree stayed a road not taken. But some passions don't leave: they settle to the bottom and wait. When the time came for the eighth album, in 2015, Holopainen reached back down to that bottom and pulled up an idea: to write a monumental song about the evolution of life. He wanted to title it after a book he loved, The Greatest Show on Earth by Richard Dawkins. But before getting to that song, it helps to understand who Nightwish really were, and why they of all bands could conceive of such an idea.

https://inv.nadeko.net/embed/qrMwxe2ya5E

Nightwish, or how to tell a story with a distorted orchestra

For anyone who doesn't follow the genre, an introduction is in order. Nightwish were born in Finland in 1996 and became, within a few albums, the reference band for a current they helped to define: symphonic metal. The idea, seemingly contradictory, is simple: take the power of metal – distorted guitars, double bass drum, massive sonorities – and make it live alongside the arsenal of classical music: orchestra, choirs, a female voice often of operatic training. The result is not a watered-down compromise but a dramatic, almost cinematic form, built to tell big stories. Nightwish songs are routinely little soundtracks to films that don't exist.

Holopainen, the keyboardist and composer, is its sole mind: he writes music and lyrics and conceives each record as a unified work, to be heard from beginning to end the way you watch a film. This obsession with storytelling explains why, sooner or later, an album about evolution had to come: for an author like this, the history of life on Earth is not a theme, it is the theme, the greatest screenplay available.

Then there is the question of the voice, which in Nightwish has never been a detail. At the origin of it all is Tarja Turunen, an operatic soprano trained at the prestigious Sibelius Academy, who founded the band in 1996 together with Holopainen and guitarist Emppu Vuorinen. Nightwish did not invent the marriage of a female voice and metal out of nothing: they arrived in the wake of a European flowering that, in the mid-Nineties, was redefining the genre – from The Gathering's Mandylion (1995), with the voice of Anneke van Giersbergen, to the Swedes Therion who orchestrated metal with operatic choirs, to their fellow travellers Within Temptation and, later, After Forever and Epica. But it was Nightwish's formula – Tarja's operatic, dramatic, classically schooled voice laid over fast, cutting guitars – that gave symphonic metal its most recognisable incarnation. For nearly a decade Tarja was the face and the voice of the group, through the albums that made them famous across Europe, up to the triumphant Once of 2004. Then, in October 2005, came the most spectacular rupture in the history of the genre: a wound that marked the band for years and that Holopainen would later transfigure into music.

In the years that followed, the voice of Nightwish became a chapter in continuous rewriting. Tarja was succeeded by the Swede Anette Olzon, with a more pop and rock timbre. But that chapter too closed abruptly: when, halfway through the 2012 tour, Olzon left the group suddenly, Holopainen found himself without a voice midway through. The solution came in the most rocambolesque manner: they called the Dutch singer Floor Jansen – already known in metal for After Forever and ReVamp – while she was at her sister's wedding. A few hours later she was on a plane, and with two days' notice she stepped onto the stage in Seattle to sing a repertoire she barely knew. The pressure of that feat is documented in the documentary Please Learn the Setlist in 48 Hours, whose title already says it all.

Jansen did not merely save the tour: she dominated it. The audience adopted her instantly, and in 2013 she became a permanent member. But there was a loose end: live she was already a legend, in the studio with Nightwish she had not yet recorded a note. Endless Forms Most Beautiful, from 2015, is her first studio album with the band, and it is here that “The Greatest Show on Earth” takes on a second meaning, parallel to the scientific one. Floor Jansen possesses one of the most versatile voices in contemporary metal – she moves from operatic soprano to aggressive growl within the span of a single verse – and those final twenty-four minutes are the proving ground on which she displays the entire range. For many listeners, the real “evolution” the record told was also that of the band itself, which after years of vocal turmoil was finally finding its most accomplished form. (A small note for those who know certain territories: Jansen is also at home in the universe of Arjen Lucassen, having sung in Ayreon and Star One – another place where science fiction and science become matter for electric orchestras.)

So here is the band – the composer-narrator obsessed with total storytelling, the voice capable of staggering vocal range – ready for the most ambitious record of its career. Only one thing was missing: convincing a biologist to come aboard. And how Holopainen pulled it off is the best part of the story.

A handwritten letter

Instead of settling for the borrowed title, Holopainen decided to ask Dawkins himself to take part in the record. And the way he asked says everything about the respect at stake. No email, no agents, no press office. Holopainen took pen and paper and wrote by hand, because – he reasoned – a handwritten letter has a better chance of being read. He explained the project, the album about evolution, the track that would carry the title of one of Dawkins's books, and asked whether the professor might like to recite a few passages on the record.

Dawkins, for his part, had not the faintest idea who Nightwish were. He admitted it with disarming candour: he had long forgotten even how to write a letter by hand, he joked, and he had never heard of the band. But his assistant had, told him they were very good, and that was enough. Two weeks later, the reply arrived by email. It was a yes.

Let's pause a moment on the image: on one side a musician who, to chase his own old scientific passion, uses artisanal care to write a letter with the candour of a pupil; on the other a scientist who agrees to step into a territory he completely ignores, trusting the idea. Neither of the two was after a stunt. They were seeking each other out on common ground.

An hour in the studio, thirty fragments

The technical part of the collaboration was surprisingly brief. Dawkins spent a single hour in an English studio recording his contributions. In those sixty minutes some thirty spoken passages were laid down. Holopainen took them home and did the work a composer does: he chose the ones that fitted best with the music, discarded the others – or rather, did not really discard them, because some later ended up in the live performances. But there is a detail that deserves attention: the music had already been written and defined note by note, before Dawkins ever opened his mouth. And Holopainen deliberately chose not to adapt anything to the professor's voice: he wanted that voice as it was, with no made-to-measure seams. Precisely for this reason Dawkins's presence turned out more powerful. Not a guest put at ease, but a real voice left free to merge with the music according to its own nature. It is the same logic with which a naturalist films an animal without taming it.

The man on the other side of the envelope

So far we have followed the story from Nightwish's side. But who was the man who received that letter, and why is his presence no ordinary cameo? Richard Dawkins, born in Nairobi in 1941 and educated at Oxford, where he took his biology degree in 1962 and his doctorate, is one of the most influential living evolutionary biologists. Not for his laboratory discoveries, however, but for something rarer: the ability to rewrite the way we think about evolution and to communicate it to millions of people.

The book that made him famous, The Selfish Gene of 1976, proposed a reversal of perspective. Until then the tendency had been to imagine that natural selection worked for the good of the species or the group. Dawkins shifted the focus onto the gene: the fundamental unit on which evolution acts, he argued, is not the individual nor the species, but the gene itself, which uses organisms – ourselves included – as “survival machines” to perpetuate itself. It is in the same book that Dawkins coined a word we all now use without thinking: meme, the unit of cultural evolution, the idea that replicates and spreads as a gene does. Few in the world have known, as he has, how to distil complex scientific concepts into limpid and impassioned prose, turning biology into a narrative capable of moving us. It is an attitude that to Holopainen must have rung familiar, because it is exactly what Nightwish do with music: take something vast and make it palpable. The Greatest Show on Earth, the 2009 book from which the track takes its title, is at bottom a great act of popularisation – an impassioned gathering of the evidence for evolution.

What the track is really about

What remains is the twenty-four minutes – the place where all this, finally, takes sound. It is the longest song Nightwish have ever written, and the mixing alone of that piece took two and a half weeks. But the length is not ostentation: it is the time needed to tell the story the track sets out to tell, namely everything. Literally everything, from the birth of the planet to a future we do not know.

The track is divided into five chapters, and follows an arc that is at once cosmological and biological. It begins in silence, the same silence of the universe before the Big Bang. Then a few piano chords emerge, scattered, with no apparent melodic logic: the universe before time, before the rules exist. After about a minute and a half, the explosion. And only around the fifth minute does life appear – and it is there that Dawkins's voice comes in, in the role that suits him most naturally: that of the narrator who walks us into natural history.

From there the lyrics become a small poetic compendium of science. There is the Earth forming in the “Goldilocks zone”, the orbital band neither too hot nor too cold where life is possible. There is LUCA, the Last Universal Common Ancestor: that single organism from which, according to the best reconstructions, every living thing on Earth descends, from the bacterium to the whale. There is the long march of chemistry becoming biology, of those “endless forms most beautiful” that give the whole album its title.

And it is here that the literary circle closes, because the story is not only about Dawkins. That phrase, “endless forms most beautiful”, is not Dawkins's: it is Charles Darwin's, and it is the dazzling closing line of On the Origin of Species. The album and the track thus rest on a double root – the nineteenth-century founding father and his most celebrated contemporary interpreter – and Dawkins enters the record not as a provocateur, but as the link connecting Darwin's voice to our ears. A curiosity within the curiosity: Holopainen had thought of titling the whole album The Greatest Show on Earth, then found it too pompous and kept that title only for the closing track, leaving to Darwin's phrase the honour of the cover.

Why this story matters

One could dismiss the episode as an oddity, a curiosity for an encyclopedia of rock, but that would be a mistake. Dawkins has always maintained that science ought to be a source of inspiration for musicians, exactly as love, death or war are. Nightwish proved him right in the most concrete way possible: by taking evolution – the grandest story our species has ever assembled – and treating it for what it is, a story worthy of twenty-four minutes of symphonic music.

Marko Hietala, at the time the band's second voice, called the track “probably the culmination of everything we've done together”. He was right.

Sources and further reading

• Nightwish, Richard Dawkins and Endless Forms Most Beautiful (Prog / Louder Sound, 2015). Primary source for the handwritten-letter story, Holopainen's biology background, Dawkins's “I'd never heard of Nightwish” admission, and the Wembley performance. https://www.loudersound.com/features/nightwish-richard-dawkins-endless-forms-most-beautiful
• VIDEO: Nightwish discuss working with Prof Richard Dawkins (Metal Hammer / Louder Sound, 2015). Holopainen and Floor Jansen on the handwritten letter and on Darwin and Carl Sagan as further inspirations. https://www.loudersound.com/features/video-nightwish-discuss-working-with-prof-richard-dawkins
• Behind the scenes with Nightwish at Wembley Arena (Louder Sound, 2016). On Dawkins's first-ever rock concert appearance at Wembley. https://www.loudersound.com/features/behind-the-scenes-with-nightwish-at-wembley-arena
• Endless Forms Most Beautiful (album) (Wikipedia). Background on the 2015 album, its Darwinian and Dawkinsian inspiration, and Dawkins's spoken-word contribution. https://en.wikipedia.org/wiki/Endless_Forms_Most_Beautiful_(album)
• Richard Dawkins (Wikipedia). Biography: Nairobi 1941, Oxford, Niko Tinbergen, The Selfish Gene (1976), the coining of “meme”, The Greatest Show on Earth (2009). https://en.wikipedia.org/wiki/Richard_Dawkins
• Tarja Turunen (Wikipedia). Founding of Nightwish in 1996, the Sibelius Academy training, the October 2005 dismissal. https://en.wikipedia.org/wiki/Tarja_Turunen
• Mandylion (Wikipedia). The Gathering's 1995 album with Anneke van Giersbergen, a foundational record of the female-fronted European scene. https://en.wikipedia.org/wiki/Mandylion_(album)
• Please Learn the Setlist in 48 Hours – documentary on Floor Jansen's emergency debut with Nightwish in 2012. http://invidious.nerdvpn.de/watch?v=vhExkmWKMEU

Discuss...

#Nightwish #RichardDawkins #Evolution #SymphonicMetal #Metal #FloorJansen #TarjaTurunen #Darwin #Science #ScienceCommunication #TheGreatestShowOnEarth #EndlessFormsMostBeautiful #Music #Atheism #Writing

The Metropolitan Police, for the first time in a public-order operation, formally deploys live facial recognition. Cost of the operation: 4.5 million pounds. The British government – “still” Labour, remember – has barred from entry eleven figures of the international far right who were due to speak at the rally: among them Polish PiS politician Dominik Tarczynski, Flemish Filip Dewinter of Vlaams Belang, the Dutch Eva Vlaardingerbroek (a polemicist close to the MAGA scene), and Senate MAGA candidate for Missouri Valentina Gomez, known for declaring publicly that Britain is “under the control of Muslim rapists protected by Premier Starmer”.

Robinson is not a 2026 improvisation. He founded the English Defence League in 2009 – seventeen years ago. He has been convicted of fraud, violence, and contempt of court. And in recent months he has toured the United States, where he was received at the Department of State, spoke about an “Islamic invasion” at the University of Florida, and appeared on all the major MAGA-right podcasts. Saturday's London march is not an isolated British event. It is a local node of a transatlantic and transcontinental network that has turned the European, American and Iranian-monarchist far right into a single political machine. In short: fascists meeting other fascists.

Geography, then

But on Saturday I was not in London. I was in Gourock, on Scotland's west coast, twenty-five miles from Glasgow, having a coffee in a café and watching the Clyde estuary and the ferries crossing to Dunoon. The geographical distance between central London and Gourock is roughly 770 kilometres. The political distance is considerably greater.

Seen from outside, England and the United Kingdom tend to be used as synonyms. They are not. The UK is not one country but at least two – plausibly four – and the two main pieces are diverging at a speed that will be hard to reabsorb. Scotland did not vote for Brexit (62% Remain, 38% Leave), is not voting for Reform UK, and has just elected, on 7 May, a parliament in which an explicit cordon sanitaire against the far right exists – something that no longer exists at Westminster. To convey what that feels like in daily life, I have to tell you two small episodes, separated by almost a decade, that happened less than an hour by train from each other.

A handbag in Linlithgow

24 June 2016, the morning after the Brexit referendum. I was living then in Linlithgow, a small town in West Lothian best known as the birthplace of Mary Stuart (Queen of Scots) and of Montgomery Scott (“Scotty” of Star Trek), halfway between Edinburgh and Glasgow.

I was queueing at the Tesco checkout with the weekend shopping. The BBC was announcing the final results: 52 to 48 for Leave at the British level, but 62 to 38 for Remain in Scotland. Scotland had voted unequivocally against Brexit and had found itself dragged out of the European Union by the English and Welsh vote. In front of me in the queue, two men in their fifties were sizing me up. One looked at the other, and then, looking me in the eye with a bully's smile, said, out loud:

“Adios amigos.”

I paused a second – the time to register what was happening – and answered him in clean English:

“Adios is Spanish. Before you insult someone, you should know what language they speak.“

Behind me in the queue was an elderly Scottish lady, grey hair, leather handbag under her arm. She had seen everything. She took a step forward, raised the bag with surprising speed, and caught one of the two square in the chest, saying:

“Go away, you fud!” (fud = jerk, stupid, asshole, in Scots)

Then she turned to me and said:

“I'm so sorry. Are you ok? They don't represent us. They don't represent Scotland.“

I have often retold that scene to friends in the years since. It already seemed to me then a compressed icon of a whole country. Ten years later, it seems something more: a historical document. That morning, in the thirty seconds in front of a supermarket till, the two nations that Brexit had just revealed and separated passed in front of me. The Britain of the adios amigos – authorised by seventeen million votes to say out loud what before was said under one's breath. And the Scotland of the handbag – an elderly woman, working-class, who took on herself the responsibility of apologising for them, for us, as if it were her personal business to prevent her nation from being represented by those two.

The detail that still moves me is that they don't represent us. She could have disowned the two as compatriots – said “they are not Scottish”, washed her hands. She did the opposite. She claimed them as ours in order to disavow them. It is the exact opposite of the gesture the two were making toward me, trying to disown me as a non-compatriot. She was trying to recognise them in order to say: this is not our nature. Two opposing gestures of citizenship, in the same minute, in the same supermarket.

A whisper at the Edinburgh border

Jump forward in time. February 2025. Edinburgh Airport, arrivals hall, returning from a short trip to Italy. I queue in front of the automatic passport gates – the ones that scan your photo and let you through. The machine, for some technical reason, does not recognise mine. I am directed to the manual desk where a Border Force officer is waiting – a woman in her forties, black uniform, neutral service expression.

She asks me, in a professional tone:

“Are you here for a short visit?“

I reply:

“No, actually, I'm coming home. I've been living in the UK since 2013.“

Her face changes slightly.

“What do you do?“

And me:

“I'm a Linux platform engineer. I work for a Scottish public body.“

And here the thing happens. Her face opens into a real smile – not the service one. She hands me back my passport and says:

“Welcome back.“

As I am putting the passport back in my wallet, she looks at me, lowers her voice slightly, and says:

“And fuck Farage.“

I laugh. I reply:

“Yeah. Fuck Farage.“

She smiles, gives a small nod, and I walk off toward baggage reclaim.

I sit on a bench, in disbelief. She was a state officer on duty, in uniform, at her workplace. The people trained for that role are explicitly instructed not to express political opinions to the public – it is considered professionally improper. And at the border, of all places, the border, the exact point where national identity expresses itself as institutional gatekeeping, where the hostile environment policy introduced by Theresa May in 2012 manifests in flesh and blood with the stamp that decides who is in and who is out. Of all places…

In that place, she read who she had in front of her – an Italian living here for thirteen years, employed by a Scottish public body, returning from a European trip – and decided that professional protocol could give way to political recognition. She recognised me as one of hers. The difference between 2016 and 2025 is striking. In 2016 I was the object of the defence – the lady was intervening for me. In 2025 I was a participant in the joke – the guard was not defending me, she was sharing with me a joke about a common enemy. It is a complete arc of citizenship, even though legally I have remained Italian with Settled Status, keeping jealously in my pocket my burgundy passport with the eagle on the cover.

What happened to England, 2012–2025

Between those two episodes a decade passed, and during that decade England did particular things. Some of the chronology will be familiar to British readers; others, even British, may not have connected the points the way the sequence connects them.

In 2012 Theresa May – then Home Secretary in the Cameron-Clegg coalition – introduced explicitly what has gone down in history as the hostile environment policy. It is a profound paradigm shift: instead of leaving the control of irregular migrants to the police alone, the British state decides to make it mandatory for employers, landlords, banks, hospitals, schools and universities to verify migration status before delivering any service. The stated idea is to make the lives of irregular migrants so difficult that they “self-deport”. It is distributed administrative racism, in which every British citizen is enlisted as a passive border agent. Landlords risking up to five years in prison if they let to someone without the right paperwork. NHS doctors required to bill foreign patients before treating them. Teachers required to flag children whose status they suspect.

Six years later, in 2018, the Windrush scandal broke. It emerged that the hostile-environment machine had systematically deported, deprived of work, excluded from medical care, and pushed into poverty thousands of black British citizens of the Caribbean generation who had legally arrived in the country between the 1940s and the 1970s. Their crime was that the British state had destroyed their archival documents in 2010 – and then demanded that they prove themselves British. Stories are told of people in their sixties and seventies, lifelong NHS workers, who find themselves without homes or salaries because they cannot retrieve school records from the Sixties. This is the hostile environment applied. It is not a theory; it is an administration.

In 2024 Labour returned to power with Keir Starmer. We all thought – on the continent – that the pendulum would swing. It has swung, but not in the expected direction. Shabana Mahmood, Labour Home Secretary, presented in 2025 an immigration White Paper which she herself describes as “the most sweeping asylum reforms in modern times”. The qualifying period for Indefinite Leave to Remain – the British equivalent of permanent residency – is doubled from five years to ten for new arrivals. Refugee status becomes temporary and revocable. The English requirement for ILR goes up from B1 to B2. It is Labour delivering the toughest asylum reform in recent British history. Hard to credit if you read about it from the continental press, but that is how it stands.

They are doing it because Reform UK – the party of Nigel Farage, an evolution of the Brexit Party, in turn an evolution of UKIP, fascists in short – has reached first place in national polls. YouGov, September 2025: Reform at 27%, against Labour at 21% and Tories in free fall. Reform's programme is explicit and published on their own site: complete abolition of Indefinite Leave to Remain (i.e. transformation of permanent residency into a series of periodic renewals for everybody), mass deportations of all irregulars, withdrawal from the European Convention on Human Rights, drastic reduction of naturalisations. Ipsos, August 2025: immigration is the British public's first concern at 48%, ahead of the economy (33%) and the NHS (22%). The Overton window has moved in metres, not in centimetres, and Labour is busy chasing Reform on the terrain of immigration instead of contesting the frame in which Reform has already won the cultural battle.

A last piece needs to be added that is essential to understand the present moment. After the Southport riots of August 2024 – when a young British man of Rwandan origin stabbed three little girls at a dance class, triggering a week of anti-Muslim disturbances across the United Kingdom – a unifying slogan emerged that fused Robinson, the Trump administration, JD Vance and Elon Musk into a single rhetorical line: two-tier policing, two-tier Britain. The thesis is that British justice is more severe toward white Christians than toward Muslims and migrants, creating a “two-tier Britain” in which natives are second-class citizens in their own country. The slogan is patently false – the Office for National Statistics figures show the opposite – but it has worked as a mass rhetorical device, and it is the frame through which Saturday's London march publicly justified itself. It is the key conceptual piece of the moment.

What happened to Scotland

Now the comparison. Scotland, until 7 May 2026, was still a political exception protected more by electoral geography than by culture – the SNP in government for nineteen years, a population voting consistently Remain, a robust civil society that mobilises tens of thousands of people in anti-fascist marches, a small but combative independent press. On 7 May the Holyrood elections crystallised a picture that surprised even the most attentive observers. John Swinney's SNP won with 58 seats, losing six on 2021 but remaining by far the biggest party. The Scottish Greens went from 7 to 15 seats, winning constituency seats (the first-past-the-post kind, as opposed to regional list seats) for the first time in their history – at Edinburgh Central and Glasgow Southside. Labour held at 17, down. Reform UK entered the Scottish parliament for the first time with 17 seats – all from the regional list, none won at constituency level. SNP plus Greens makes 73 seats out of 129: the widest pro-independence majority ever at Holyrood since 1999.

But the most important figure is not this. Swinney declared at his press conference, the day after, a sentence that is no longer said at Westminster: “I will talk to all other parties, with the exception of Reform”. He said it clearly, without euphemism. That sentence defines an explicit cordon sanitaire – the thing that English Labour has not done and probably never will, busy as it is contending with Reform for an electorate it has culturally surrendered to.

There is a legal and cultural framing that supports the cordon. In 2024 the Scottish parliament passed the Hate Crime and Public Order (Scotland) Act – a law that explicitly criminalises incitement to racial and religious hatred, with an application that has been anything but uncontroversial (J.K. Rowling has been a vocal critic) but which exists as a normative baseline that the rest of the United Kingdom lacks. The Scottish government runs a programme called New Scots for refugee integration, explicitly promoted as public policy. The contemporary Scottish identity has been built, from the 1980s onwards, on an active opposition to Thatcherism, to metropolitan imperialism, to the racism of the Daily Mail. So it is not nature – it is recent historical construction, and as such it is fragile, but real.

It must be said, so as not to slide into romanticism, that Scotland is not 1970s Sweden. Reform took 17 seats here too. Anti-migrant protests outside the hotels housing asylum seekers in smaller centres – Erskine, Falkirk, on the edges of Glasgow – have become routine in the last two years. Police Scotland in 2024-2025 recorded an increase in racist offences, which now account for 60% of all hate crime in the country. Anti-Irish Catholic sectarianism is a historical constant of the western belt of Glasgow, and it flares up regularly during the Old Firm football derbies. But the structural difference is there, it is legible, and it is written not only in votes and laws but also in small daily episodes.

On skin: five years in Sheffield

Between 2018 and 2023 I lived in Sheffield, South Yorkshire, for work. Sheffield is one of the most contradictory cities of the English north: historical capital of the City of Sanctuary movement for refugees (founded right there in 2007), but surrounded by ex-pit towns where Brexit won decisively, where Reform is becoming the first party, where the post-industrial economy never recovered from the closure of the mines in 1984. Cosmopolitan city centre, suburbs and belt another country.

Those five years I felt them on the skin, before I felt them in my head. Somatic knowledge always precedes the analytical kind – the body registers patterns of exposure and caution that the mind has not yet finished organising. It was the difference between speaking Italian on the phone on the 52 bus in Sheffield and on the tram in Glasgow. Between the where are you from said as gatekeeping in a Manchester pub and the where are you from said as curiosity in a pub in Lanark. Between deciding every morning how much caution to put into your accent at the supermarket, and feeling that caution was not necessary. Small details, individually trivial, statistically overwhelming.

Despite this, I was protected and I was among expats: my team leader was a Pole, my colleague a Spaniard, a dear friend an Italian. And a kind lady – South African – from the finance team had a soft spot for me. But it was not “home”. In 2023 I changed job and went back to Scotland, and this April I closed my “emigration” with steps I had not thought possible before. My tree puts down roots.

Two kinds of people

We left the lady in Linlithgow, in June 2016. The woman with the bag, the two fools, the they don't represent us. It has come to me, in the last few hours, to think about that scene while watching the images of Robinson's march scroll on the social feeds. The Linlithgow lady was already, without knowing it, the Scotland that ten years later would win the election against Reform. Her handbag was already constitutional politics, before being a private gesture. Swinney declaring “all parties except Reform” is the same thing, done by a much younger person, in a suit and tie, formalised at a press conference – but it is the same thing.

Societies recognise themselves in the moment they choose how to treat their own abusers. A society that defends them, justifies them, courts them, copies them in order to intercept their vote – is a society in which the two at the Tesco become the majority, then a party of government, then a rally with MEGA caps in the heart of the capital, with wooden crosses and “future for white people” on the leaflets. A society that publicly disowns them, excludes them from institutional dialogue, faces them in the streets with the largest anti-fascist demonstration in recent history (the Together Alliance march of this past March, of which the continental press of course barely wrote a word) – is a society in which the lady of Linlithgow is not a folkloric exception, but a structural political possibility.

Scotland is not better than England. It is different. Very different. Its choices over these years – the SNP, the Greens, independence as horizon, Europe as desire, the Hate Crime Act as baseline – are not nature but political decisions taken repeatedly, until they have become collective identity. A fragile, contested, reversible identity – but real.

My grandmother used to say that there are two kinds of people you don't shake hands with: the stupid and the fascists. My grandmother would have loved the Scots.

Sources and further reading

On Saturday's march and the transatlantic far-right network

• CBS News (2026). Thousands hit London streets for “Unite the Kingdom” march organized by far-right activist Tommy Robinson. Reportage on the day, with police estimates of around 60,000 attendees, framing of the rally as “protest against the erosion of British identity”, and account of Robinson's State Department visit. https://www.cbsnews.com/news/london-unite-the-kingdom-march-tommy-robinson/
• Al Jazeera (2026). Tens of thousands march in London in far-right and pro-Palestine protests. The parallel Nakba Day march, the 11 foreign nationals barred from entry, the Met's biggest public order operation in years. https://www.aljazeera.com/news/2026/5/16/tens-of-thousands-march-in-london-in-far-right-and-pro-palestine-protests
• Center for the Study of Organized Hate (2026). London's “Unite the Kingdom” Rally and the Transatlantic Far-Right Playbook. The most useful analytical piece on the rally as a node in a wider international network – documents the “Make Europe Great Again” preparatory meeting in Paris, the Patriotic Alternative Facebook posts revealing the openly Nazi tail of the mobilisation, the saturation of the Robinson-Vance-Musk axis. https://www.csohate.org/2026/05/12/unite-the-kingdom-rally/

On the Hostile Environment, Windrush, and the trajectory of UK immigration policy

• Hostile environment policy (Wikipedia). Good entry point for those approaching the concept for the first time, with the 2012-2018-2024 chronology, primary sources from Hansard, and the connection to Windrush. https://en.wikipedia.org/wiki/Hostile_environment_policy
• Windrush scandal (Wikipedia). Reconstruction of the scandal, of the parliamentary inquiry, of the (partial) reparations and structural causes. https://en.wikipedia.org/wiki/Windrush_scandal
• Home Office (2025). Earned settlement: a fairer pathway. Official consultation document of the November 2025 White Paper that doubles the qualifying period for Indefinite Leave to Remain from 5 to 10 years. Primary source. https://www.gov.uk/government/consultations/earned-settlement
• House of Commons Library (2026). Changes to UK visa and settlement rules after the 2025 immigration white paper. Parliamentary research briefing – the best independent and condensed analysis of the proposed changes, with estimates of those affected (around 1.6 million people who arrived in the UK since 2021). https://commonslibrary.parliament.uk/research-briefings/cbp-10267/

On Reform UK, polling, and the cultural shift

• YouGov (2025). Voting intention polls for 2025. Reform UK ahead in national polls, with the September 27% peak quoted in the article. https://yougov.co.uk/topics/politics/trackers/westminster-voting-intention
• Ipsos UK (2025). Issues Index, August 2025. Immigration as first public concern at 48%, ahead of economy and the NHS. https://www.ipsos.com/en-uk/ipsos-issues-index

On the Southport riots and the “two-tier” frame

• 2024 United Kingdom riots (Wikipedia). Reconstruction of the August 2024 events – the Southport stabbing, the spread of anti-Muslim disturbances, the police response, the emergence of the two-tier policing slogan and its adoption by US right-wing figures. https://en.wikipedia.org/wiki/2024_United_Kingdom_riots

On the 7 May 2026 Scottish elections and Swinney's stance

• 2026 Scottish Parliament election (Wikipedia). Detailed results, breakdown by constituency, full seat tables, post-election narrative. https://en.wikipedia.org/wiki/2026_Scottish_Parliament_election
• Scottish Daily Express (2026). “John Swinney opens door to nightmare Scottish Greens coalition as he clings onto power”. Primary source for Swinney's “I won't be inviting Reform in to have those discussions” statement. Curiously, the most direct citation of the cordon sanitaire declaration comes from a right-wing tabloid which obviously dislikes it – which makes the citation politically credible. https://www.scottishdailyexpress.co.uk/news/politics/john-swinney-opens-door-nightmare-37134152

On the Scottish framework: Hate Crime Act, New Scots

• Hate Crime and Public Order (Scotland) Act 2021 (Wikipedia). Reconstruction of the legislative process, of the controversies during implementation, of the practical applications since April 2024. https://en.wikipedia.org/wiki/Hate_Crime_and_Public_Order_(Scotland)_Act_2021
• Scottish Government (ongoing). New Scots Refugee Integration Strategy. The official Scottish public policy that frames refugee integration as a public good. https://www.gov.scot/policies/migration/new-scots-refugee-integration/

On the anti-fascist response: Together Alliance

• Together Alliance (2026). The civil society coalition of hundreds of organisations – including trade unions (NEU, UCU, Unite, Unison, TUC), faith organisations, Muslim Council of Britain, environmental groups (Friends of the Earth) – which organised the 28 March 2026 London demonstration. Estimated turnout: half a million. https://www.togetheralliance.org.uk/

For background on the political economy of contemporary far-right movements

• Mudde, C. (2019). The Far Right Today. Polity Press. Best academic synthesis on the structure of the contemporary far-right ecosystem – distinction between radical right (anti-immigration, populist, but within constitutional politics) and extreme right (anti-democratic). Useful framework for situating Reform UK and Robinson on the spectrum.
• Goodwin, M., Eatwell, R. (2018). National Populism: The Revolt Against Liberal Democracy. Pelican. Devil's advocate reading – sympathetic to the electoral phenomenon described – but useful precisely for that. The four Ds: distrust, destruction, deprivation, dealignment.

Discuss...

#Scotland #England #UK #Politics #Brexit #FarRight #TommyRobinson #ReformUK #ScottishIndependence #SNP #JohnSwinney #Immigration #AntiFascism #Holyrood #HostileEnvironment #Windrush #Italian #Migration #SolarPunk #Writing

The one thing I had configured carefully was the logs: nginx with an extended format, journald with audit, a few baseline fail2ban jails. I wanted to see what happens to a server that doesn't yet have a life, before I gave it one. Twenty-four hours later, I opened the logs. No humans. That was expected – I hadn't told anyone the domain. But there was already a small zoo of other presences. A wget from a Polish VPS with a phantom reverse DNS, the kind registered with a placeholder that never got updated. Three GETs, same resource, thirty-six second intervals. Then nothing. An SSH scan on port 80 – yes, an SSH scan on the HTTP port – written in Go, with a user-agent that claimed to be Mozilla/5.0 but was negotiating TLS the way only Go's crypto libraries do. VisionHeight, a commercial scanner that bills itself as ethical, mapped seven ports in two and a half minutes. Censys came through twice, identifying itself, leaving its own PTR and a link to its opt-out page. A Common Crawl crawler. GPTBot. ClaudeBot. AppleBot.

People: zero.

I spent the evening watching those logs the way you'd watch a sequence of read-heads on a tape. It was like opening the door to a flat you'd just rented and finding it already occupied by intruders. This is a public network, they seemed to be saying, and nobody told you what public means.

Since then I've done what everyone does: I've built defences. nftables to drop ASNs known for aggressive scanning. fail2ban with custom jails for nginx that recognise the patterns of the noisier scans – probes against /wp-login.php on a server that doesn't run WordPress, attempts at /.env, requests for phpMyAdmin paths that don't exist. GoAccess to visualise what little organic traffic remains once the rest is filtered out. An alert system over ntfy for out-of-band anomalies. It is routine – every sysadmin running a homelab has their own variant. But building it calmly, rather than as a patch on something that has already fallen over, is precisely what gets you to look at things that would otherwise scroll past, filtered away.

And while I was building it, a question came to mind, maybe a banal one, an extremely banal one: who am I doing all this for?

Not for the readers – those are few, almost none, they arrive via RSS, shared links, the occasional search engine. I was defending the server from a network that is predominantly non-human. I was configuring jails for scanners that don't know me, for crawlers that don't read me, for botnets that don't particularly mean me harm – they mean harm to anyone reachable on a port 22 or 80.

The threshold: 51% (and already 53%)

In 2024, for the first time in ten years, bot-generated traffic surpassed human traffic on the internet. Fifty-one percent against forty-nine. The figure comes from Imperva's Bad Bot Report, 2025 edition, the twelfth in the annual series – the analysis is based on thirteen trillion requests blocked by their global mitigation network in 2024 alone. It is the number that best sums up where we have ended up.

The 2026 Bad Bot Report, published a few weeks ago with 2025 data, has updated the figure: 53% bots, 47% humans. Another point and a half lost in twelve months. It did not happen all at once. Here is the historical series, from 2015 onwards:

(Source: Imperva, Bad Bot Report 2025 and 2026)

Humans have lost seven percentage points in ten years. The erosion is slow and steady – a descending curve measured in years, not in months. Nobody cut a ribbon to announce we have crossed the threshold. It was a gradual shift of the axis, a median that moved while we were looking elsewhere. Meanwhile, the bad bots grew from 27% to 37%. Ten percentage points in ten years, all on the predatory side. Brute force, credential stuffing, data scraping, account takeover, API fraud. Imperva records that ATOs – Account Takeover Attacks – grew by 40% in 2024 alone, and in 2025 the financial sector absorbed 46% of all ATO incidents worldwide. And, dulcis in fundo, the “good bots” – Googlebot, Bingbot, the legitimate aggregators, the health checkers – went down. From 19% in 2015 to 14% in 2024. The indexing services that historically justified bandwidth consumption have lost ground: the network has become more automated, but in a direction that does not pay off for those who publish.

Cloudflare confirms this with independent data. Their Radar Year in Review 2025, published at the end of December, reports that global internet traffic grew by 19% in 2025, and a substantial share of that growth is attributable to bots and AI crawlers. Googlebot still dominates – around 28% of verified traffic – but the new generation is gaining fast: OpenAI's GPTBot went from 4.7% in July 2024 to 11.7% in July 2025. ChatGPT-User, the bot that acts on explicit user command, recorded a year-on-year growth of 2,825% in request volume. That is not a typo. PerplexityBot, even more extreme: +157,490%.

The 51% threshold has to be read in this context. The curve has been rising for years, and 2024 is not the peak. The network we are using today is not the 2015 network with a few more bots: it is a structurally different network, where humans have gone from being the main signal to being the background noise.

Who is talking in this network?

When you say “bot” you do not say one thing. The presences in the logs belong to three families that do different jobs, have different economies, and produce different pressures on the infrastructure. Three main categories, then.

The cartographers. These are the scanners that map the entire IPv4 space – four billion three hundred million addresses – across all or nearly all known ports, and maintain queryable databases of exposed services. The founding project is ZMap, released in 2013 by a team at the University of Michigan. ZMap is a port scanner that can scan the entire IPv4 space on a single port in under 45 minutes from a single machine, from userspace, over a gigabit connection. Technically remarkable: it cuts by an order of magnitude the time needed to “see” all of the internet. Censys was built on top of ZMap, launched in 2015 by the same authors. Censys continuously scans IPv4, collects TLS certificates, service banners, software fingerprints, and keeps everything in a queryable commercial database. Shodan, founded in 2009 by John Matherly, is the conceptual predecessor: less polished technically, but longer-lived and more deeply rooted in sysadmin culture. Rapid7's Project Sonar, ZoomEye, Fofa, Netlas – all follow the same logic.

In 2012, an anonymous researcher decided he wanted to census the internet but did not have the bandwidth. He built an illegal botnet of compromised routers – the Carna Botnet – and ran the first Internet Census: he published the dataset online and declared his own offences. It remains a case study in the asymmetry between technical capability and legality – what Censys does today from a datacentre, ten years ago was a federal crime in the United States. The scanners describe themselves as ethical. They respect abuse@, publish their methodology, exclude networks on request, leave identifiable PTRs. All true. But the data they produce – the complete, near-real-time map of what is exposed on the internet – is sold by subscription, and the clients include academic research and the surveillance industry, corporate threat intelligence and aspiring attackers with seventy-nine dollars a month for a base account. In 2014, at Def Con 22, researchers Dan Tentler, Paul McMillan and Robert Graham ran a live IPv4 scan on port 5900 looking for VNC servers without authentication. They found thirty thousand systems accessible without a password. Among them: two hydroelectric power stations, the cameras of a Czech casino, industrial control systems, ATMs, a caviar production plant. The map exists because producing it is cheap, and who consults it – for what purposes, with what consequences – is a consequence of that price, not the reason for the project.

The extractors. These are the AI crawlers. They existed in embryonic form before too – Common Crawl for years, the indexing archives of search engines forever – but since November 2022, with the release of ChatGPT, they have changed in nature and in volume.

Cloudflare's data, collected from a fixed sample of clients to eliminate the growth bias, is explicit. Between July 2024 and July 2025:

• GPTBot (OpenAI): from 4.7% to 11.7% of total crawler traffic
• ClaudeBot (Anthropic): from 6% to nearly 10%
• Meta-ExternalAgent (Meta): from 0.9% to 7.5%
• PerplexityBot (Perplexity): growth of 157,490%
• Bytespider (ByteDance): declining, from 14.1% to 2.4%

The most revealing figure is the composition by purpose. Cloudflare classifies AI crawling into three categories: training (data collection to train models), search (indexing for chat search), user action (visits on explicit user command). Over the past twelve months, 80% of AI crawling has been for training. 18% for search. 2% for user action. In the most recent six months the training share has risen further, to 82%. The overwhelming majority of the work these bots do around the web does not, then, serve network mapping – it serves to extract content, process it, and turn it into training data for models that will then sell access or use the output to generate responses that compete with the originating site.

Another Cloudflare metric measures the imbalance directly: the crawl-to-refer ratio, that is, how many requests a bot makes versus how much traffic it then sends back to the source site. In July 2025, Anthropic was crawling 38,000 pages for every human visitor it sent back – a clear improvement on the 286,000:1 ratio recorded in January of the same year, but still the most lopsided extreme among the major AI platforms. OpenAI in the same period was running at around 1,500:1. Perplexity 194:1. The economic model is asymmetric extraction: take a lot, give back little.

The parasites. These are the bad bots in the strict sense: 37% of total internet traffic in 2024. Thirteen trillion requests blocked by Imperva's network alone in that year.

Here the composition changes. Imperva observes that “simple” attacks – basic scripts, dictionary attacks, automated scans – grew from 40% to 45% in 2024. The report explicitly attributes this growth to the arrival of generative AI: tools like ChatGPT, Claude, Llama have lowered the technical barrier to writing a brute forcer, a credential stuffer, a malicious crawler. What ten years ago required Perl and John the Ripper today requires a prompt and ten minutes. 31% of total attacks recorded by Imperva fall into one of the twenty-one OWASP Automated Threats categories. 44% of advanced bot traffic attacks APIs, no longer web pages – because APIs expose business logic with fewer defences and more value. 21% of attacks use residential proxies: IP addresses belonging to real domestic connections, rented on the grey market, allowing the bot to blend in as legitimate user traffic. Geo-fencing, per-IP rate limiting, ASN blacklists – all useless against an attacker who routes traffic through a residential fibre line in Milan.

One detail demolishes a widespread myth. Attackers usually do not want to take a site down. They want to use it. A compromised site is worth more alive than dead: as a host for phishing, cryptocurrency mining, botnet command-and-control, traffic redirect for black-hat SEO, file storage for warez. When the site falls, the attacker has done something wrong – they have saturated resources, triggered detection, burned their foothold. Akamai regularly publishes reports that confirm this: the economic model of the malicious bot is the long stay, not the raid. This changes the reading of visible symptoms. If a site falls over with intermittent 502s, the structural explanation is almost always: saturation of a PHP-FPM pool due to medium-scale bot traffic, on infrastructure that was not dimensioned to absorb half the internet knocking at the same time. The political explanation – they are attacking us to silence us – is almost always false, because anyone who knows how to attack seriously does not let the site fall over.

robots.txt, or the death of a social pact

In June 1994 Martijn Koster, a Dutch sysadmin running the early web crawlers for ALIWEB, proposed a convention: a text file at the root of the site, robots.txt, in which the operator could declare which parts of their domain crawlers were kindly asked not to visit. No central authority would enforce it, no network protocol would verify it. It was a gentleman's pact, full stop. It worked because in the nineties crawlers were few, they were run by people who knew each other, and nobody had an economic interest strong enough to burn their reputation by ignoring a directive. For thirty years it held. Googlebot, Bingbot, Yandex, Common Crawl – all respected robots.txt as part of the basic etiquette of indexing. It was so established that the formal specification only arrived in 2022 (RFC 9309), decades after the daily practice. When the IETF standardised it, they did so to document a consolidated practice, not to create a new one.

That pact, in the last three years, has been broken.

Drew DeVault, founder of SourceHut – the niche git platform much loved by those who do not want to be on GitHub – published a post in March 2025 that became a manifesto, titled Please stop externalising your costs directly into my face. The piece describes, with technical coldness, the behaviour of LLM crawlers:

they crawl everything they can find, robots.txt be damned, including expensive endpoints like git blame, every page of every git log, and every commit of every repository, and they do this using random User-Agents that overlap with end-users and come from tens of thousands of IP addresses – mostly residential, in unrelated subnets, each making no more than one HTTP request over any window we tried to measure – actively and maliciously adapting and blending in with legitimate traffic to evade any attempt at characterisation or blocking

It is the description of a distributed DDoS attack carried out by companies that present themselves as legitimate consumers of bandwidth. SourceHut had to unilaterally block entire cloud providers – Google Cloud, Microsoft Azure – because it was the only viable defence.

The Wikimedia Foundation, in April 2025, published data that complements this. Since January 2024, the bandwidth consumed by media downloads on Wikimedia Commons has grown by 50%. The increase does not come from new human readers: it comes from AI scrapers vacuuming up the entire catalogue of 144 million open-licence files. Wikimedia has quantified it: 65% of the most expensive traffic hitting the central datacentres is bot-generated, even though bots account for only 35% of total pageviews. The bots read in bulk – they request obscure pages that the regional cache does not have, forcing the infrastructure to fetch them from the centre. A human reader costs little; an AI crawler costs a lot, and the cost-to-benefit ratio for the body hosting the content has become unsustainable. The Foundation has set as a 2025/2026 annual goal: “reduce by 20% the traffic generated by scrapers”. An organisation that hosts the largest free encyclopaedia in the world is forced to invest engineering in repelling those who want to read it.

The KDE project's GitLab went down temporarily because of a crawler coming from Alibaba IP ranges. GNOME's GitLab installed Anubis, a proof-of-work challenge written by Xe Iaso – on arrival at the page, the browser has to solve a small computational problem before the content is shown. Costs nothing to a human, costs dearly to a bot that has to do millions a day. The numbers published by Bart Piotrowski, GNOME's sysadmin, after switching on Anubis: in two and a half hours, 81,000 total requests, of which only 3% made it through the proof-of-work. 97% were bots. Anubis' default loading screen shows a girl in anime style – it is an explicitly provocative aesthetic choice by Iaso, who has declared he wanted to make the experience annoying for those using these tools to extract.

Kevin Fenzi, who administers Fedora's infrastructure, has blocked traffic from entire countries. Drew DeVault, in the same post, writes:

Every time I sit down for a beer with my friends and fellow sysadmins, it is not long before we start complaining about the bots and asking each other whether the other has found the definitive way to get rid of them. The desperation in these conversations is palpable

It is the first-person chronicle of a technical community that has watched a thirty-year cooperative protocol break in thirty-six months.

Anthropic, OpenAI and the others publicly respond that they respect robots.txt. The sysadmins' logs say otherwise. Cloudflare, in its December 2025 report, writes unambiguously that “crawling activity can be aggressive, often ignoring the directives found in robots.txt files”. The structural problem is simple: robots.txt never had an enforcement mechanism. It rested on reputation. For those extracting data today to train AI models, the dataset is worth more than the reputation lost by ignoring it.

What it means for those who publish

For anyone running a small site – a blog, an online magazine, a collective's server, a personal homelab – the 51% (and more) figure translates into a daily operational reality that those who do not administer do not see. A server receives, in proportion, the same kind of bot traffic as the New York Times. Not the same volume, of course – but the same mix. GPTBot downloads wp-content, Censys maps the ports, some botnet tries credentials against three or four well-known WordPress endpoints. Even publishing three articles a month to a readership of two hundred people, you end up statistically anonymous, inside a scanning distribution that is uniform across all of IPv4.

This produces two effects.

The first is that the technical barrier to publishing on one's own has grown. In the 2000s it was enough to install WordPress on a shared host and forget about it. Today that model survives only if there is someone taking care of the maintenance – timely updates, well-curated plugins, robust passwords, offsite backups, monitoring. Without it, the site does not get attacked in a targeted way: it simply gets consumed by background pressure, like a cliff that erodes without any particular wave breaking on it.

The second is centralisation. The industry's response to the problem has been “managed everything”: Cloudflare in front of everything, managed WAFs, hosting that does automatic protection, CDNs that absorb anomalous traffic. They work. But the price is that a large chunk of the web now passes through a single provider – Cloudflare handles something like 20% of global HTTP requests – and the small independent publisher who would like to remain small and independent has to choose between delegating their network to a commercial intermediary or accepting standing upright in the wind.

On the defensive front there is a ferment of countermeasures – creative and desperate at the same time. Beyond Anubis, there are tar pits: Nepenthes, written by an anonymous developer who signs himself “Aaron”, responds to crawlers with infinite labyrinths of generated content – pages that link to other pages that link to others, all synthetic, all designed to consume the bot's resources without giving anything useful in return. Cloudflare has released a commercial equivalent, AI Labyrinth, which does the same thing serving irrelevant text to recognised crawlers. There is the community project ai.robots.txt, which maintains an up-to-date list of AI crawler user-agents and provides both a ready-made robots.txt and .htaccess rules to block them. A small archipelago of individual countermeasures – effective in some cases, but also a symptom: the fight is site by site, sysadmin by sysadmin, because no higher level exists where the question can be resolved.

Self-hosting is still possible. I do it myself, many others do. But it requires time, competence, continuous attention. It has become a niche. What in the 1990s was the normal way of being online is today an exception that needs to be justified – and maintained by hand.

We publish for human readers. But the infrastructure is shaped by bots. The visible web – the one humans see, navigate, read – is the surface tip of an iceberg made mostly of traffic invisible to the eyes and visible in the logs. The real web – the one the bots see – is all of IPv4, scanned in search of usable surfaces.

Guests on our own web

When Tim Berners-Lee described the World Wide Web in the early 1990s, he spoke of a space for connecting people: documents, ideas, knowledge, communities. The cyberlibertarian narrative of the years that followed – Barlow's Declaration of the Independence of Cyberspace in 1996, the Californian dream of the internet as individual emancipation from the hierarchies of the twentieth century – amplified that promise until it became myth. Thirty years later, the data is one: in 2025, humans are 47% of internet traffic. The majority is machines. And 80% of the work of those machines is the extraction of value from pages that other humans have written, to be processed and sold as predictive, classificatory, generative capability.

Lawrence Lessig saw it in 1999, in Code and Other Laws of Cyberspace. The thesis was simple: code is law. The technical architecture of a network is already political, because it determines what behaviours are possible. Changing the code – the protocols, the specifications, the design choices – means changing which practices are economic and which are not. TCP/IP does not speak about identity, and that is a political choice with thirty-year consequences. robots.txt was cooperative, and that is a political choice that has become a vulnerability. Those who have controlled the architecture – the ARPANET engineers first, the large infrastructure companies later – have already written the rules of the game, regardless of who won the elections or wrote the laws. Lessig has been repeating it for twenty-five years. It is happening now, on a global scale.

We are guests on our own web. We have been for at least a decade, and for two years we have been statistically a minority. The rent we pay is in data extracted without our noticing, in attention consumed by content generated by those who have scraped ours, and in administration hours spent keeping in place infrastructure that is not designed for us. It is not a metaphor: it is an accounting that could be done line by line, if anyone felt like keeping it. The interesting question, then, is not how we block the bots: it is what it means to publish and administer in an internet where the intended audience is no longer the majority of the recipients. A question we should have asked ourselves a long time ago, and one that concerns not only technical operators, but anyone who considers the internet a common good – political, cultural, material.

Sources and further reading

On bot traffic statistics and trends

• Imperva (Thales) (2025). 2025 Bad Bot Report: The Rapid Rise of Bots and the Unseen Risk for Business. Twelfth annual edition. The decade-long historical series, the pillar 51% figure, composition by attack category, estimates on residential proxies and ATOs. Thirteen trillion bot requests blocked in 2024. https://www.imperva.com/resources/resource-library/reports/bad-bot-report/
• Imperva (Thales) (2026). 2026 Bad Bot Report: Bad Bots in the Agentic Age. Updated figures for 2025: 53% bots, 47% humans. https://www.imperva.com/blog/
• Cloudflare Radar (2025). 2025 Year in Review: The rise of AI, post-quantum, and record-breaking DDoS attacks. AI crawler composition by purpose (training/search/user action), GPTBot/ClaudeBot/Meta-ExternalAgent share, crawl-to-refer ratio by platform. Independent confirmation of the Imperva data from a completely different network angle. https://radar.cloudflare.com/year-in-review/2025
• Cloudflare Blog (2025). From Googlebot to GPTBot: who's crawling your site in 2025. https://blog.cloudflare.com/

On the breakdown of cooperative protocols

• DeVault, D. (2025). Please stop externalising your costs directly into my face. SourceHut blog, March 2025. The manifesto, in first person, of a sysadmin who watches the cooperative robots.txt pact break. Essential reading to understand what it means to administer a FOSS service under pressure from LLM crawlers. https://drewdevault.com/2025/03/17/2025-03-17-Stop-externalizing-your-costs-on-me.html
• Wikimedia Foundation (2025). How crawlers impact the operations of the Wikimedia projects. Diff blog, April 2025. The internal data: 65% of the most expensive traffic from bots, 35% of pageviews. The most documented case of asymmetry between costs borne by the body hosting free content and benefits extracted by crawlers. https://diff.wikimedia.org/
• Iaso, X. (2024–present). Anubis (proof-of-work anti-AI-scraper). The concrete tool that GNOME, KDE and several other FOSS communities have adopted to defend public infrastructure from aggressive crawlers. Demonstrates that defence, today, is proof-of-work – that is, computational friction applied to those who want to read. https://anubis.techaro.lol/

On scanning infrastructure

• Durumeric, Z., Adrian, D., Mirian, A., Bailey, M., Halderman, J. A. (2015). “A Search Engine Backed by Internet-Wide Scanning”. Proceedings of the 22nd ACM Conference on Computer and Communications Security (CCS '15). Founding paper of Censys. Describes how scanning IPv4 has become economically trivial. Essential technical reading to understand the discovery/defence asymmetry. https://zmap.io/
• Akamai (various years). The Web Scraping Problem and related Threat Intelligence reports. Economic model of the malicious bot as a parasitic long stay, not as a destroyer. Demolishes the common intuition that a site that falls over has been “attacked”: those who know how to attack well do not make anything fall over. https://www.akamai.com/blog/security

On the political economy of digital infrastructure

• Lessig, L. (1999, updated as Code v2 in 2006). Code and Other Laws of Cyberspace. Basic Books. Code is law. The technical architecture of a network is already political because it defines what is possible. Twenty-five years later, the thesis is the single most useful conceptual tool for reading what is happening to robots.txt. http://codev2.cc/
• Zuboff, S. (2019). The Age of Surveillance Capitalism. PublicAffairs. Framework of non-consensual extraction as the dominant economic model of Silicon Valley. To be read thinking that its thesis, written about behaviour, applies today one level deeper: to the textual raw material.
• Crawford, K. (2021). Atlas of AI. Yale University Press. The materiality of AI as extractive asymmetry: mines, datacentres, underpaid human labour. I would add: your server.

Original protocol specifications

• Postel, J. (ed.) (1981). Internet Protocol. RFC 791. The original IP specification, fourteen pages that never talk about identity. https://datatracker.ietf.org/doc/html/rfc791
• Koster, M., Illyes, G., Zeller, H., Sassman, L. (2022). Robots Exclusion Protocol. RFC 9309. The formal specification of robots.txt, arriving thirty years after the practice and already obsolete in the practice. Worth rereading every so often to remember that today's internet is a palimpsest of hacks on top of a protocol conceived for a world that no longer exists. https://datatracker.ietf.org/doc/html/rfc9309

Discuss...

#Bots #AICrawlers #robotsTxt #DigitalSovereignty #SelfHosting #Cloudflare #SurveillanceCapitalism #FOSS #Internet #SolarPunk #Writing

A room in Cambridge, a government project, and a woman

The story of ARM does not begin in a Silicon Valley garage. It begins in Cambridge, in 1983, in a small company called Acorn Computers, on a commission from the BBC.

The context matters, because it changes the whole flavour of the story. The British government had decided to launch a national computer literacy programme – the BBC Computer Literacy Project – and needed a machine that could go into schools. Acorn won the tender with the BBC Micro, a cheap and robust computer that would introduce an entire generation of Britons to programming. It was the first time a state systematically funded popular access to computing. Not a startup with a venture-capital pitch: a public project, with public money, for an explicitly democratising goal.

But the BBC Micro was not enough. Acorn needed something more powerful for the next step, and the processors available on the market – 6502, Z80, the early Intel offerings – were either too slow, too complex, or too expensive. Acorn's research and development team then decided to design one from scratch, drawing inspiration from Patterson and Ditzel's work at Berkeley on the RISC architecture: simple instructions, executed quickly, few transistors, low power consumption. The result, in 1985, was the ARM1: thirty thousand transistors, no cache, no microcode.

The person who designed the architecture and instruction set of that ARM1 was called Sophie Wilson. Her approach is summarised in a sentence she gave in an interview with the Telegraph, and it is worth quoting:

We accomplished this by thinking about things very, very carefully beforehand.

Nothing particularly sophisticated, on the face of it. But in a sector where the dominant tendency was to add instructions and complexity to increase performance, the intuition of Wilson and her colleague Steve Furber went in the opposite direction: take away instead of add, simplify instead of complicate.

There is an episode that explains better than any technical analysis where this philosophy led. On 26 April 1985, when the first chips came back from the VLSI Technology foundry, Furber connected them to a development board and was puzzled: the ammeter in series with the power supply read zero. The processor seemed to be consuming literally nothing. The team that had designed the ARM1 numbered a handful of people – Wilson on the instruction set, Furber on microarchitecture design, a few collaborators around them – and operated with negligible resources compared to Intel or Motorola. The idea that they had just produced a processor that consumed zero was implausible.

The explanation, as Wilson recounted in a 2012 interview with The Register, was wrong in the most embarrassing way possible:

The development board the chip was plugged into had a fault: there was no current being sent down the power supply lines at all. The processor was actually running on leakage from the logic circuits. So the low-power big thing that the ARM is most valued for today, the reason that it's on all your mobile phones, was a complete accident.

The board was faulty, the power was not actually reaching the chip, and the processor was running on the leakage current from the logic circuits. The most important characteristic of the most widespread ARM architecture on the planet – the energy efficiency that makes it suitable for mobile devices – was discovered by mistake, on a broken board, by an engineer convinced he had a faulty measuring instrument.

Furber, for his part, explained the dynamic in more engineering terms:

We applied Victorian engineering margins, and in designing to ensure it came out under a watt, we missed, and it came out under a tenth of a watt.

The “Victorian engineering margins” are the generous safety margins typical of late nineteenth-century engineering – over-dimensioning every component to avoid failures. Furber and Wilson, accustomed to designing with limited resources and no margin for error, had applied the same principle to the chip design: design for consumption under a watt, and end up well below.

There was no magic with the low power characteristics apart from simplicity.

No magic. Just a design done well by a small team that could not afford to get it wrong. On that accident, and on that simplicity, ARM's dominance in mobile for the next forty years would be built.

A note on Sophie Wilson

Born in Leeds in 1957. She studied mathematics at Selwyn College, Cambridge, and as a student already worked with Hermann Hauser at Acorn – designing the Acorn System 1 even before graduating. In 1981, on commission from the BBC, she wrote BBC BASIC: a complete programming language in 16 kilobytes, so well-designed that it is still in use today on embedded systems. The “subtract instead of add” philosophy that would make ARM1 what it is was not born in 1985: it was born in the extreme memory constraints of the BBC Micro. Only later, in 1983, did Wilson begin work on the ARM1 instruction set, which she completed with Steve Furber in 1985. After Acorn she moved to Element 14, a 1999 spin-off absorbed by Broadcom in 2000. At Broadcom, where she still works as a Distinguished Engineer, she contributed to the BCM family of SoCs – including those that ended up inside the early Raspberry Pis, BCM2837 of the Pi 3 included. Recognition came late: Computer History Museum Fellow Award in 2012, Fellow of the Royal Society in 2013, Commander of the Order of the British Empire in 2019. In the 1990s she completed her gender transition, continuing to work in the sector without interruption.

In 1990, Acorn, Apple and VLSI Technology founded a separate joint venture to manage and license the architecture. The name changed from Acorn RISC Machine to Advanced RISC Machines. ARM Holdings was born as an independent company, headquartered in Cambridge, with a business model that had no precedent in the sector: it would never manufacture a single chip. It would sell the idea of the chip. Licences, royalties, IP. Anyone who wanted to build an ARM processor would have to pay them.

It was a technical choice, but also a political one. ARM did not have the capital to build factories, did not have the infrastructure. But it had something harder to replicate: a clean, efficient architecture, designed well from the start.

The architecture of invisible power

ARM's business model is one of the most elegant – and least understood – in the entire technology industry. It works like this: ARM designs the processor architectures and licenses their use to third parties in exchange for an upfront fee (typically between one and ten million dollars) plus a royalty on every chip produced, usually around 1–2% of the final device price. Whoever buys the licence can then build their own chips based on that architecture, customising it within the limits allowed by the contract. They are not buying a product, then: they are buying the right to make one.

Garnsey, Lorenzoni and Ferriani, in a fundamental study on the birth of ARM as a spin-off from Acorn published in Research Policy in 2008, describe this transition as an exemplary case of techno-organizational speciation: technology is not simply transferred, but is radically transformed in the passage to a new domain through a new organisational model. ARM is not Acorn that changes its name: it is a new organism, with a completely different survival logic, which carries the original DNA but adapts to an environment Acorn could never have inhabited.

The practical result of this structure is what the industry calls neutral positioning. ARM does not compete with its customers – it does not sell chips, does not produce devices – so it can sell the same licence to Qualcomm, Apple, Samsung and MediaTek, who fight each other on the market every day. It is the “Switzerland” of silicon: a credible referee, a common infrastructure, a layer everyone builds on without having to trust the others. This has created an ecosystem of over a thousand licensee partners – a number impossible to reach for any traditional chip manufacturer. Furber, today professor of computer engineering at the University of Manchester, summed up the result in a way that is hard to forget:

I suspect there's more ARM computing power on the planet than everything else ever made put together. The numbers are just astronomical.

It is not rhetoric: it is the logical consequence of a model that multiplies adoption instead of concentrating it.

But this neutrality has a structural cost that is rarely thematised. When ARM sells a licence, it also sells dependence. Whoever builds their own SoC on ARM architecture is bound to that instruction set for the entire life of the product. Changing architecture would mean rewriting the software, recertifying the systems, redoing the chip design. The exit cost is very high. And this means that ARM, despite producing nothing, exercises enormous systemic power: it can renegotiate licence terms, raise royalties, decide who gets access to the most advanced architectures and who does not. Abstract as this dependence may sound on paper, there is a recent case that makes it very concrete – and worth following in detail, because it illustrates exactly how ARM power is exercised in the real world.

In 2021, Qualcomm acquired for $1.4 billion a Californian startup called Nuvia, founded by three former Apple Silicon engineers – Gerard Williams III, Manu Gulati, John Bruno – who were designing a server chip called Phoenix, based on the ARM v8.7-A architecture. Nuvia had its own ALA (Architecture License Agreement) with ARM, negotiated on the terms of a small startup entering a new market. When Qualcomm bought it, it integrated the Phoenix technology into its own Oryon core, the heart of the new Snapdragon X Elite – the chip with which Qualcomm wanted to challenge Intel and AMD in the AI PC laptop market.

The problem was contractual, not technical. Qualcomm's ALA with ARM already existed, and provided for lower royalties than Nuvia's. Qualcomm argued that the integration of Nuvia into its own chips fell under its pre-existing ALA. ARM replied that no: the acquisition required a full renegotiation from scratch – on ARM's terms, naturally. In 2022 ARM took Qualcomm to court asking, among other things, for the physical destruction of the pre-acquisition Nuvia designs. Not a downsizing, not a renegotiation: destruction. The message was unambiguous: IP licensing is not a sale, it is a revocable permission, and the permission is granted by whoever owns the architecture.

The case went to trial in Wilmington, Delaware, in December 2024. The jury ruled unanimously in favour of Qualcomm on two of the three contested points, hung jury on the third. On 30 September 2025, Judge Maryellen Noreika issued the final ruling: full and final judgment in favour of Qualcomm and Nuvia on all fronts, also rejecting ARM's request for a new trial. The judge explicitly noted that ARM itself, in its own internal documents, admitted to having recorded historic licensing and royalty revenues after attempting to terminate Nuvia's ALA in 2022 – which, translated, means: while claiming to have been damaged by Nuvia's actions, ARM was making piles of money precisely thanks to the ecosystem built on that architecture.

ARM has announced it will appeal. Qualcomm, for its part, already has a counter-suit open since April 2024 against ARM – accusing it of withholding technical deliverables, anti-competitive behaviour, and (in a subsequent amendment) of intending to enter the server chip market as a direct competitor. The trial, originally set for March 2026, has been postponed to October 2026 to deal with a series of pending motions – a sign that the complexity of the dispute does not exhaust itself easily. That is: ARM, which built everything on neutral positioning, finds itself accused in court of wanting to become a silicon producer. Aka: the Switzerland that suddenly wants an army.

The Qualcomm/Nuvia case is important not because Qualcomm won, but because it publicly exposed the nature of the power ARM exercises. The real asset had never been the architecture – the architecture is technical documentation, brutally, in the end. The real asset was the contract. The capacity to drag into court anyone who thinks they can use that documentation without the right permission. Langdon Winner, in his influential 1980 essay Do Artifacts Have Politics?, argued that technological choices are never neutral – they incorporate power structures, distribute access in non-random ways, create dependencies that persist long after the initial decision.

It is still true that, in a world in which human beings make and maintain artificial systems, nothing is “required” in an absolute sense. Nevertheless, once a course of action is underway, once artifacts like nuclear power plants have been built and put in operation, the kinds of reasoning that justify the adaptation of social life to technical requirements pop up as spontaneously as flowers in the spring.

And ARM is an almost perfect case of this thesis applied to the IP economy: an architecture born of a public computer-literacy project becomes the foundation on which an invisible monopoly is built across tens of billions of devices. It is not malice. It is structure. The chip has no intentions. But the licensing structure that sits on top of it, that one does.

A new front: the datacentre

A parenthesis is necessary, because it tells where ARM is going right now – and why the Qualcomm/Nuvia case has the importance it has.

For the first part of its history, ARM was the architecture of mobile. Servers, datacentres, enterprise computing were Intel territory: x86 dominated in an apparently unchallenged way. Things began to change in 2018, when Amazon Web Services announced the first Graviton, a custom ARM chip designed in-house by Annapurna Labs (acquired by AWS in 2015). The selling argument was simple and technically sound: at equivalent loads, ARM chips consumed much less energy than equivalent x86, and in a datacentre where the electricity bill is a third of operating costs, this translates directly into margin.

Since then the trajectory has been steady and surprisingly fast. In 2023 ARM accounted for about 5% of the cloud compute of the three major hyperscalers. ARM itself, in its 2025 communications, claims that by year-end approximately half of the compute shipped to the top hyperscalers will be ARM-based – a figure to be taken with the caution due to a company talking about its own market, but consistent: for the third consecutive year, more than half of new CPU capacity added to AWS is Graviton, and 98% of the top one thousand EC2 customers use it. AWS Graviton5, announced on 4 December 2025 at re:Invent, has 192 cores in a single socket, an L3 cache five times larger than the previous generation, and is based on the Neoverse V3 ARMv9.2 cores at 3 nanometres. Google has launched Axion (based on Neoverse V2) with the claim of a 65% better price-performance compared to x86 instances. Microsoft has rolled out Cobalt 100 in 29 global regions. NVIDIA – the very same NVIDIA that had tried to buy ARM – uses ARM Neoverse cores in Grace, the CPU that accompanies its H100 and B100 GPUs for AI workloads. Spotify, Paramount+, Uber, Oracle, Salesforce have migrated infrastructure to ARM. Over a billion ARM Neoverse cores have been deployed in datacentres worldwide.

This changes the proportions of the game. When ARM made money on smartphone royalties, we were talking about cents per chip but on billions of units. In datacentres things are different: every Graviton5 costs AWS thousands of dollars, and every server with an ARM chip on board is a more substantial royalty. The datacentre is the segment where ARM can finally start extracting value aggressively. And it is also the segment where licensees have most to lose: if Apple or Qualcomm raise your royalties on a phone, it is an annoyance; if ARM raises your royalties on the chip running your cloud, it is an attack on the operating margin of your business.

It is easier to understand, in this light, why Qualcomm pulled out the Nuvia case with such determination. And why – as we will see shortly – it is looking for an architectural way out.

The failed coup

November 2020. Jensen Huang, NVIDIA's CEO, announces the acquisition of ARM from SoftBank for $40 billion. It would have been the largest operation in semiconductor history. It did not go through, and understanding why helps to see how systemic ARM's position in the industry was – and still is.

Hermann Hauser, the Austrian from Cambridge who had founded Acorn, the company from which ARM was born, had reacted to the SoftBank acquisition back in July 2016 with a public statement on Twitter that left no room for interpretation:

ARM is the proudest achievement of my life. The proposed sale to SoftBank is a sad day for me and for technology in Britain.

When, four years later, NVIDIA announced its intention to buy ARM from SoftBank, Hauser's reaction was even sharper. In an interview with the BBC he explained the structural problem with a clarity that regulatory documents rarely achieve:

It's one of the fundamental assumptions of the ARM business model that it can sell to everybody. The one saving grace about Softbank was that it wasn't a chip company, and retained ARM neutrality. If it becomes part of Nvidia, most of the licensees are competitors of Nvidia, and will of course then look for an alternative to ARM.

And in his written testimony submitted to the British Parliament he added, with the freedom of someone who had nothing left to lose:

I have no shares or other interest in ARM as I had to sell them all to Softbank. I can therefore freely speak my mind.

Hauser was right. NVIDIA, in 2020, was already dominant in artificial intelligence through its GPUs. Buying ARM would have meant getting early access to new designs ahead of competitors, the ability to slow or deny licences to rivals, and benefiting freely from the architecture while others continued paying royalties. Qualcomm, Microsoft and Google publicly opposed the deal. The American FTC opened an antitrust proceeding. The European Commission launched an investigation. Britain opened its own. China raised a red flag. In February 2022, the deal was formally cancelled for significant regulatory challenges.

There is another Hauser statement worth quoting. In a 2022 interview with UKTN, he called British politicians «technologically illiterate» and «the root cause» of the governance problems around ARM. He argued that the government should have taken a golden share in ARM long before, and that any attempt to do so in 2022 was «trying to close the gate after the horse has bolted». An architecture born with public money and a public mandate had become a pawn in the power game between SoftBank, NVIDIA and the NASDAQ – because no one had thought, at the appropriate moment, that it was worth keeping it in public territory.

The end of the story: SoftBank took ARM public in September 2023, in what was the largest IPO of the year. ARM Holdings is today listed on NASDAQ with a market capitalisation of around $150 billion. Masayoshi Son is still the controlling shareholder. The fact that the acquisition attempt by the world's largest AI chip producer was blocked by regulators does not eliminate the problem – it shifts it. ARM is independent, but it is a very particular form of independence: that of a systemic infrastructure in the hands of financial investors, subject to stock-market logic, obliged to grow revenues every quarter. The uncomfortable question is: what happens when the needs of a commons architecture – stable, predictable, accessible, neutral – conflict with the needs of a publicly listed company that has to raise royalties to satisfy shareholders? It is not a theoretical question. ARM has systematically increased its licence fees in recent years. And the major licensees have started looking for alternatives.

The half-democratisation

We have to give ARM what ARM deserves, before continuing with the critique. And what it deserves is considerable.

The Raspberry Pi – version 3 in 2017, version 5 today – costs less than eighty euros for the most recent version. It is a complete computer, capable of running Linux, a server, a media centre, a network node. It exists because the ARM architecture has made it possible to produce powerful and very low-power SoCs at costs that x86 processors cannot get close to. The same principle applies to the billion-plus smartphones in the hands of people in countries where a desktop PC would be an inaccessible luxury. To the microcontrollers controlling IoT sensors at a few cents each. To the embedded processors in medical devices, industrial control systems, critical infrastructure. ARM has materially lowered the cost of access to computational hardware on a global scale.

Wilson herself, looking back on the whole story, framed it with a lucidity that almost sounds like a warning:

To build something new and complicated, it's not the sort of quick thing, it's a sustained effort over a long period of time. It takes many people's different inputs to make something unique and novel. Overnight success takes 30 years.

Thirty years of invisible work, of architectures refined chip by chip, of licences negotiated one at a time, before the world noticed that ARM was everywhere.

The “democratisation” effected by ARM is real but structurally asymmetric. It has democratised access to hardware for device manufacturers – anyone can build an ARM chip by paying the licence – but not necessarily for the end users of those devices. An iPhone – or an Android phone – has an ARM chip designed by a company, but the end user has no access to the chip's architecture, no possibility to modify it, no transparency on what runs at that level. The chip is ARM, the device is a closed box. This is the final contradiction: you may have the right – or almost – to manage the software running on an ARM chip, but below the kernel, below the bootloader, there is a chip whose architecture was defined in Cambridge, produced in Taiwan, integrated into a SoC designed by Broadcom, over which you can have no control. Sovereignty ends exactly where silicon begins. Those who really benefited are the oligopoly of large licensees – Apple, Qualcomm, Samsung, NVIDIA, Amazon with its Gravitons – not the small Bangalore startup with an idea for a specialised chip.

And yet – and here the story gets complicated, in an interesting way – within the narrow space the ARM licensing model concedes, someone is nevertheless trying to pull the lever of openness at the levels available. In December 2024, a Shenzhen company called Radxa announced the Radxa Orion O6, presented as the “World's First Open Source Arm V9 Motherboard”. It is a Mini-ITX board at $200 in the base version, based on the Cix CD8180 SoC – an ARMv9.2 chip with 12 cores (four Cortex-A720 at 2.8 GHz, four at 2.4 GHz, four Cortex-A520 at 1.8 GHz) produced by Cix Technology, a Chinese fabless founded in 2021. Debian 12, Fedora and Ubuntu run natively on it, with UEFI EDKII and SystemReady SR certification. The first Geekbench benchmarks put it at the level of an Apple M1 in single-core – not bad for an ARM board at less than a tenth of the price of a Mac mini.

*Note: it is worth clarifying what “open source” means here, because it means different things at different levels. The ARMv9.2 instruction set on which the CD8180 is built is not open: Cix pays regular royalties to ARM Holdings like all other licensees. The SoC itself is not open: it is a proprietary chip, with the NPU microcode and Mali GPU blocks all closed. What is open is the layer immediately above: board schematics, Board Support Package, EDKII bootloader, Linux kernel, device tree – all published under free licences, replicable, modifiable.*

It is also a concrete demonstration of what the open hardware movement has been arguing for twenty years: openness is layered, and opening one more layer than was open before is already a political act, even if the foundation underneath remains closed. The fact that this board comes from China – like the RISC-V pivot we will discuss shortly – is no accident: it is consistent with a geopolitical trajectory that seeks margins of technological sovereignty wherever it is possible to extract them.

The Linux moment for hardware

And here RISC-V comes onstage. And the story gets more interesting.

RISC-V was born in 2010 at the University of California Berkeley, in the same department that had helped inspire the original RISC architecture thirty years earlier. Krste Asanović and his collaborators needed a clean processor architecture for research, without having to pay licences or ask permission. They decided to design one from scratch, and to make it completely open: no royalties, no licences, no intellectual property to respect. The RISC-V instruction set is an open standard, freely published, that anyone can implement, modify, distribute.

For ten years RISC-V was an academic experiment, then a nucleus of embedded adoption, then an interesting alternative for those who wanted custom chips without paying ARM. In the last two or three years the proportions have changed. The SHD Group, a market analysis firm that has been monitoring the RISC-V sector since 2019, announced at the November 2025 RISC-V Summit that the technology's market penetration had exceeded 25% – an important symbolic threshold, even if it is to be taken with some caution. The same RISC-V International annual report for 2025 admits it is not entirely clear whether the 25% refers to the global microprocessor market in the strict sense or only to the segments where RISC-V already has a significant presence (embedded, IoT, microcontrollers). The SHD projection for 2031 is 33.7%. However it is measured, the trajectory is that of an architecture that is no longer a niche: it is the third pillar of computing, alongside x86 and ARM.

The strength of RISC-V is not just technical – it is political in the most precise sense of the term. Some examples:

The Chinese front. China has very concrete reasons not to want to depend on ARM, a company listed in New York with American shareholders. Under increasingly stringent US sanctions on advanced Intel/AMD chips, China has pivoted en masse to RISC-V – also because the RISC-V International consortium was strategically moved from Delaware to Switzerland in March 2020, formally placing it beyond the reach of unilateral American export controls. Alibaba, through its T-Head division, has released the XuanTie C920 chips and successors. Smaller Chinese manufacturers are flooding the mid-market with RISC-V AI accelerators that cost significantly less than the equivalent Western ones under sanction. It is an architectural decoupling, not just a commercial one.

The European front. The European Union, through the EU Chips Act, funds the Project DARE consortium (Digital Autonomy with RISC-V in Europe) with the explicit goal of reducing European dependence on American and British technology in critical infrastructure. Quintauris, a joint venture founded in December 2023 by Bosch, Infineon, Nordic Semiconductor, NXP and Qualcomm (with STMicroelectronics joining as a sixth shareholder in 2024), developed in 2025 RT-Europa, the first RISC-V platform for real-time automotive controllers – a sector where dependence on foreign IP had become strategically intolerable.

The Qualcomm front. In December 2025, while the Nuvia case closed yet another chapter against ARM, Qualcomm acquired Ventana Micro Systems, one of the most advanced companies in the development of high-performance RISC-V cores. Literally: not only was Qualcomm fighting ARM in court, it was also buying the way to no longer need ARM. It is the most significant move in all the recent history, because for the first time one of the major ARM licensees equips itself with a credible architectural plan B.

Three different fronts, one same direction. The parallel with Linux is more than metaphorical. Linux did not kill Windows or macOS. But it did create a real alternative that changed the terms of power in the software industry. RISC-V aspires to do the same thing for hardware. And the critical point – the one Winner would have appreciated – is that this openness is built into the architecture itself, not guaranteed by a company's good will. You cannot buy RISC-V and “close it”. The instruction set is public by definition. You can build proprietary implementations on top of it – and many companies are doing that – but the foundation remains accessible.

And here the question: will RISC-V be incorporated by capitalism exactly as Linux was? The honest answer is: probably yes, and in part it already has been. The major RISC-V implementations by Apple, Google and Meta are not open source – they use the open instruction set to build proprietary architectures. The fact that the foundation is free does not mean that everything built on top of it is. The same logic Boltanski and Chiapello described applies: critique is not defeated, it is incorporated. But at least the foundation remains open. And that counts.

Conclusions – or questions, if you prefer

ARM is born of a public mandate and a democratisation project, and becomes the foundation of a private oligopoly. The chip is the same; the power structure on top of it is radically different from the one that produced it. And that chip really did lower the entry barriers for hardware producers – it produced the Raspberry Pi, the cheap phones, the microcontrollers everywhere, the more efficient datacentres – but the democratisation stopped at the gates of the production chain. The end users of those devices gained no real sovereignty over the silicon they hold in their pocket.

NVIDIA's attempt to acquire ARM was blocked by regulators, but only because it would have concentrated power too visibly. The systemic power ARM already exercises – silently, through licences and royalties, through legal cases against those trying to step out of contractual terms – disturbs no regulator, generates no headlines, produces no parliamentary hearings. It is the kind of power that makes itself invisible precisely because it is structural: it does not lie in a decision, it lies in the conditions within which decisions are made.

There is also a contradiction that concerns me personally. That Raspberry Pi I had on the table – and all the ARM chips in the phones I have hacked for years – were already, in some sense, part of a system I did not control. I changed the software on top. I did not change the power structure underneath (one could make the same argument about Intel, ça va sans dire…). Digital sovereignty ends exactly where silicon begins, and pretending otherwise would be dishonest.

RISC-V opens a real crack. Not a revolution – a crack. The possibility that the foundation of computing be a commons, instead of private property subject to corporate decisions and legal battles. It does not solve the problem of closed hardware, it does not solve the problem of oligopolistic foundries, it does not solve any of the contradictions described. But at least it does not aggravate them. It is the same logic of the open hardware movement, which for twenty years has been trying to apply to silicon what free software has applied to code – with more modest results, because the physical layer is structurally more hostile to the commons: if you cannot open it, you do not really own it. And in a sector where every layer of the technology stack has been systematically fenced off, keeping the foundation open is a political act, not just a technical one.

What stays with me is a feeling familiar to anyone who has spent time thinking about computing as political territory. Technological choices incorporate power structures. Power structures persist long after the original choices have been forgotten. And whoever controls the basic infrastructure – the instruction set, the architecture, the licences – controls something much more important than a company: they control the rules of the game on which everything else is built.

The question I leave open is: in whose favour were these rules written? And by what right do they continue to apply?

Sources and further reading

On the history of ARM and its origins

• Garnsey, E., Lorenzoni, G., Ferriani, S. (2008). “Speciation through entrepreneurial spin-off: The Acorn-ARM story”. Research Policy, 37(2): 210-224. doi: 10.1016/j.respol.2007.11.006. The most in-depth academic study on the origin of ARM as a spin-off from Acorn and on the genesis of its IP licensing-based business model. https://www.sciencedirect.com/science/article/abs/pii/S0048733307002363
• Patterson, D., Ditzel, D. (1980). “The Case for the Reduced Instruction Set Computer”. ACM SIGARCH Computer Architecture News, 8(6): 25-33. The founding paper of the RISC architecture at Berkeley, which inspired the ARM project. https://dl.acm.org/doi/10.1145/641914.641917

On the IP licensing business model

• Ferriani, S., Garnsey, E., Lorenzoni, G., Massa, L. (2015). “ARM plc and the IP Business Model”. Working Paper, Centre for Technology Management, University of Cambridge. https://www.ifm.eng.cam.ac.uk/uploads/Research/CTM/working_paper/2015-02-Ferriani-Garnsey-Lorenzoni-Massa.pdf
• Grindley, P. C., Teece, D. J. (1997). “Managing Intellectual Capital: Licensing and Cross-Licensing in Semiconductors and Electronics”. California Management Review, 39(2): 8-41.

On power in technological choices

• Winner, L. (1980). “Do Artifacts Have Politics?”. Daedalus, 109(1): 121-136. https://www.cc.gatech.edu/~beki/cs4001/Winner.pdf
• Boltanski, L., Chiapello, È. (1999). Le nouvel esprit du capitalisme. Gallimard. (English transl. The New Spirit of Capitalism, Verso, 2005). https://www.jstor.org/stable/4201214

On the Qualcomm/Nuvia case

• Paul, Weiss (2025). “Qualcomm Wins Decisive Post-Trial Victory in High-Profile Licensing Dispute Against Arm”. https://www.paulweiss.com/insights/client-news/qualcomm-wins-decisive-post-trial-victory-in-high-profile-licensing-dispute-against-arm. Press release of the law firm that represented Qualcomm, with summary of the 30 September 2025 ruling.
• The Register (2025). “Judge dismisses Arm's last legal claim against Qualcomm”. https://www.theregister.com/2025/10/01/arms_last_legal_claim_against/
• Computerworld (2025). “Arm's high-stakes licensing suit against Qualcomm ends in mistrial, but Qualcomm prevails in key areas”. https://www.computerworld.com/article/3629812/

On the NVIDIA acquisition attempt and geopolitical implications

• U.S. Federal Trade Commission (2021). Complaint in the Matter of NVIDIA Corporation and Arm Limited. https://www.ftc.gov/legal-library/browse/cases-proceedings/2110081-nvidia-corporationarm-limited
• Hauser, H. (2020). Written evidence submitted to the UK Parliament Business, Energy and Industrial Strategy Committee on the proposed acquisition of ARM by NVIDIA. Document BFA0018. https://committees.parliament.uk/writtenevidence/12711/pdf/
• Hauser, H. (2022). Interview with UKTN: “UK left it too late to take golden share in Arm”. https://www.uktech.news/news/government-and-policy/hermann-hauser-arm-golden-share-20220623

On Sophie Wilson, Steve Furber and the origin of ARM1

• Wilson, S. (2012). Interview with The Register: “ARM creators Sophie Wilson and Steve Furber”. https://www.theregister.com/2012/05/03/unsung_heroes_of_tech_arm_creators_sophie_wilson_and_steve_furber/. Contains Wilson's statement on low power as a complete accident.
• Furber, S. (2010). Interview with ACM Queue: “A Conversation with Steve Furber”. https://queue.acm.org/detail.cfm?id=1716385. Contains the statement on Victorian engineering margins.
• Furber, S. (2011). Interview with Communications of the ACM. https://cacm.acm.org/news/an-interview-with-steve-furber/. Contains the assessment on total ARM computing power on the planet.
• Furber, S. (2017). “ARM: The architecture that conquered mobile computing”. Philosophical Transactions of the Royal Society A, 375(2104). doi: 10.1098/rsta.2017.0148.
• Computer History Museum (2012). Fellow Award citation for Sophie Wilson and Steve Furber. https://computerhistory.org/chm-fellows/sophie-wilson/

On ARM in datacentres

• Arm Holdings (2025). “Half of the Compute Shipped to Top Hyperscalers in 2025 will be Arm-based”. Arm Newsroom. https://newsroom.arm.com/blog/half-of-compute-shipped-to-top-hyperscalers-in-2025-will-be-arm-based
• Arm Holdings (2025). “How Arm is redefining compute through the converged AI data center”. Arm Newsroom. https://newsroom.arm.com/blog/arm-converged-ai-data-center-aws-graviton5
• Omdia (2026). “Arm Steps Deeper into Silicon: Implications for the Semiconductor Value Chain”. https://omdia.tech.informa.com

On the democratisation of access to computing

• Benkler, Y. (2006). The Wealth of Networks: How Social Production Transforms Markets and Freedom. Yale University Press. http://www.benkler.org/Benkler_Wealth_Of_Networks.pdf
• Söderberg, J. (2008). Hacking Capitalism: The Free and Open Source Software Movement. Routledge. https://downloads.gvsig.org/download/people/vagazzi/Hacking%20Capitalism.pdf

On RISC-V and architectural sovereignty

• RISC-V International (2024). RISC-V Ratified Specifications. https://riscv.org/technical/specifications/
• RISC-V International (2026). Annual Report 2025. https://riscv.org/wp-content/uploads/2026/01/RISC-V-Annual-Report-2025.pdf. The official RISC-V International annual report, with the SHD Group estimate on market penetration (33.7% projected by 2031, 25% threshold reached in 2025 in some segments).
• Waterman, A., Asanović, K. (eds.) (2019). The RISC-V Instruction Set Manual. UC Berkeley Technical Report UCB/EECS-2019-103. https://riscv.org/wp-content/uploads/2019/12/riscv-spec-20191213.pdf
• Asanović, K., Patterson, D. A. (2014). “Instruction Sets Should Be Free: The Case for RISC-V”. EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2014-146.
• Center for Security and Emerging Technology (2025). “RISC-V: What it is and Why it Matters”. https://cset.georgetown.edu/article/risc-v-what-it-is-and-why-it-matters/. On the incorporation of RISC-V International in Switzerland in March 2020 and the geopolitical implications.
• Jamestown Foundation (2025). “Examining China's Grand Strategy For RISC-V”. https://jamestown.org/program/examining-chinas-grand-strategy-for-risc-v/
• The Register (2025). “Qualcomm takes RISC on Arm alternative with Ventana buy”. https://www.theregister.com/2025/12/10/qualcomm_riscv_arm_ventana/. On the acquisition of Ventana Micro Systems by Qualcomm on 10 December 2025.
• Quintauris GmbH (2023). “Five Leading Semiconductor Industry Players Incorporate New Company, Quintauris, to Drive RISC-V Ecosystem Forward”. Press release, 22 December 2023. https://www.quintauris.com

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#ARM #RISCV #Semiconductors #OpenHardware #SophieWilson #DigitalSovereignty #IPLicensing #Computing #SolarPunk #FOSS #Writing

The funny thing – funny in the sense that it makes you laugh, but badly – is that I'm not alone. Every day, somewhere in the world, someone orders a mini PC, a Raspberry Pi, a managed Mikrotik switch, with the stated goal of taking back control of their digital life. They order it on Alibaba, pay with PayPal, wait for the courier. And they see nothing strange in any of this, because the contradiction is so structural it has become invisible. This article is an attempt to make it visible again. Without easy solutions, because I don't have any. And when have I ever…

The Promise of the Homelab

When, in 2019, I started self-hosting pretty much everything – Nextcloud (always on a Raspberry Pi, first RPi3 then RPi4), Jellyfin, Navidrome, FreshRSS, and about twenty-five other services on Proxmox LXC, each with its own isolated Docker daemon – I did it with a precise motivation: I wanted to know where my data lived, who could read it, and have the ability to switch it off myself if I ever felt like it. Not when a company decides to shut down a service, not when someone else changes the licence terms. Me. This came after a long period of reflection on myself, the work I was doing and still do, and the technological society I live in. It is an ideological choice before it is a technical one. Technology as a tool for autonomy rather than control; infrastructure as something you own instead of something that owns you. I hope no one is alarmed if I say that some of these reflections began with reading Theodore Kaczynski's Manifesto, before eventually landing, of course, on more authoritative sources.

Yes, I'm mad, but not quite that mad…

When you pay a subscription to a cloud service, the transaction does not end the moment you authorise the electronic payment. Shoshana Zuboff, in The Age of Surveillance Capitalism, calls this mechanism behavioral surplus: the behavioural data extracted beyond what is needed to provide the service, then resold as predictive raw material.

Under the regime of surveillance capitalism, however, the first text does not stand alone; it trails a shadow close behind. The first text, full of promise, actually functions as the supply operation for the second text: the shadow text. Everything that we contribute to the first text, no matter how trivial or fleeting, becomes a target for surplus extraction. That surplus fills the pages of the second text. This one is hidden from our view: “read only” for surveillance capitalists. In this text our experience is dragooned as raw material to be accumulated and analyzed as means to others' market ends. The shadow text is a burgeoning accumulation of behavioral surplus and its analyses, and it says more about us than we can know about ourselves. Worse still, it becomes increasingly difficult, and perhaps impossible, to refrain from contributing to the shadow text. It automatically feeds on our experience as we engage in the normal and necessary routines of social participation.

You are not the customer of the system – you are its product. Your habits, your schedules, your preferences, your hesitations before clicking on something: all of this is collected, modelled, sold. The transaction is not monthly: it is continuous, invisible, and never ends as long as you use the service. With hardware, in principle, the transaction is one-time: you buy, you pay, it ends, it is yours. The disk is in your room, not on a server subject to government requests, security breaches, or business decisions that are nothing to do with you but impact your access to those services. This distinction – between a tool you use and a system that uses you – is the real stake of the homelab. It is not about saving money, it is not about performance. It is about who controls what.

The problem is that building this infrastructure requires hardware, time, knowledge, and resources. The hardware comes from somewhere; the time, the knowledge, and the energy resources come from a privilege not granted to everyone.

The Market I Hadn't Seen

Search for “mini PC homelab” on any marketplace. What you find is a productive ecosystem that has exploded over the past five years in a way I honestly did not expect.

MINISFORUM, Beelink, Trigkey, Geekom, GMKtec. Zimaboard, with its single-board aesthetic designed explicitly for those who want home racks. Raspberry Pi and the galaxy of clones – Orange Pi, Rock Pi, Banana Pi. Managed Mikrotik switches at accessible prices. 1U rack cases to mount under the desk. M.2 NVMe SSDs with TBW figures calculated for small-server workloads. Silent power supplies designed to run 24/7. A market built from scratch, that exists precisely because there is a community of people who want to run servers at home. r/homelab and r/selfhosted on Reddit have approximately 2.8 and 1.7 million members respectively – numbers publicly verifiable, and growing. YouTube is full of dedicated channels. There is an entire attention economy built around “escaping” the attention economy.

But it is worth asking: who built this market, and why. MINISFORUM and Beelink do not exist out of ideological sympathy for the homelab movement. They exist because they identified a profitable segment and served it with industrial precision. Kate Crawford, in Atlas of AI, documents how technology supply chains follow niche demand with the same efficiency with which they follow mass demand: factories in Guangdong optimise production lines not for a worldview, but for a margin. The fact that the resulting product also satisfies an ideological need is, from the manufacturer's point of view, irrelevant.

The Victorian environmental disaster at the dawn of the global information society shows how the relations between technology and its materials, environments, and labor practices are interwoven. Just as Victorians precipitated ecological disaster for their early cables, so do contemporary mining and global supply chains further imperil the delicate ecological balance of our era.

The mechanism had been described with theoretical precision back in 1999 by Luc Boltanski and Ève Chiapello in The New Spirit of Capitalism. Their thesis: capitalism is never defeated by criticism – it is incorporated. When a critique becomes widespread enough, the system absorbs it and transforms it into a market segment. The artistic critique of the 1960s – autonomy, authenticity, rejection of standardisation – became the marketing of the creative economy. The critique of digital centralisation – sovereignty, privacy, control – has become an online catalogue to browse through.

Resistance has become a market segment. Every time someone buys a HUNSN to stop paying subscriptions to services they don't control, a factory in Guangdong sells a HUNSN. Capitalism has not been defeated – it has shifted (at least for a small slice of the population: the nerds, the hackers) the extraction point from subscriptions to hardware.

The Accumulation Syndrome

But there is a further level – more ridiculous and more personal – that homelab communities never discuss openly, yet anyone who has a homelab recognises immediately. The Raspberry Pi 4 bought “for a project.” The old ThinkPad kept because “you never know.” The 4TB disk salvaged from a decommissioned NAS – and “it might come in handy.” The second-hand switch picked up on eBay for eighteen euros because it was cheap and might be useful. The cables, the cables, the cables.

r/homelab has a term for this: just in case hardware. It is the hardware of the imaginary future, of projects that only exist in your head, of configurations that one day – one day – you will finally test. In the meantime it occupies a shelf, draws current in standby, and generates a diffuse sense of possibility that is indistinguishable from the most classic consumerism. The underlying psychological mechanism has a precise name: compensatory consumption – consumption as a response to a perceived loss of autonomy or control. You buy hardware because buying hardware gives you the feeling of recovering agency over something. The aesthetic is different from traditional consumerism – no luxury logos, no recognisable status symbols – but the mechanism is identical.

That said, there is a partially honest answer to all of this: the second-hand and refurbished market. The ThinkPad X230 on eBay, the Dell R720 server decommissioned from a datacentre, the disk from someone who upgraded their NAS. My ZFS NAS, to give one example, is a recycled old tower with four 1TB disks in RAIDZ – hardware that would otherwise have ended up in landfill, with a life cycle extended by years, without generating new production demand. It is closer to the ethics of repair than to compulsive buying. But it has its own internal contradiction: it requires even more technical competence than buying new – knowing how to assess wear, diagnose an unknown component, manage ten-year-old drivers. The barrier to entry rises further. And the refurbished market is itself now an organised commercial sector, with its own margins, its own platforms, its own pricing logic. It is not a clean way out. It is a less dirty way out.

And then there is the energy question, which is usually ignored in homelab discussions and is instead the most uncomfortable of all – uncomfortable enough to deserve a more in-depth treatment later on. For now, suffice it to say: every machine on your shelf that “draws current in standby” is a line item in the energy bill that the homelab movement rarely accounts for.

Not for Everyone. And It Should Not Be This Way.

There is a second level of the paradox that is even more uncomfortable than the first. Building a homelab costs money – relatively little, but it costs. It requires physical space. It requires a decent connection. And it requires time. A lot of time. Not installation time – that is measurable, finite. The learning time that precedes everything else. To reach the point where you can build a functional infrastructure with Proxmox, LXC containers, centralised authentication, reverse proxy, automated backups – you need to have already spent years understanding how Linux works, how to reason about networks and permissions, how to read a log. I started with a Red Hat in 1997, and it took me almost thirty years to get where I am. I should know this. Yet it always escapes me. And that time did not fall from the sky. It is time I was able to dedicate because I had a certain kind of job, a certain stability, a certain amount of mental energy left at the end of the day. It is middle-class-with-a-stable-position time, not the time of someone working three warehouse shifts a week. Passion is not enough.

Johan Söderberg documents this in Hacking Capitalism: the FOSS movement was born as resistance to capitalism, but reproduces within itself hierarchies of skill and merit that make it structurally exclusive. Freedom is technically available to anyone, but effective access requires resources distributed in anything but a democratic manner. Söderberg goes further than simply observing the exclusivity: the voluntary open source work produces use value – functioning software, documentation, community support – that capital then extracts as exchange value without remunerating those who produced it. Red Hat builds a billion-dollar company on a kernel written largely by volunteers. It is not just that not everyone can get in: it is that those who get in often work for someone without knowing it. The homelab inherits this problem and amplifies it.

The narrative of orthodox historical materialism corresponds with some very popular ideas in the computer underground. It is widely held that the infinite reproducibility of information made possible by computers (forces of production) has rendered intellectual property (relations of production, superstructure) obsolete. The storyline of post-industrial ideology is endorsed but with a different ending. Rather than culminating in global markets, technocracy and liberalism, as Daniel Bell and the futurists would have it; hackers are looking forward to a digital gift economy and high-tech anarchism. In a second turn of events, hackers have jumped on the distorted remains of Marxism presented in information-age literature, and, while missing out on the vocabulary, ended up promoting an upgraded Karl Kautsky-version of historical materialism.

This is not a quirk of the homelab movement: it is a recurring structure in every technological wave. Langdon Winner, in his influential essay Do Artifacts Have Politics?, argued that technological choices are never neutral – they incorporate power structures, distribute access in non-random ways. Amateur radio in the 1920s, the personal computer in the 1980s, the internet in the 1990s: every time the promise was democratising, every time the actual distribution followed the lines of pre-existing privilege. Not out of malice, but out of structure. The irony is this: those who would most need digital autonomy – those who cannot afford subscriptions, those who live under governments that surveil communications, those most exposed to data collection – are exactly those least likely to be able to build a homelab. Not for lack of interest or intelligence. For lack of time, money, and years of privileged exposure to technology.

Homelab communities do not usually talk about this. They talk about which mini PC to buy, how to optimise energy consumption, which distro to use as a base. The conversation about structural exclusivity exists, but at the margins – in Jacobin, in Logic Magazine, in EFF activism – while the centre of the discourse remains impermeable. It is not that no one speaks about it: it is that the peripheries speak about it, and the peripheries do not set the agenda. This entire conversation takes place in a room to which not everyone has a ticket. And those inside do not seem to find that particularly problematic.

A Technological Cosplay?

So is the whole thing a con? Is the homelab just anti-capitalist cosplay while you continue to fund the same supply chains? In part, yes.

The HUNSN 4K was designed in China, assembled in China, shipped by container on ships burning bunker fuel. Global maritime transport is responsible for approximately 2.5% of global CO₂ emissions – a share that the IMO (International Maritime Organization) has been trying to reduce for years with slow progress and targets continually postponed. Then: distributed through Alibaba, paid with a credit card. Every piece of technology hardware carries an extractive chain that begins in lithium mines in Bolivia and cobalt mines in the Democratic Republic of the Congo, passes through factories in Guangdong, and ends in electronic waste processing centres in Ghana. The hardware travels that supply chain exactly like any other consumer device. Furthermore, hardware has a lifecycle. In five years the HUNSN 4K will be too slow, or it will break, or something will come out with energy efficiency too much better to ignore. And I will buy again. The mini PC market for homelabs depends on the obsolescence of previous purchases – exactly like any other consumer market.

The critique of capitalism, when it is widespread enough, is not suppressed – it is incorporated. The system absorbs the values of resistance and transforms them into a market segment. Autonomy becomes a selling point. Decentralisation becomes a brand. The rebel who wanted to exit the system finds himself funding a new vertical of the same system, convinced he is making an ethical choice.

The Counter-Shot

But there is a structural difference that would be dishonest to ignore.

When you pay a subscription to a cloud service, the cost is not just the monthly fee. It is the continuous cession of data, behaviours, habits. It is the behavioral surplus Zuboff talks about: you are not using a service, you are being used as raw material to train models, build profiles, sell advertising. The transaction never ends, in ways you often cannot see and cannot escape from as long as you use the service.

With hardware, the transaction ends. The data stays on a physical disk in your room, not on a server subject to government requests, breaches, or business decisions that have nothing to do with you but impact your life. The software running on it – Proxmox, Debian, Nextcloud, Jellyfin – is open source; you can modify it. If something changes in a way you cannot accept, you can leave. This resilience has real value – but it is worth noting that it is asymmetric resilience: it works for those who have the skills to exercise it. For those who do not, the theoretical portability of their data from Nextcloud to something else requires exactly the same skills we have already identified as the barrier to entry. The freedom to leave is real. Access to that freedom, much less so.

And then there is the energy question, which I have deferred long enough. The major hyperscalers – AWS, Google, Azure – operate with a PUE (Power Usage Effectiveness) between 1.1 and 1.2. For every watt of useful computation they dissipate barely 0.1–0.2 watts in heat and infrastructure. They have enormous economies of scale, optimised industrial cooling, significant investments in renewable energy, and above all: their servers run at very high utilisation rates. Almost always busy.

A home homelab works in a radically different way. The machine runs 24/7 even when it is doing nothing – and for most of the time it is doing nothing. Navidrome serving three requests a day, FreshRSS fetching every hour, an LDAP container sitting listening without receiving connections. You are paying the energy cost of the infrastructure regardless of usage. The implicit PUE of a homelab, calculated honestly on the ratio between total consumption and actual workload, is much worse than that of a datacentre. IEA data (Data Centres and Data Transmission Networks, updated annually) shows that large cloud providers progressively improve energy efficiency thanks to economies of scale that no individual homelab can replicate. The flip side is that the same growth in demand that makes economies of scale possible negates the efficiency gains: Amazon's absolute emissions increased between 2023 and 2024 despite improved PUE. Efficiency improves. Total consumption grows anyway. This is Jevons' Paradox: energy efficiency, instead of reducing consumption, increases it, because it lowers the marginal cost of use and stimulates demand that grows faster than the efficiency gains.

Note: The comparison is not as linear as the numbers suggest. PUE measures the internal efficiency of a datacentre, not the energy cost of the network traffic that data generates every time it leaves it – traffic that a homelab eliminates almost completely for internal services. Nor does it measure proportion: AWS is efficient at delivering services to millions of users, but that scale says nothing about the real cost of storing fifty gigabytes of personal data on a server designed for loads a thousand times greater. A HUNSN N100 in idle consumes less than 8 watts. The honest energy comparison is not homelab vs hyperscaler in the abstract – it is homelab vs proportional share of hyperscaler for your specific workload, a calculation that nobody can make with publicly available data.

This does not automatically mean that the cloud is the ethically correct choice – the problem does not reduce to PUE, and surveillance has costs that are not measured in kilowatts. It means that anyone with SolarPunk values who chooses the homelab must reckon with a real contradiction: the choice of sovereignty may be, watt for watt, energetically more costly than the system one wants to escape. I have no clean answer, but ignoring the question would be dishonest. Söderberg acknowledges that the FOSS movement has produced concrete and undeniable gains – they simply are not enough, on their own, to subvert the dynamics of informational capitalism.

In short: this is not a critique of the homelab, but it is a critique of the homelab presented as a sufficient revolutionary act.

What Happens at Eleven PM – and Beyond

That night, with the HUNSN 4K on the table, I pressed on. I installed Proxmox. I configured the network. I started bringing up containers one by one. And at some point – three hours had passed, I had three terminals open and was debugging nslcd to centralise LDAP authentication across all the containers – I realised something: I was doing all of this simply because I enjoyed it. Not to resist something. Not to advance an ideological agenda. Because there was a problem to solve and solving it gave me satisfaction. Mihaly Csikszentmihalyi describes this state in Flow as total absorption in a task calibrated to one's own competencies: time expands, attention narrows, awareness of context vanishes. It is not motivation – it is something more immediate. Debugging an authentication problem at eleven at night on a system I could have chosen not to build is, neuropsychologically, indistinguishable from pleasure. Not the satisfaction of having finished: the process itself. Moreover, for an AuDHD person like me, going into hyperfocus allows you to lose your sense of time entirely, and to literally escape from a world you viscerally loathe.

Ah – you had not figured that out yet?

When I had finished and closed everything, the satisfaction was still there. Along with a mildly uncomfortable awareness: I could probably have used a hosted service, lived just as well, and not lost three hours of a weeknight. But in the meantime I had understood how PAM worked, I had read documentation I had never opened before, I had implemented it on my homelab, I had learned something I hadn't known I wanted to know.

And here the circle closes in a somewhat unsettling way. Söderberg speaks of voluntary open source work as the production of pure use value – the intrinsic pleasure of doing, understanding, building something that works. But it is exactly this use value that capital then extracts as exchange value: the competence I accumulate debugging LDAP at eleven at night is the same competence I bring to work the next day, that I put into articles like this one, that I share in communities where others use it to build their own homelabs. Technical pleasure is not neutral. It has a production chain. Not always visible, but real.

This is what the homelab is, at least for me: a way of learning that produces, as a side effect, an infrastructure I control. The ideology is there, but it comes second. First comes the pleasure of understanding how something works. Or rather: ideology and pleasure are interchangeable, and often run in parallel – but this does not resolve any of the contradictions I described above. It leaves them all standing, in fact makes them stranger. Am I resisting capitalism, or am I just cultivating an expensive hobby with a political aesthetic?

The Hacker Ethic

The word “hacker” has had bad press for decades. In 1990s news bulletins it was a synonym for a hooded cybercriminal; in the jargon of security companies it became a marketing term to prepend to anything. Neither has much to do with what the word historically means. Steven Levy, in Hackers: Heroes of the Computer Revolution, reconstructs the culture that formed around the MIT and Stanford labs in the 1960s: a community of programmers for whom code was an aesthetic object, access to information a moral principle, and technical competence the only legitimate hierarchy. The principles Levy identifies as the “hacker ethic” are precise: access to computers – and to anything that can teach you how the world works – should be unlimited and total. All information should be free. Decentralised systems are preferable to centralised ones. Hackers should be judged by what they produce, not by titles, age, race, or position. You can create art and beauty with a computer.

It is not a political manifesto in the traditional sense. It is something more visceral – a disposition toward the world, a way of standing before a system you do not yet understand: the correct response is to take it apart, understand how it works, and put it back together better than before.

Pekka Himanen, in The Hacker Ethic and the Spirit of the Information Age – with a preface by Linus Torvalds and an epilogue by Manuel Castells, which already says something about the project's ambition – performs a more explicit theoretical operation. He builds the hacker ethic in direct opposition to the Protestant work ethic described by Max Weber: where Weber saw work as duty, discipline as virtue, and leisure as absence of production, Himanen identifies in the hacker a figure who works out of passion, considers play an integral part of work, and rejects the sharp separation between productive time and free time. The hacker does not work for money – money is a side effect, when it comes. They work because the problem is interesting. Because the elegant solution has value in itself. Because understanding how something works is, in and of itself, sufficient.

Hacker activity is also joyful. It often has its roots in playful explorations. Torvalds has described, in messages on the Net, how Linux began to expand from small experiments with the computer he had just acquired. In the same messages, he has explained his motivation for developing Linux by simply stating that “it was/is fun working on it.” Tim Berners-Lee, the man behind the Web, also describes how this creation began with experiments in linking what he called “play programs.” Wozniak relates how many characteristics of the Apple computer “came from a game, and the fun features that were built in were only to do one pet project, which was to program … [a game called] Breakout and show it off at the club.”

Recognise something? I do. Those three hours debugging nslcd at eleven at night were not work in the Weberian sense – nobody was paying me, nobody had asked me to do it, there was no corporate objective to reach. They were hacking in the precise sense that Levy and Himanen describe: exploration motivated by curiosity, with the infrastructure as an object of study as much as of utility. The homelab is, culturally, a direct expression of the hacker ethic. It is no coincidence that homelab communities and open source communities overlap almost perfectly, that they use the same language, the same platforms, the same values. But here, as elsewhere in this article, the story gets complicated.

The hacker ethic promises a pure meritocracy: you are judged by what you can do, not by who you are. It is an attractive idea. It is also, in practice, a partial fiction. Technical meritocracy presupposes that everyone starts from the same point – that skills are accessible to anyone who really wants to acquire them, that the time to acquire them is distributed equally, that mentorship networks and learning resources are available regardless of context. The homelab as hacker practice inherits both things: the genuine nature of curiosity as a driver, and structural exclusivity as an undeclared side effect. The pleasure of taking a system apart to understand how it works is real and should not be devalued. But that pleasure is available, in practice, to those who already have the ticket.

Conclusions

The HUNSN 4K runs, alongside the other “little electronic contraptions,” on a rack next to my armchair – the one where, at the end of the day, I indulge my guilty pleasure of reading a book in the company of my cats. Proxmox, the Nextcloud server, the ZFS NAS, a small MINISFORUM box running Ollama with some local open-weight LLM models, a Raspberry Pi 5 running the Tor Relay, and a HUNSN RJ15 with pfSense controlling incoming and outgoing traffic. An infrastructure, in short, that allows me to have something resembling digital sovereignty within the limits of the possible. The contradictions I have described do not resolve. They are held together, with effort, as any intellectually complex position on a complex system must be held together.

The first: the market that made the accessible homelab possible is the same market the homelab is supposed to emancipate us from. If this explosion of affordable, efficient mini PCs had not happened – if capitalism had not decided to build exactly what we wanted – how many of us would have taken the same path? How much of our “ethical choice” depends on the existence of products designed and sold precisely for us?

The second: does incorporated resistance truly lose its force, or does it remain resistance even when someone profits from it? Boltanski and Chiapello describe the incorporation mechanism, but do not argue that critique loses all effectiveness in the process. Perhaps the homelab is simultaneously a product of the system and a real, if partial, form of withdrawal from it. The two things are not mutually exclusive.

The third: if digital autonomy requires decades of accumulated skills, enough free time to use them, and enough money to buy the hardware, are we building a democratic alternative? Or are we building an exclusive club with a rebel aesthetic, reproducing the same hierarchies of privilege it claims to want to fight?

The fourth: the energy question has no clean answer, and Jevons' Paradox makes it even more uncomfortable – because it works in both directions. The cloud improves efficiency and increases total consumption. A homelab consumes proportionally more, but does not fuel the demand that drives that total consumption upwards. Are we building digital sovereignty, or are we simply choosing where to position ourselves within a contradiction that cannot be resolved at the individual level?

I don't know. But at least I know where my data is.

Fun Fact

This article was written in Markdown using a Flatnotes instance running as a CT container on Proxmox, while listening to a symphonic metal playlist served by Navidrome – another CT container – pulling OGG files from a ZFS NAS over an NFS share. The cited books were in EPUB format on Calibre Web. In the background, Nextcloud on a Raspberry Pi 4 was syncing and backing up everything. Spelling mistakes were corrected by Qwen2.5, an LLM model served by Ollama on the MINISFORUM box, accessible locally via oterm and Open WebUI. And all of this, controlled from a laptop running Linux.

Coincidences? I don't think so.

Discuss...

#Homelab #SelfHosted #SurveillanceCapitalism #Privacy #OpenSource #HackerEthic #SolarPunk #DigitalSovereignty #FOSS #Linux #Writing

I waited. I thought it was still loading. Nothing. The grid kept changing. I tried clicking on the cells. Nothing. I tried pressing keys on the keyboard. Nothing. I watched for a few minutes, waiting for something to happen – a game over, a score, an objective. Nothing. It wasn't a game. There was nothing to “play.” It was like watching rain fall, but digital. Hundreds and hundreds of pixels kept appearing and disappearing. I got bored, closed the tab. Years later – I don't remember how many, a lot – I happened to read an article on Wikipedia. The title was “Conway's Game of Life.” And the penny dropped.

What I had seen that day wasn't a game, or at least not in the traditional sense. It was a simulation. And that simulation, with four rules that even a child could understand, was doing something that none of those rules explicitly anticipated: producing complexity. Order from chaos. Structures that emerged, grew, interacted. Patterns that moved across the grid as if alive. And then – and this is where I had my epiphany – those structures could simulate an electronic circuit. Any electronic circuit. Theoretically, any computation that a Turing machine can perform. Four rules, binary cells. In essence: a universal computing machine.

Welcome to the story of how the English mathematician John Horton Conway, trying to build the simplest possible toy, accidentally built one of the most powerful demonstrations of how complexity can emerge from nothing. Dear creationists – yes, this one's for you too.

Von Neumann had a question

Before Conway, there was Von Neumann. John von Neumann – Bond, James... okay, I'll stop – was already asking, back in the 1940s, a question that sounds almost philosophical: can a machine build a copy of itself? It wasn't an abstract question. Von Neumann had already demonstrated theoretically that it was possible. His model – a two-dimensional “cellular automaton” – proved the principle. It worked like this: a configuration of cells on a grid contains within itself the “instructions” (encoded as the arrangement of active and inactive cells) to replicate itself. The structure reads these instructions, manipulates the surrounding cells, and generates an identical copy of itself in another area of the grid. The copy contains the same instructions, so it can repeat the process indefinitely. It's every engineer's dream (or nightmare, depending on your perspective): a machine that reproduces without external intervention.

The problem was the monstrous complexity of the system. Von Neumann's model required 29 different states per cell – twenty-nine – and a set of rules that filled pages and pages of algebra. It was functional, demonstrably correct, but it was a monster. Nobody could really grasp it at a glance, let alone implement it and study it in practice. It was like having the perfect recipe for a dish, but with 300 rare ingredients and 50 steps requiring laboratory equipment.

In 1962, the English mathematician John Horton Conway – professor at Cambridge, specialising in group theory and other things that sound complicated – decided to do something apparently simple. He looked for the most minimal possible version of Von Neumann's idea. A system of rules poor enough to be understandable by anyone, but rich enough to allow complex behaviour and, eventually, self-reproduction. It took him years. Not weeks, not months. Years. From 1962 to 1970. Eight years of proposals, tests, failures, adjustments. Every ruleset was analysed: too ordered? Everything converges to fixed configurations and the system dies. Too chaotic? Total noise, no structures. Conway was looking for a precise critical point: enough stability to allow persistent forms, enough instability to allow unpredictable and interesting behaviour.

He was obsessed with this balance. He tested it on graph paper (computers weren't yet fast enough to do it quickly), with groups of students, by hand, generation after generation. Painstaking work. Or the work of a madman, depending on how you look at it.

By 1970 he had found what he was looking for. He called it the “Game of Life.” Martin Gardner, who had a monthly column in Scientific American called “Mathematical Games,” presented it in October of that year. And within weeks it became one of the most famous objects in the entire history of recreational mathematics and computer science.

The four rules (and why each one matters)

The system is embarrassingly simple. You have an infinite two-dimensional grid (in practice: very large). Each cell can be in one of two states: alive (black) or dead (white). Each cell has eight neighbours – the four cardinal directions plus the four diagonals. At each generation, all cells simultaneously update their state following four rules:

1. A live cell with fewer than 2 live neighbours dies – isolation. There isn't enough interaction to sustain life. It's loneliness that kills.

2. A live cell with 2 or 3 live neighbours survives – stability. Local density is just right. There's enough support, but not too much competition. It's the point of equilibrium.

3. A live cell with more than 3 live neighbours dies – overpopulation. Too much competition for resources (it's a metaphor, but it works). Too much crowding suffocates.

4. A dead cell with exactly 3 live neighbours comes to life – reproduction. Three live cells create the conditions to generate new life. Not 2, not 4. Exactly 3.

That's it. Nothing else. No exceptions, no special conditions, no “if this cell is particular then...”. Four rules, applied uniformly to every cell, every generation, forever.

Now stop for a moment and think about this: where is the complexity in these rules? Where does it say that structures must emerge? Where does it say that patterns can exist that move, oscillate, interact in non-trivial ways? Nowhere. The rules only talk about individual cells and their immediate neighbours. Nothing more. And yet complexity emerges. It emerges necessarily, as an inevitable consequence of that subtle balance Conway spent eight years searching for. It isn't programmed into the rules. It's an emergent property of the system. And this is the point that made the penny drop for me, years after that grid: complexity doesn't need to be designed. It can simply happen, if the conditions are right.

The taxonomy

In the first year after publication in Scientific American, readers – programmers, mathematicians, students, enthusiasts – flooded the magazine with discoveries. It had become a viral phenomenon, in an era when “viral” still meant photocopies and letters sent by post. And very quickly a natural classification of structures emerged.

Still lifes – completely stable patterns that never change. The simplest is the “block”: a 2×2 square. In the block, every cell has exactly 3 neighbours – the other three cells of the square. Each one survives because it has exactly 3 live neighbours. The pattern doesn't change, doesn't move. It's just there, motionless, forever. Other examples: the “beehive,” the “loaf” – stable forms that once formed remain identical.

Oscillators – patterns that change but return to their initial configuration after a finite number of generations. The simplest is the “blinker”: three cells in a horizontal line. In the next generation they become three cells in a vertical line. Then back to horizontal. Then vertical. Period 2, infinite oscillation. Other more complex examples: the “toad” (period 2), the “beacon” (period 2), the “pulsar” (period 3, one of the most visually beautiful).

And then there's the one. The glider, my favourite – illustrated in detail on MathWorld.

Five cells, arranged in a specific configuration that looks almost like a wonky little triangle. And this thing – this small five-cell structure – moves. Not in the sense that the cells physically shift around the grid (the cells are fixed, remember). In the sense that the pattern propagates through space, one cell at a time, diagonally downward to the right (or in any direction, depending on the initial orientation). After four generations, the glider has returned to its original configuration, but shifted one position diagonally. And then it continues. Forever. It crosses the grid indefinitely, unless it meets an obstacle.

And here something starts to change in the way people thought about the system. Because a glider isn't just a pretty pattern to watch. It's a signal. It's something that carries information from point A to point B. It has a direction, it has a speed (c/4, where c is the maximum possible speed in the Game of Life, which is one cell per generation), it has persistence.

And if you have a glider, the next question is obvious: can you create something that generates more gliders? The answer arrived in 1970, a few months after the original publication. Bill Gosper – an MIT programmer, one of the first hackers in history – found the “glider gun.” A configuration of 36 cells that, every 30 generations, spits out a new glider. A periodic signal generator. A signal. A periodic source. A precise direction. In a 2D grid with binary cells and four elementary rules. This is where the story is going.

The heart: four rules, one Turing machine

TL;DR: The Game of Life is Turing-complete. This means that, in principle, you can perform any computation that a Turing machine can perform, inside a 2D grid with binary cells and four rules. No processor. No integrated circuits. Just cells being born and dying according to Conway's four rules.

To understand why the Game of Life is Turing-complete, you need to take a step back on what “Turing-complete” means. Alan Turing, in 1936 (at 24 years old – the age at which I was still playing at being a Wikipedia editor), defined an abstract model of computation: a machine that reads an infinite tape of cells, writes on it, and moves forward or backward, following a finite set of deterministic rules. If a system can simulate any Turing machine – that is, if you can configure it to perform any computation that is computable – that system is Turing-complete. Which means, in practice, that it's universal from a computational standpoint. There is nothing a Turing machine can do that this system cannot do (given enough space and time).

Now back to the Game of Life. We have the glider: a signal that moves. We have the glider gun: a periodic source of signals. But is this enough to build a computer? No. To have a logic circuit you need the fundamental logic gates – AND, OR, NOT. All basic boolean operations. Everything else – addition, multiplication, comparisons, conditional jumps, arbitrary algorithms – is built by combining logic gates.

Logic gates in the Game of Life are implemented by exploiting interactions between gliders. When two gliders intersect, the result depends on their relative configuration, the precise timing of the encounter, the direction of approach. Some combinations cause the two gliders to completely annihilate each other (output: no glider). Others produce new gliders in specific directions (output: one or more gliders). By changing the geometry of the encounter – the exact position of the glider guns that generate them, the timing, the distances – you can build configurations that behave like AND, OR, and NOT gates. The incoming gliders represent the input bits (0 or 1, depending on whether the glider is present or not). The outgoing gliders represent the result of the logical operation.

If you have logic gates, you have combinational circuits. If you have combinational circuits and a memory mechanism (implemented with glider loops and oscillating patterns), you have sequential circuits. And if you have arbitrary sequential circuits, you have a Turing machine.

This isn't theory. It's been done. In 2000, Paul Rendell built a functioning Turing machine entirely within the Game of Life – with tape, read/write head, states, transitions. In 2010, a group of researchers led by Paul Chapman took the concept further still and built a complete computer – including a display – that runs the Game of Life... inside the Game of Life.

These implementations are, obviously, infinitely slower than a real processor. A single clock cycle requires hundreds or thousands of generations. A simple addition takes billions of steps. But they work. The computation happens, correct, deterministic, verifiable.

But back to the main point. What does all this mean? It means that the grid I was staring at all those years ago – that thing I didn't understand, that looked like organised noise – had more theoretical computational power than any processor I've ever used. Not in terms of speed (that would be ridiculous) but in terms of what can be done.

The biology that isn't biology (but almost)

Conway never claimed that the Game of Life literally simulated biological life. The rules have nothing to do with DNA, cells, metabolism, evolution. There's no natural selection, no adaptation. It's a purely deterministic system where the same initial conditions always produce the same result. Zero stochasticity, zero mutations, zero genetics.

And yet the field of “artificial life” owes an enormous debt to the Game of Life. Because the GoL demonstrated experimentally a principle that before 1970 was more philosophical intuition than concrete proof: biological complexity doesn't require an intelligent designer. It can emerge from simple rules, applied uniformly, with nothing more than local interactions between identical elements. Self-organisation – structures that emerge without central coordination. Competition for space – patterns that survive are those satisfying the conditions of survival (the four rules). Emergence of hierarchical structures – from the single glider (elementary pattern) to the glider gun (generator) to logic circuits (systems of patterns that interact in a coordinated way).

It's not biological evolution in the Darwinian sense. But it's the same underlying principle: from simplicity, complexity emerges, without that complexity needing to be explicitly encoded in the fundamental rules.

The risk here is always falling into superficial analogies that don't hold up to analysis. The GoL doesn't simulate real ecosystems. The “cells” aren't biological cells. There's no metabolism, no sexual reproduction, no genetic variability. The parallel should be taken for what it is: an illustrative case of a more general principle, not a replica of real life. But it remains true that when you watch a glider gun fire gliders indefinitely, or when you see complex patterns emerging from random initial configurations, it's hard not to think: “this looks alive.” It isn't, of course. But the boundary between “looks alive” and “is alive” is more blurred than we like to admit.

Wolfram and the search for universality

If Conway showed that complexity emerges from simplicity in one specific case, Stephen Wolfram tried to do something more ambitious: systematically map all possible behaviour of simple cellular systems.

Wolfram – physicist, mathematician, creator of Mathematica (yes, that Mathematica) – published in the 1980s a series of papers on one-dimensional “cellular automata,” even simpler versions of the Game of Life. Imagine not a 2D grid, but a single row of cells. Each cell has only two neighbours (left and right) instead of eight. Each cell can be 0 or 1. And a cell's behaviour in the next generation depends only on its own state and those of its two neighbours.

How many possible rules are there for such a system? 256. Exactly 256, because there are 8 possible configurations of three cells (2³), and for each you must decide whether the central cell will be 0 or 1 in the next generation (2⁸ = 256 total combinations).

Wolfram numbered them all – Rule 0, Rule 1, Rule 2... Rule 255 – and tested them systematically, generation after generation, starting from different initial configurations. And he discovered that, despite their apparent diversity, all 256 automata naturally grouped into four categories of behaviour:

Class I – convergence to a uniform state. Everything dies or everything becomes the same. Total order, extremely boring.

Class II – simple periodic behaviour. Oscillators, stable patterns that repeat. Interesting order, but predictable.

Class III – complete chaos. Pseudo-random noise, no persistent structures. Unpredictable but not interesting.

Class IV – the interesting point. Complex non-periodic behaviour. Structures that emerge, interact, produce patterns that are neither ordered nor chaotic. It's the zone between order and chaos where interesting things happen.

Class IV is the one that matters. It's the critical point – the same balance Conway spent eight years chasing in the Game of Life. And in 2002, Matthew Cook (working with Wolfram) formally proved that Rule 110 – a single one-dimensional ruleset among the 256 possible – is Turing-complete.

Rule 110. Three bits of input, one bit of output, eight total rules. Simpler than the Game of Life. And universal.

Wolfram went further. In his controversial book A New Kind of Science (2002, over 1,200 pages that he wrote entirely himself, which already says something about the personality), he launched a much larger thesis: that the universe itself might fundamentally be a cellular automaton. That physical reality – the behaviour of particles, fields, forces, gravity – might be the result of simple rules applied uniformly to a discrete grid of “cells” at a sub-Planck scale.

It's a bold thesis. The scientific community received it with significant scepticism – it isn't easily falsifiable in the traditional sense, it requires enormous conceptual leaps, and Wolfram doesn't exactly have a reputation for modesty (understatement). But it hasn't been disproved. And the fact that systems as simple as Rule 110 are sufficient to produce universal behaviour is proof that the principle works: from simplicity, any level of computational complexity can emerge.

If the universe really is a cellular automaton, then God (or the Flying Spaghetti Monster) is a programmer who wrote very simple rules and then pressed “Enter.” Everything else – stars, galaxies, you reading this – is emergence. All consequence, no explicit design.

The cultural legacy

There's something strange about the cultural history of the Game of Life. There's nothing to win, nothing to lose, no objectives. It isn't a tool – it produces no practically useful results in any sense. It solves no real problems. It's a pure intellectual object. A puzzle with no solution because it has no question. And yet millions of people have implemented it. In every imaginable programming language. Python, Java, C, Rust, JavaScript, Haskell, Brainfuck (yes, really). On every platform. Arduino, Raspberry Pi, FPGA, GPU with CUDA. In every format. Terminal with ASCII art, graphical interfaces, physical LEDs, E-ink screens. On programmable calculators. On Game Boy. On two-euro microcontrollers.

It has become the “Hello World” of simulation. The first program you write when you want to understand emergence, cellular automata, complexity. And every time someone re-implements it – and they do it purely for pleasure – they repeat an act that Conway performed in 1970: taking an abstract idea and turning it into something concrete, tangible, visible.

I did it myself, years later – I implemented it in bash. There was no practical reason for it. I did it because I wanted to truly understand it, build it with my own hands, see how it worked. And this pattern repeats throughout hacker and open source culture. If you want to play the game of life – which sounds like it means something else entirely – you can download the script from here.

The Game of Life has been ported to systems Conway would never have imagined. Someone implemented it in Excel with formulas. Someone built it with real electronic circuits. Someone constructed it with quantum cellular automata. Someone used it to generate music (every live cell is a note). Someone made it three-dimensional. Pure pleasure in building something that works, that does what it should do, that is elegant in its simplicity. It's the practical demonstration that mathematical beauty exists.

Back to the grid

That Flash grid I was staring at all those years ago is still in my memory with a strange clarity, like the feeling of looking at something that made no sense. Today, though, I know it made more sense than I could have imagined. Four rules, no objective, no designer saying “now do this, now do that.” And the result was – and is – one of the most elegant demonstrations that complexity doesn't need an author. That it can emerge from nothing.

Von Neumann had asked: can a machine reproduce itself? Conway had searched for the simplest possible system that showed interesting behaviour. And what he found was something much larger: proof that universal computation can emerge from binary cells and four elementary rules. And everything else – the gliders, the guns, the logic circuits, Turing-completeness, the hypnotic beauty of the patterns that emerge – is consequence. Pure, inevitable consequence.

And perhaps this is why that Flash grid stayed with me for years, even without understanding it. Because at some unconscious level I could sense that there was something fundamental inside it. Something that spoke to how the universe works – not literally, perhaps, but as a metaphor. As a demonstration that simple rules, applied consistently, produce everything we see around us. That the complexity of the world – ourselves included – might simply be a consequence of rules we don't yet know how to read.

To quote an old UAAR slogan: “The bad news is that God doesn't exist. The good news is that you don't need him.”

Sources and further reading

Foundational papers and books – Gardner, M. (1970). “Mathematical Games: The Fantastic Combinations of John Conway's New Solitaire Game 'Life'“. Scientific American, 223(4), 120-123. – Von Neumann, J. (1966). Theory of Self-Reproducing Automata. University of Illinois Press. – Wolfram, S. (1983). “Statistical Mechanics of Cellular Automata”. Reviews of Modern Physics, 55(3), 601-644. – Berlekamp, E. R., Conway, J. H., & Guy, R. K. (1982). Winning Ways for Your Mathematical Plays, Volume 2: Games in Particular. Academic Press.

Turing-completeness and implementations – Rendell, P. (2000). “A Turing Machine in Conway's Game of Life”. – Chapman, P., et al. (2006). “OTCA Metapixel – Life in Life”. – Cook, M. (2004). “Universality in Elementary Cellular Automata”. Complex Systems, 15(1), 1-40.

Online resources – LifeWiki: https://conwaylife.com/wiki/ (the definitive resource, cataloguing thousands of patterns) – Wikipedia: https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life – Gosper's Glider Gun: https://en.wikipedia.org/wiki/Gun_(cellular_automaton) – Rule 110: https://en.wikipedia.org/wiki/Rule_110 – Turing completeness: https://en.wikipedia.org/wiki/Turing_completeness

Pattern explorers – Online simulators: https://playgameoflife.com/ – Golly (dedicated software): http://golly.sourceforge.net/

Interviews and biographical material – Numberphile – John Conway interview series

Discuss...

#GameOfLife #Conway #CellularAutomata #TuringComplete #Complexity #EmergentBehaviour #Mathematics #Wolfram #ComputerScience #Hacker #Writing

Same film, next scene.

Friday afternoon – because critical migrations always happen out of hours. I'm migrating a system from Red Hat 7 to Red Hat 9. Why? To support the new version of Charon-SSP, the Stromasys emulator that lets SPARC hardware run on x86. All of this to keep alive a virtual machine running Solaris 9, an operating system from 2002 that went end-of-life in 2014. It's a layered structure, each level propping up the one below. One of those classic houses of cards you can't quite understand how it stays balanced.

Welcome to the world of legacy systems. A world where “modernising” often means finding increasingly creative ways to change nothing at all, and where communities and old-school sysadmins are the ones guarding infrastructure that corporations abandoned long ago. Try asking Oracle for Solaris support: they'll laugh in your face.

The numbers

In January 2025, the UK government published a report that should have rattled a few chairs at Westminster. Twenty-eight percent of central government IT systems are classified as legacy – up from 26% in 2023. Estimated productivity losses? Forty-five billion pounds. In 2024, the NHS recorded 123 critical IT system crashes. One hundred and twenty-three.

But wait, because the numbers get even more interesting when you look at the banking sector. COBOL – a programming language dating back to 1959 – still processes 95% of global ATM transactions, 43% of the world's banking systems, and around 3 trillion dollars of commerce every day. Every day. It's estimated there are still 220 billion lines of COBOL code in production.

And Windows XP? The one Microsoft stopped supporting in 2014? Today, 1-2% of internet-connected devices still run it. Sounds small until you realise we're talking about millions of machines. And not your grandad's PC: we're talking about MRI scanners in hospitals, industrial control systems, bank ATMs. Critical devices that can't be updated because the software controlling them only runs on XP, and re-certifying the entire system would cost more than building a new one.

Remember WannaCry in 2017? The ransomware that paralysed 75,000 computers in 99 countries? The NHS was devastated. And do you know how many Windows XP machines the NHS had in 2019 – two years after the attack, five years after end-of-support? 2,300.

At this point in the story one might say “right, the problem is clear: legacy systems are dangerous and need replacing.” And that would be the easy narrative – the one that consultants selling “digital transformation” love, and vendors wanting to sell licences love. What if I told you that a Solaris 11 system, properly isolated in a VLAN, is significantly more stable and secure than a shiny new Ubuntu 24.04 LTS?

Reality, as always, is more complicated.

Problems upon problems

Here's the fundamental issue: we use the word “legacy” as if it meant one thing, when it actually covers at least three completely different situations.

Type 1: Unavoidable legacy Solaris 9 on SPARC hardware controlling industrial machinery. Windows XP on MRI scanners. Systems where hardware and software are inseparable, where an upgrade would require replacing equipment worth millions, where re-certification for medical or industrial use would take years and fortunes. These systems are legacy out of necessity, not negligence. There's no fault here. There's only the reality of a technological ecosystem where certain devices have 20-30 year lifespans and the software controlling them can't be changed without changing everything else.

Type 2: Avoidable legacy CentOS 7, for instance. End of support: 30 June 2024. Available alternatives: AlmaLinux, Rocky Linux, migration to RHEL. Cost of migration? Economically: it depends. In time, resources, learning: enormous. How many CentOS 7 systems are still in production today? Too many. Why? Because nobody wants to pay RHEL licences, because “we'll do it next quarter,” because “there are other important things to deal with,” because “if it ain't broke, don't fix it.” This is legacy by choice – or rather, by inertia. It's an organisational decision, not a technical one.

Type 3: Non-legacy perceived as legacy Take COBOL on modern IBM mainframes. Today's mainframes aren't the ones from the 1970s – they're immensely powerful machines, with dedicated processors, hardware security, 99.999% uptime. The COBOL running on them is the same as ever, but the underlying infrastructure is current. Is the code legacy, or the platform? And if the platform is modern, can we still call it legacy? The distinction is fundamental because it determines the strategy. A Type 1 system needs to be isolated and protected. A Type 2 system needs to be migrated. A Type 3 system needs to be left alone. Try explaining that to a CTO who just finished reading a Gartner report on “legacy modernisation.”

From a thread on TheLayoff:

“FWIW, there's a very good chance that your electronic footprint on any given day has passed through a piece of SPARC equipment running Solaris, and that will continue to happen for a good portion of your lifetime.”

Would you believe me if I told you I've seen original BSD systems with eleven years of uptime?

The real problem isn't the machines

Here we get to the heart of the matter. And the answer will surprise you: the real problem with legacy systems isn't technological. It's human.

Let's talk about the “COBOL Cowboys” – retired programmers called back on consulting contracts when something breaks. They're the last generation that knows how those systems actually work. When they leave, they take decades of undocumented knowledge with them. According to Deloitte, companies have seen a 23% decline in mainframe workforce over the last five years, with 63% of those positions left unfilled. It's not that there's no money to hire – it's that there's nobody to hire. Young developers don't want to learn COBOL. It's “unsexy.” It's “archaic.” It's “boomer stuff.”

From ComputerWeekly:

“The retirement of the generation of experts who possess in-depth knowledge of Cobol systems is leading to a severe knowledge shortage. They have knowledge not only of the Cobol programming language, but also of the specific systems they have worked on and built over the years” – Tijs van der Storm, CWI/University of Groningen

And so we find ourselves in a paradoxical situation: systems processing trillions of dollars a day, managed by people who might die of old age before anyone learns to replace them. Knowledge transfer never happened. Documentation – where it exists – is outdated, incomplete, written in a language nobody understands anymore. And every year that passes, the gap widens.

This is the real legacy problem. Not the systems. The people.

When modernisation fails (spoiler: often)

There's a story that people in the UK know well, but that strangely never comes up when “digital transformation” is being discussed. It's called the National Programme for IT, or NPfIT.

Launched in 2002, it was the largest public sector IT project in British history. The goal? Modernise the entire NHS IT infrastructure. Initial budget: 6 billion pounds. Planned completion: 2010.

In 2011, after nine years of delays, exploding costs, vendors abandoning the project, and a system that simply didn't work, the UK government announced the dismantling of NPfIT. Final estimated cost: over 10 billion pounds. For a system that was never completed.

What went wrong? Practically everything. Top-down decisions made by politicians who didn't understand technology. Rigid contracts with vendors who didn't understand the NHS. Resistance from medical staff who hadn't been consulted. Continuously shifting requirements. Impossible integrations with existing systems.

From TechMonitor:

“A lack of digital and procurement capability within government has led to wasted expenditure and lack of progress on major digital transformation programmes.”

The lesson? “Modernising” is not automatically better than “maintaining.” Sometimes, the legacy system that works is preferable to the modern system that never will. But this lesson, apparently, we haven't learned. Because the dominant narrative remains the same: legacy = bad, modern = good. And consultants keep selling the shiny new thing.

Strategies that actually work

TL;DR: There is no single solution. There's a matrix of options ranging from virtualisation to isolation, from refactoring to API wrapping. The choice depends on the type of legacy, the budget, and the acceptable level of risk.

The Gartner 7Rs (yes, they have a name for everything):

1. Retire – Switch it off. Only works if nobody's actually using it.
2. Retain – Keep it as is. Sometimes the best choice.
3. Relocate – Move it to new infrastructure without changes.
4. Rehost – “Lift and shift” to cloud. Changes the hardware, not the software.
5. Replatform – Minimal changes to run on a modern platform.
6. Refactor – Rewrite parts of the code while maintaining functionality.
7. Rearchitect – Completely redesign. The riskiest and most expensive.

Virtualisation and emulation For systems on proprietary architectures (SPARC, VAX, Alpha, PA-RISC), solutions like Stromasys Charon emulate the original hardware on x86-64 platforms. The operating system and software don't change – only the iron underneath does. For legacy x86 systems (Windows XP, Server 2003, old Linux), standard virtualisation (Proxmox, VMware, KVM) allows you to “freeze” the environment and keep it running indefinitely. I've seen Proxmox setups running Windows 3.11. I'm not joking.

Network isolation If a system can't be patched, it can at least be isolated. Dedicated VLANs, restrictive firewalls, air-gap where possible. It doesn't fix the problem, but it limits the impact in case of compromise.

API wrapping Put a modern REST layer in front of a legacy system. The mainframe keeps doing what it knows how to do; the outside world talks to the API. This is the strategy many banks use to expose COBOL functionality to mobile applications.

The public sector: a special case

Those who work in the public sector know that the dynamics differ from the private sector in ways that make the legacy problem even more complex.

Multi-year budgets. You can't decide in January to modernise a system and have the money by March. Funding cycles are long, rigid, subject to political priorities that change with every election.

Procurement. Buying software in the public sector is a bureaucratic nightmare. Tenders, compliance requirements, impact assessments, GDPR, accessibility. A purchase that takes a week in the private sector takes months here.

Compliance. Systems handling health, education, or tax data are subject to stringent regulatory requirements. You can't simply “migrate to the cloud” – you have to demonstrate that the cloud complies with an endless list of standards.

Service continuity (which in my view is the core problem). If a private company's system goes down for a day, they lose money. If a system managing national exams, or medical prescriptions, or pension payments goes down, the consequences fall on real people with no alternatives. The risk of downtime during a migration is often simply unacceptable.

And then there's the political dimension. Every government wants to announce its own “digital revolution.” Nobody wants to inherit the previous government's problems. And so projects get started, abandoned, restarted, re-abandoned, in an endless cycle of waste.

NPfIT wasn't an exception. It was the rule.

The uncomfortable question

At this point, the question nobody wants to ask is this: what if some legacy systems were simply… better? Not better in an absolute sense, but better for their specific purpose?

Let me tell you something. I worked for years in environments dealing with large-scale Oracle infrastructure – the company that sells “cloud transformation” and “modern infrastructure” to half the world. And among other things, you know what got managed day to day? Old ZFS storage. Stuff that, on paper, should have been “modernised” years ago. Those machines had been running since before Docker existed, before Kubernetes, before “cloud native” became a term. And they worked. Quietly. Without drama. Nobody was in any hurry to replace them. Why would they be? In pursuit of what advantage, exactly?

The COBOL processing bank transactions has been optimised for sixty years. Every bug has been found and fixed. Every edge case has been handled. Every possible scenario has been tested in production billions of times. It's code that has achieved a kind of perfection through Darwinian evolution. Rewriting it in Python would mean starting from scratch. New bugs. New untested scenarios. Years of instability before reaching the same level of reliability.

And in the meantime? In the meantime, the legacy system keeps working. There's a reason banks aren't in a rush to abandon mainframes. It's not ignorance. It's not laziness. It's that they've done the maths and understood that the risk of the new outweighs the cost of the old. And the old administrators have retired. But this is an uncomfortable truth. It doesn't sell well in PowerPoint presentations. It doesn't generate consulting contracts. It doesn't make tech headlines.

And so we keep talking about “modernisation” as if it were automatically a good thing. As if “new” meant “better.” As if technology had a moral direction.

So what?

Legacy doesn't mean old – it means abandoned. The problem is never technical – it's always organisational. And “modernising” is not automatically better than “maintaining.”

If there's one lesson, it's this: be suspicious of anyone with simple answers to complex problems.

Every time I hear some manager say “we need to automate everything with AI,” I think about the software pachyderms holding up half of critical infrastructure. I think about the time it would take to train a model on COBOL written in 1987 with no documentation. I think about how long it would take to migrate a Java 1.7 system running on Solaris 9. I think about the hours spent reverse-engineering platforms still running Lotus Notes. I think about the costs. I think about the risks. And then I think that those same managers don't have the budget to hire juniors willing – and why should they be, when the IT world is moving in a completely different direction – to learn systems that have been decommissioned for at least thirty years. And I laugh. Bitterly, but I laugh. Then I take a few drops of CBD to calm myself down.

Before talking about artificial intelligence – and those who know me know I'm not against AI at all – perhaps we should make sure that human intelligence doesn't retire, taking years of undocumented knowledge with it. But that, evidently, is a less sexy priority to put on the slides.

Sources and further reading

UK government reports – NAO: “The sustainability of government IT” (January 2025) https://www.nao.org.uk/reports/local-government-financial-sustainability-2025/ – NHS Digital: Infrastructure assessment reports https://www.bma.org.uk/advice-and-support/nhs-delivery-and-workforce/the-future/building-the-future-healthcare-infras

COBOL and mainframes – Reuters: “Banks scramble to fix old systems” (Commonwealth Bank Australia cost analysis) https://www.reuters.com/article/technology/banks-scramble-to-fix-old-systems-as-it-cowboys-ride-into-sunset-idUSKBN17C0CN/ – IBM: “COBOL Modernization” https://www.ibm.com/think/topics/cobol-modernization

Legacy virtualisation – Stromasys: “What are legacy systems” https://www.stromasys.com/resources/what-are-legacy-systems-challenges-benefits/ – Proxmox Forums: discussions on legacy system virtualisation https://forum.proxmox.com/tags/legacy/

Sector analysis – Gartner: 7Rs of Application Modernization https://www.techtarget.com/searchCloudComputing/tip/Use-the-7-Rs-to-develop-an-app-modernization-strategy – Deloitte: Mainframe workforce decline study https://www.deloitte.com/us/en/insights/topics/technology-management/tech-trends/2023/future-mainframe-technology-latest-trends.html – WSJ: How AI Can Rev Up Mainframe Modernization https://deloitte.wsj.com/cio/how-ai-can-rev-up-mainframe-modernization-2e3c1c4a

Case studies: failures – Computer Weekly: “What went wrong with the National Programme for IT” https://www.computerweekly.com/opinion/Six-reasons-why-the-NHS-National-Programme-for-IT-failed – NAO: Post-implementation review NPfIT https://www.nao.org.uk/reports/review-of-the-final-benefits-statement-for-programmes-previously-managed-under-the-national-programme-for-it-in-the-nhs/

Security – WannaCry incident reports https://any.run/malware-trends/wannacry/ – NHS Windows XP audit findings (2019) https://www.verdict.co.uk/windows-xp-nhs/

Discuss...

#LegacySystems #Sysadmin #COBOL #Solaris #Linux #PublicSector #DigitalTransformation #Mainframe #OpenSource #Infrastructure #Writing

I remember closing the book with an unpleasant feeling. Morozov doesn't give you the satisfaction of choosing a side in history. He forces you to see that technology amplifies everything—the good and the bad, freedom and control. And that authoritarian regimes have a very steep learning curve, unfortunately. Fifteen years later, the young people in Tehran are trying again: they're taking to the streets trying to overthrow the regime. In the West, I thought we had learned our lesson, that we would stop projecting our technological fantasies onto real protest movements. Obviously, I was wrong.

Iran 2009, or when Twitter (didn't) overthrow a regime

To understand why Iran 2026 is déjà-vu, we need to go back 17 years. June 2009. Mahmoud Ahmadinejad is re-elected president of Iran with 63% of the vote. The opposition—led by Hossein Mousavi—cries fraud. Millions take to the streets. Tehran fills with green. It's the explosion of the “Green Movement.” And here begins the narrative that would define a decade. CNN headlines: “Iran's Twitter Revolution.” Time Magazine puts Twitter on the cover with the Iranian flag. Andrew Sullivan—a famous blogger at the time—obsessively tweets using #iranelection and is called “the voice of the Iranian people.” Western media cite tweets as if they were dispatches from a war zone. The story was beautiful: young Iranians, tech-savvy and hungry for democracy, were using Twitter to organize protests, coordinate demonstrations, evade regime censorship. Facebook to plan, Twitter to coordinate, YouTube to document. It was the digital revolution overthrowing a dictatorship. Technology defeating repression. The good guys defeating the bad guys. The US State Department was so convinced of Twitter's importance that Jared Cohen—an official—sent an official email to Twitter asking them to “delay scheduled maintenance” so as not to interrupt the Iranian protests. Twitter agreed.

Then came Golnaz Esfandiari, an Iranian journalist for Radio Free Europe/Radio Liberty. Where did the tweets actually come from? In June 2010, a year after the protests, Esfandiari published an article in Foreign Policy titled “The Twitter Devolution.” She wrote:

“Western journalists who couldn't reach—or didn't bother reaching?—people on the ground in Iran simply scrolled through the English-language tweets posted with tag #iranelection. Through it all, no one seemed to wonder why people trying to coordinate protests in Iran would be writing in any language other than Farsi.”

Question: Why would Iranians organizing protests in Iran write in English? Esfandiari had identified the main Twitter hubs commenting on the Tehran protests and discovered something embarrassing: one was in the United States, one in Turkey, one in Switzerland. The latter's profile stated they “specialized in urging people to take to the streets.” She interviewed Mehdi Yahyanejad, manager of Balatarin (one of the most popular Farsi-language websites) who said:

“Twitter's impact inside Iran is nil [...] Here [in the United States], there is lots of buzz. But once you look, you see most of it are Americans tweeting among themselves.”

Iranians—the real ones, in the streets—used SMS, phone calls, word of mouth. Traditional methods. Twitter was mainly useful for one thing: letting the world know what was happening. Documentation, not organization. But the numbers were even worse. In his 2011 book, Morozov cited data that made everything even clearer: only 19,235 Twitter accounts registered in Iran (0.027% of the population) on the eve of the 2009 elections. And many Green Movement sympathizers had changed their Twitter location to “Tehran” to confuse authorities, making it nearly impossible to distinguish whether people tweeting from Iran were in Tehran or, say, Los Angeles. An Al-Jazeera analysis cited by Morozov clarified that fact-checking during the protests had confirmed only 60 active Twitter accounts in Tehran. Sixty. And when Iranian authorities tightened their grip on online communications, that number dropped to six.

Vahid Online, a prominent Iranian blogger who was in Tehran during the protests, dismantled the Twitter Revolution thesis even more directly:

“Twitter never became very popular in Iran. [But] because the world was watching Iran with such [great interest] during those days, it led many to believe falsely that Iranian people were also getting their news through Twitter.”

Morozov put it with a perfect metaphor:

“If a tree falls in the forest and everyone tweets about it, it may not be the tweets that moved it.”

At this point in the story one could say “okay, the protests happened in Iran and the West encouraged and celebrated them. What's wrong with that?” Nothing, except that the ayatollah regime learned the lesson. This was the part of Morozov's thesis that had really shaken me. In plain terms, while the West was self-celebrating the “Twitter Revolution,” the Iranian government was taking notes. They understood that social media could be more useful to them than to activists. They could track who posted, they could identify protest leaders, they could infiltrate groups, they could use data to arrest, torture, kill. The 2009 protests were brutally suppressed. The Green Movement failed. And the regime emerged stronger, more experienced, more prepared to use technology as a weapon of control. But we were the good guys helping, right? Esfandiari and Morozov tried to tell us we were doing everything wrong, that we were projecting our fantasies and underestimating authoritarian regimes. Did we listen? Evidently not.

Iran 2026: same film, different cast

December 28, 2025. Protests begin in Iran. Economic crisis, the rial—Iran's currency—collapsed to 1.4 million per dollar, 40% inflation, UN sanctions reimposed in September, the entire Iranian “Axis of Resistance” in tatters after the 12-day war with Israel in June. The streets fill. First Tehran, then the whole country. 31 provinces. Millions of people. And of course, social media explodes. Twitter/X fills with videos, slogans, messages of solidarity. Western media cite tweets as primary sources. Reza Pahlavi—the exiled heir of the Shah deposed in 1979—calls for protests from his social accounts. Persian TV channels in exile (Manoto, Iran International) broadcast 24/7. The US State Department operates a Persian-language Twitter account (@USABehFarsi) constantly posting messages of support. Repetita (non) iuvant. It's 2009 again. Same narrative, same enthusiasm, same conviction that this time—this time for real—Twitter and social media will overthrow the regime. Then, on January 8, 2026, on the twelfth day of protests, the Iranian regime does something interesting. It shuts off the internet. Completely.

And I, being a good nerd who doesn't sleep, lives at night, and does things better left unsaid—sorry, the statute of limitations hasn't expired yet—asked myself: wait. If the internet is off in Iran, where is all this content coming from? Who is telling this story? And above all: are we making the same mistake as 2009 again? So, browsing here and there, I came across a long article by Shahram Akbarzadeh—professor of “Middle East & Central Asian Politics” at Deakin University—titled “The web of Big Lies: state-sponsored disinformation in Iran.” And I started reading.

Before moving forward: stop

Let's make one thing clear right away, because I already know someone will misunderstand: I stand in solidarity with those protesting in Iran. Completely. A theocratic regime that kills protesters—estimates range from 44 to 20,000 dead, impossible to know for certain precisely because of the blackout—deserves nothing but condemnation. The reasons for the protests are real, legitimate, understandable. Devastating economic crisis, systematic repression, 47 years of religious dictatorship. Those who take to the streets risk their lives. And they do.

But solidarity doesn't mean suspending critical thinking. It doesn't mean uncritically accepting every narrative being sold to us. It doesn't mean ignoring who is constructing this narrative, how and why. On the contrary. If we truly care about the Iranians who are protesting, we have a duty to understand what's really happening. Because wrong narratives have real consequences. And the consequences are always paid by them, not by us tweeting from the couch. So: solidarity yes, but also questions, if no one minds.

Technical Box: the evolution of digital censorship

TL;DR: Iran didn't simply “pull the plug.” It implemented the most sophisticated layered censorship system ever seen, which leaves infrastructure apparently normal while completely isolating the population. It's precision censorship, not sledgehammer censorship.

8:30 PM IRST (5:00 PM UTC). NetBlocks, the organization that monitors global connectivity, registers a sudden collapse: Iran goes from 100% to ~3% connectivity in a few hours. Not just mobile, also landlines, also phones. Calling into Iran from abroad? Impossible. Journalists trying from Dubai can't connect. Families abroad can't reach relatives in Tehran. Total blackout. But there's something curious. BGP routes—the paths that make the internet work—remain visible. Iranian servers continue responding to pings. From outside, the infrastructure looks normal. Cloudflare, IODA (Georgia Tech), all traditional monitoring systems see Iran still “online.” Yet user traffic has dropped 97%. How is this possible? To understand what happened on January 8, we need a step back. Iran has developed three generations of shutdowns, each more sophisticated than the last:

2019—Brute Force: During the November 2019 protests (which caused ~1,500 deaths), the regime simply removed BGP routes. It's like ripping out cables: crude, visible, it took 24+ hours to implement because every ISP had to do it manually. Economically devastating—banks stopped, the economy collapsed for six days.

2022—”Digital Curfew”: During the Mahsa Amini protests, selective targeting. They shut down cell towers in specific areas, slowed internet during protest hours (4:00-10:00 PM), blocked specific apps (WhatsApp, Instagram). More refined, less expensive.

2025-2026—”Stealth Blackout”: The final form. And here it becomes technically fascinating.

The current system operates at a single national chokepoint—all Iranian ISPs converge at a few state-controlled exit points. There, a layered system filters everything:

Layer 1—DNS Poisoning: Any DNS query for foreign domains gets redirected to 10.10.34.34—a private IP serving a generic block page. You search for google.com? You get an Iranian server saying “domain not found.”

Layer 2—Protocol Whitelisting: Only three protocols pass: DNS (port 53), HTTP (port 80), HTTPS (port 443). Everything else gets silently dropped. SSH? No. OpenVPN? No. WireGuard? No. Any traditional VPN? No. Zero response, zero error, simply... nothing.

Layer 3—Deep Packet Inspection (DPI): The showpiece. System purchased in 2008 from Nokia Siemens Networks, continuously updated. The DPI inspects ALL HTTPS traffic: – Reads the SNI (Server Name Indication) field in the TLS handshake – Inspects the commonName field in certificates – Analyzes HTTP headers (case-sensitive!) – Injects TCP RST or HTTP 403 block pages on the fly – Selective throttling of encrypted traffic. Practical example: you try to visit Twitter via HTTPS. Your browser starts the TLS handshake. The DPI reads “twitter.com” in the SNI field—which travels in cleartext—and injects a TCP RST. Connection terminated. Twitter's server doesn't even know you tried to connect.

Layer 4—National Information Network (NIN): The national Iranian intranet. Domestic services (banking, some state news sites) work perfectly. It's the internet... but only Iranian.

The result: – From the perspective of BGP routers: everything normal – From the perspective of servers: ping responds, infrastructure up – From the perspective of users: the internet no longer exists

It's genius, in the technical sense of the term.

During the June 2025 blackout (during the war with Israel), some tools worked: – Psiphon: 1.5 million users maintained (one third of normal base) thanks to multi-protocol design – Ceno Browser: decentralized peer-to-peer, from 600 to 8,000 active peers – Tor bridges: shot up – Starlink: worked... for those who could afford it (hotels, offices, a few privileged people)

But in the current January 2026 blackout? Even Starlink has started suffering interference. The regime has learned. And the cost? The impact? – Hospitals: booking systems offline – Banks: digital transactions blocked – Pharmacies: impossible to verify electronic prescriptions – Shops: many didn't open (POS not working)

The real purpose isn't to stop the economy. It's to stop documentation. It's to obscure the massacres.

And Signal?

There's an interesting detail completely missing from the 2026 protests narrative, and the silence says a lot. Signal—the encrypted messaging app considered the gold standard for activists and dissidents—is barely mentioned. No articles, no appeals, no campaigns to bypass censorship. Yet Signal had been the weapon of choice during the 2017-2018 protests.

“Signal has always been advertised as the go-to application for dissidents or activists to stay secure from any state authority,”

said Mahsa Alimardani, researcher for Article19, in 2021.

But what happened? January 2021, after a massive migration from WhatsApp to Signal, the Iranian government labeled it as “criminal content” and blocked it completely. September 2022, during the Mahsa Amini protests, Signal was still blocked and had to launch a global campaign (#IRanASignalProxy) to create proxy servers to bypass censorship. January 2026? Total silence. Signal had been neutralized four years earlier. The technically superior option to all others—end-to-end encryption by default, zero metadata collection, run by a nonprofit—had already been removed from the playing field. The regime had done its homework. They had identified the most dangerous tool for them and crushed it while it was still small, years before it became mainstream.

And when the total blackout arrived on January 8, the debate about “Signal yes/no” was already obsolete.

But If the Internet Is off, how do they communicate?

This is the key question. On January 8, the internet dies in Iran. But videos keep arriving. Tweets continue. News continues. How?

First answer: Starlink Some Iranians—very few—have access to Starlink, Elon Musk's satellite service. Mainly hotels, offices, homes of wealthy people. These become the few “eyes” that can still communicate with the outside. But we're talking about an infinitesimal percentage of the population. And even Starlink is suffering increasing interference.

Second answer: before the blackout Many videos we see now were uploaded before January 8. They get re-shared, re-posted, presented as “real-time” but actually they're from days ago. Difficult to distinguish without precise geolocation and verifiable timestamps.

Third answer (the uncomfortable one): from outside Most of the narrative doesn't come from Iran. It comes from Persian TV channels in exile, from the Iranian diaspora, from social accounts of opponents abroad.

And here things get complicated.

Where does the narrative really start?

Euronews, January 10, 2026:

“Rumours have been particularly widespread throughout the two weeks of mass protests across Iran. Many of those rumours originate from anonymous users on social media platforms, and are being covered by media outlets, purely for headline purposes.”

The Conversation (academic analysis):

“Instagram and Twitter are filled with such reaction, making this form of engagement unusually widespread and visible... Iranian dissident news channels outside the country have become key but controversial sources of rolling information, shaping their own narratives from limited available reports.”

Miaan Group (Middle East research organization):

“Available evidence suggests that Pahlavi support is uneven, largely media- and social-media-driven, and not underpinned by organized infrastructure on the ground. Overstating exile-led narratives risks misreading the protest's domestic drivers and reinforcing Tehran's justification for repression.”

That is: by amplifying the narrative constructed from abroad, we're literally giving the regime justification to massacre protesters. And this isn't speculation. Jerusalem Post cites an Iranian expert:

“The monarchist Persian language media stations, especially Manoto TV, are manipulating images of protests in Iran to portray Reza Pahlavi as the only man whose name is heard in the streets, but this is a completely false and duplicitous depiction.”

We're talking about active manipulation. Not generous interpretation—manipulation. Real videos of protests, audio removed, false voice-overs added to make it seem like people are asking for the Shah's return. Black and white become increasingly similar to gray, don't they?

Who commands this revolution?

Reza Pahlavi. The exiled heir. 65 years old, has lived in the United States since he was 16 (when his father was overthrown in 1979). He explicitly called for protests from January 8, using his social channels. But how much support does he really have in Iran?

From CNN, with rare honesty:

“Analysts say that it is unclear what might be driving the renewed excitement for the royal family in Iran. Arash Azizi, an academic and author of the book 'What Iranians Want,' told CNN that, while Pahlavi 'has turned himself into a frontrunner in Iranian opposition politics,' he is also 'a divisive figure and not a unifying one.'”

And here lies the paradox. Iranians take to the streets for the collapsed economy, for personal freedoms, for the end of religious dictatorship, for civil rights. Not necessarily for the return of the monarchy. The Shah—Pahlavi's father—was himself a dictator, supported by the CIA, responsible for brutal repression. The 1979 revolution overthrew him precisely for this. But the narrative reaching the West? “They want Pahlavi.” Why? Because the exile TV channels say so. Because the Iranian diaspora—living in Los Angeles, London, Paris—supports him. Because videos are manipulated to make it seem like people are asking for him. And the regime? The regime uses exactly this narrative to justify the massacres. “See? It's a monarchist insurrection supported from abroad. They're foreign agents. Terrorists. The repression is justified.”

And we, therefore, what should we do? Stay silent?

Source analysis—aka “Who are we really citing”

Let's look at where the “news” about Iran comes from:

Iran International: Persian TV based in London. Funding: controversial, documented Saudi ties. Repeatedly accused of manipulating footage.

Manoto TV: Another Persian TV in exile. Declared pro-monarchist. Accused of false voice-overs.

HRANA (Human Rights Activists News Agency): Based in the United States. Founded by anti-regime activists. Provides the death toll numbers. Primary source for many Western media.

Reza Pahlavi: The heir himself. Worth commenting?

US State Department: Twitter account @USABehFarsi posting in Persian. Constant message: “we support you, overthrow the regime.”

Notice something? All major sources are based outside Iran, have a clear political agenda (anti-regime, often pro-Pahlavi), and in some cases there's documented content manipulation. And sources from Iran are nearly nonexistent, practically zero, because the internet is off. So the narrative is being constructed entirely from outside, in an information vacuum, by actors with specific interests. It's 2009 again. But in 2009, at least, they were naive Westerners tweeting about Iran thinking they were helping. In 2026 we have active video manipulation, exile TV channels constructing false narratives, the US State Department directly feeding Persian social media, Western media citing compromised sources as primary. All this while Iran is completely offline.

And meanwhile, the real people protesting for real reasons—economy, freedom, dignity—die every day. 2,000 dead. Maybe 6,000. Maybe 20,000. We'll never know for certain, precisely thanks to the blackout.

Am I naive? Perhaps

I return to that unpleasant feeling from ten years ago, when I closed “The Net Delusion.” Morozov doesn't let you win. He doesn't let you choose the good guys' side. He shows you that technology amplifies existing power dynamics. That authoritarian regimes learn. That Western slacktivism has real consequences.

And that the worst thing we can do is project our technological fantasies—the “Twitter Revolution”—onto real protest movements, with real people risking real lives. When we get the narrative wrong, when we amplify the wrong voices, when we manipulate content to conform to our preferred story... the consequences aren't paid by us. They're paid by them. The Iranians who protest don't need us to tweet #IranProtests from the couch. They don't need exile TV channels manipulating their videos. They don't need the US State Department publicly “supporting” them (giving the regime the “foreign interference” narrative).

They need us to understand what's really happening, to distinguish between real protests and constructed narratives, to be careful about who we amplify and why. They need us to stop believing that the internet solves political problems with a simple “click and share.” Because, as Morozov warned us, it often complicates them.

The internet is serious business, and should be treated seriously.

The blackout becomes permanent

In mid-January 2026, news emerged that could make everything even more disturbing. Iran International reported that the Iranian regime is finalizing a project to permanently disconnect the country from the global internet. And it's not just a theoretical project. It's almost operational.

The architecture of the great Iranian firewall

The details are chilling in their concreteness. The data center is bunkerized under the Fanap building in Pardis IT Town (20km from Tehran), designed to withstand missile attacks. It has a capacity of 400 server racks with Huawei hardware. Estimated cost is between $700 million and $1 billion. Logistics saw 24 containers enter Iran after the June 2025 war. Management is assigned to ArvanCloud (Iranian cloud) through a shell company called Ayandeh Afzay-e Karaneh. And the connections are clear: Fanap and its CEO Shahab Javanmardi are under US sanctions for ties to intelligence and IRGC.

How it would work technically

The system is based on the National Information Network (NIN)—a project started in 2005, gradually implemented from 2013 and fully operational since 2019. It's the Iranian intranet, in essence. It works like this: when you connect in Iran, your traffic passes through a centralized control point—the Telecommunication Infrastructure Company (TIC), state monopoly. There, the system decides. Request for a .ir site or NIN service? Goes on the domestic Iranian network. Request for a foreign site? Goes to the gateway toward the global internet (if active).

The “kill switch” simply disables the foreign gateway. And suddenly Iranian banks work (on NIN), local e-commerce works (on NIN), government services work (on NIN), Iranian emails work (on NIN), while Google, Twitter, Facebook, all the foreign internet is at zero. The difference from 2019 is substantial. Before, shutting off the internet meant paralyzing the economy—no banks, no payments, nothing. It cost billions per day. It wasn't sustainable long-term. Now instead? They can shut off the global internet while leaving everything else working. It's economically sustainable. They can maintain it for months.

A technological paradox

Here's something that struck me: technically it's sophisticated—very sophisticated. But strategically... there's a contradiction that almost doesn't make sense. Let's look at how modern surveillance works in Russia and the United States, not to defend it, obviously, but to understand the difference in approach.

The Russian model (SORM): The internet stays open and functioning. Users can access Google, Facebook, Twitter. But every ISP has installed an FSB “black box” that records everything. Every email, every click, every message. Storage is mandatory: 6 months of full content, 3 years of metadata according to the 2016 Yarovaya law. The FSB can retrieve data in real-time directly, without the ISP knowing what they're looking for. In 2023: 500,000 surveillance requests approved, only 272 denied. The result? Opponents use the internet normally, thinking they're free. They organize, communicate, build networks. And meanwhile the system records everything. When needed—20,000+ arrests for online speech between 2022 and 2024—they already have all the evidence, all the contacts, the entire map of social relationships.

The American model (PRISM): Same logic, different implementation. Since Snowden we know that NSA accesses Google, Facebook, Microsoft, Apple servers directly. They collect everyone's metadata. “We kill people based on metadata,” said former CIA director Michael Hayden. Appearance of democracy and free internet. Reality of invisible but total mass surveillance.

The Iranian approach (NIN): Shut off the internet when needed.

By shutting off the internet, Iran loses all the intelligence capability these systems provide. They can no longer track who talks to whom. They can't infiltrate groups. They can't monitor opponents' communications. They can't build maps of social networks. They literally remove the most powerful surveillance tool that exists from themselves. In exchange they get the ability to hide massacres for a few weeks. But at the cost of complete loss of intelligence during the blackout, blatant evidence of authoritarianism, economic damage even with NIN functioning, international isolation, and demonstration of their own fragility.

Russia and the USA have understood something that Iran seems not to have grasped: invisible control is infinitely more effective than visible control. You let people think they're free, let them use the internet, let them communicate. And meanwhile you record everything, analyze everything. When needed, you strike with surgical precision having all the necessary evidence. Iran has built a visible digital cage. One that declares to the world “we're an authoritarian regime terrified of our population.” One that eliminates its own surveillance capability precisely when it would need it most. It's the difference between long-term thinking (building permanent intelligence systems) and short-term thinking (hiding today's massacres). SORM and PRISM are invisible dystopias, and they work precisely because people don't see them. NIN is visible dystopia. And visible dystopias tend to generate revolutions, and fail soon.

IranWire reports that the plan is to maintain the blackout at least until the Iranian New Year, March 20, 2026.

It is, in essence, an act of desperation. The general population (level 1) will have only NIN, zero external access. “Authorized” professionals (level 2) will have NIN plus filtered internet. Government, IRGC and elite (level 3) will have full access. Every connection is tracked via national ID and phone number. Every access is attributable. And when they reactivate the internet—even partially—they'll know exactly who used Starlink, who used a VPN, who shared videos.

The model, needless to say, is China. The Chinese Great Firewall blocks foreign services but replaces them—Baidu instead of Google, Weibo instead of Twitter. China offers you an alternative, even if controlled. Iran? Iran can simply shut everything off and force you onto the national network. And with Huawei providing hardware and expertise (the same ones who built the Chinese system), and Russia providing advanced DPI technology (Protei), they have all the puzzle pieces.

And we're back to square one, as usual.

Tor: the infinite technological war

While Starlink makes headlines as the only tool of freedom, there's a tool that for nearly 20 years has been playing hide and seek with authoritarian regimes. Tor—The Onion Router—is historically the tool of choice for those living under censorship. During the Chinese Great Firewall. During the Russian invasion of Ukraine. In Egypt during the Arab Spring. In Syria. And in Iran, repeatedly.

Every time Iran has experienced moments of crisis, Tor has seen massive usage spikes:

2009—Green Movement: Tor relays shot up to 1.5 million Iranian users. The regime blocked direct connections. Users discovered Tor Bridges (non-public relays, harder to block). The regime learned.

2019—November, gasoline protests: Complete blackout for 6 days. Tor usage dropped to zero along with all internet. But when they turned it back on, the number of Tor users was higher than before. People had learned.

2022—Mahsa Amini, Woman Life Freedom: Nightly digital curfews (only mobile networks off 4:00-10:00 PM). Tor Bridges exploded. The regime implemented DPI to recognize Tor traffic and block it selectively.

And here's the interesting point. It's not a simple block. It's a continuous technological war.

In 2012, a Tor developer wrote on the official blog a phrase that should make us reflect:

“The Iranian government has, in less than a year and starting from scratch, caught up and now surpassed the Tor project in technical ability.”

What does this mean practically? That the Iranian regime has developed DPI systems capable of recognizing Tor traffic even if encrypted. Wait, how is that possible? Tor uses SSL/TLS exactly as if it were cleartext. All traffic is encrypted. How do they distinguish it? By watching behavior, not content. It's like recognizing someone by the way they walk even if they're wearing a disguise. Iranian DPI analyzes:

• Packet timing: Tor routes traffic through three relays, creating characteristic latency patterns
• Packet size: Tor uses 512-byte cells, an unusual size
• TLS handshake: The “hello, I'm a client” / “hello, I'm a server” sequence has specific patterns for each protocol
• Traffic flow: Tor sends data in bursts different from a normal HTTPS connection

They're not reading inside encrypted packets. They're watching from outside and recognizing the fingerprint. In real-time. On all national traffic. It's technically impressive.

But the Tor project responded

The strategy has evolved over time, essentially completely disguising Tor traffic to make it look like something else.

• Pluggable Transports: Tor in disguise. Traffic is made to look like normal web browsing, or Skype, or something else.
• Snowflake: Tor hiding behind WebRTC connections (those used for video calls). Hard to block without blocking all video calls.
• Meek: Tor disguising itself as traffic toward legitimate services like Microsoft Azure or Amazon CloudFront. To block it they have to block services they themselves use.
• Distributed Bridge Relays: Secret non-public relays, harder to identify and block.

And it works. Sometimes. Until the regime updates again. Snowflake gets identified? Tor develops a new pluggable transport. The regime recognizes it? The next one is developed. For every step forward by censors, Tor actively responds.

And now? January 2026? Here's a problem. Tor usage data always has a publication delay to protect users. But historically, the pattern is always the same: crisis and protests begin, censorship increases, Tor usage shoots up, the regime develops countermeasures, and finally total blackout if necessary. Given that we're in total blackout, Tor usage has crashed to zero—like in 2019. You can't use Tor if you don't have internet, not even censored internet. But when they turn it back on—and they will, even just partially—I expect to see a massive spike. Because Iranians have learned. Starlink costs too much. Normal VPNs get blocked. Tor, with the right bridges, still works.

But there's another paradox. Tor protects anonymity during connection. But the simple fact of trying to connect to Tor is identifiable by DPI. And traceable to your national ID. So the regime can see: who tried to use Tor (even if blocked), when they tried and for how long. And when the blackout ends, they might have a complete list of “technologically sophisticated dissidents” to arrest. It's the same logic as Starlink—retroactive use as evidence of dissent. The fight for free internet in Iran has been going on for nearly 20 years. It's not a new story. But even Tor can be defeated by a total blackout. And with the NIN/Huawei system becoming permanent, even when they turn the internet back on it might be an internet so controlled, so filtered, so tracked, that not even Tor will be enough.

Conclusions—and some questions

I started with Morozov, with that unpleasant feeling from ten years ago. With the discovery that the “Twitter Revolution” of 2009 was a Western projection, not an Iranian reality. And I've arrived here. Iran 2026. Same film, different cast. Same narratives constructed from abroad. Same amplification of exile voices. Same video manipulation. Same regime using all this as justification to massacre. But there's a crucial difference from 2009. In 2009, the regime had learned that the internet was useful to them (surveillance) but dangerous (documentation). In 2026, they've solved the equation radically: they've built a system to have internet when they need it (domestic NIN) and shut it off when they don't (kill switch toward the outside). 700 million—1 billion dollars. Huawei hardware. Russian DPI. Anti-missile bunker. 400 server racks. Operational by March 2026. It's no longer temporary and expensive censorship. It's permanent information control infrastructure. It's a digital cage.

Where does the content about Iranian protests come from while the internet has been off for 9+ days? Mainly from abroad. From exile TV channels with controversial funding. From diaspora living thousands of miles away. From sources with clear agendas and, in some cases, documented manipulation.

Who is driving the narrative? Pahlavi from the USA. Manoto TV altering audio. Iran International accused of false voice-overs. US State Department tweeting in Persian. Diaspora demonstrating with Shah flags.

Who is driving the real protests in Iran? Probably no one. Probably it's leaderless, organic, driven by economic desperation and 47 years of repression. The people in the streets shout “bread, work, freedom”—not necessarily “bring us back the Shah.”

But the narrative reaching us? That one talks about Pahlavi. About monarchy. About “Iranian Revolution 2.0.” Exactly the narrative the regime wants to justify the massacres. “See? Western plot. Foreign agents. Monarchist terrorists.”

And the gap between narrative and reality? It costs human lives. 2,000 dead? 6,000? 12,000? 20,000? We'll never know for certain, precisely thanks to the blackout that was supposed to be “temporary” and is becoming permanent.

Morozov was right

The internet, unfortunately, is not free by definition. Technology amplifies existing power dynamics. Authoritarian regimes learn, adapt, build increasingly sophisticated systems. The Iranian regime has spent 17 years—from 2009 to today—studying how to control the internet. They've invested billions. They've collaborated with China and Russia. They've developed DPI that recognizes Tor, systems that block VPNs, architectures that allow economically sustainable blackouts. And the technological “resistance”? It depends on Elon Musk donating Starlink—and he can decide to turn it off tomorrow. It depends on Tor Project playing whack-a-mole with Iranian countermeasures. It depends on individuals who risk arrest and torture to use circumvention technologies. It's not a fair fight. It never was.

Cyber-utopianism is a drug. It makes us feel good. It makes us feel like we're “helping.” That technology always wins. That the internet liberates. But reality is more complex, more uncomfortable. Technology is a tool. And like all tools, it can be used to liberate or to oppress. Authoritarian regimes have resources, expertise, and zero ethical constraints. The “resistance” has volunteers, limited budgets, and the weight of not wanting to cause harm. The Iranians who protest don't need us to celebrate Starlink as savior. They don't need us to amplify narratives constructed from abroad. They don't need our slacktivism. They need us to understand what's really happening. To distinguish between real protests and constructed narratives. To not give the regime the propaganda ammunition it needs. To stop believing that the internet solves political problems. They need us to finally learn the lesson Morozov was trying to teach us 15 years ago.

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