Well, I already finished the rewatch. I have never had a show hold such a chokehold on me, but wow, I am ready for round 3.

I have about 20 days before the move and still have so much to finish and do. I did not get a lot done today, shocking, but I have ambitious plans for tomorrow. I have to get rid of so much crap. How do I get rid of things I’m sentimentally attached to? I am seriously struggling with it.

I need to come up with a game plan tomorrow so that I can get back on track.

Thank you for your message. I am currently out of office — but will return at the end of the month.

Half a percentage point. That is how much a year of schooling has lost in wage value, in the American occupations most exposed to generative AI, since ChatGPT arrived in November 2022. It sounds like a rounding error. It is not. It is one of the first direct estimates of something economists have suspected for three years: the machine is coming for the part of your education that can be written down.

The number comes from a working paper posted to arXiv on 26 October 2026 by Eduardo Levy Yeyati, Darío Judzik and Juan Ignacio Barbiero of Universidad Torcuato Di Tella in Buenos Aires. It is titled “Practice Makes Perfect: Tacit Knowledge, Generative AI, and Returns to Schooling and Experience”, and it does something deceptively simple. It takes the workhorse equation of labour economics, the one that tells you how much an extra year in a classroom or an extra year on the job adds to your pay, and asks whether its coefficients moved when large language models went mainstream.

They did. In highly exposed occupations, the return to a year of schooling fell by 0.55 log points, roughly 7 per cent of what it had been. The return to experience did something stranger. It did not rise or fall uniformly. It rotated, like a seesaw. Early-career experience became more valuable. Late-career experience became less so. The pivot sits at about 18 years.

Put that next to two other pieces of 2026 research and a picture forms. PwC's Global AI Jobs Barometer, built from more than a billion job advertisements, finds the labour market splitting into two tracks, with the jobs where AI raises the bar for expertise growing twice as fast as the jobs where AI lowers it. And a field experiment led by the MIT economist David Autor finds that when patent lawyers trained alongside an AI assistant were later asked to work without it, the senior lawyers kept their gains while the juniors, on average, did not.

Together, the three studies describe a repricing. Codified knowledge, the stuff a degree certifies, is getting cheaper because a machine can supply it on demand. Tacit judgement, the stuff you only get by doing the work, is getting dearer, but it has a shelf life. For anyone who has just borrowed tens of thousands to buy a credential, that is uncomfortable news. Read carefully, it is also not the catastrophe the headline numbers suggest.

Seven and a Half Points a Year

To understand what moved, you need to know what was being measured. In 1974 the Columbia economist Jacob Mincer published “Schooling, Experience, and Earnings”, a slim book from the National Bureau of Economic Research that gave the discipline its workhorse. Mincer's insight was that if you take the logarithm of a person's earnings, you can model it as a straight-line function of their years of schooling plus a curved function of their years of work experience. The curve is concave: experience pays a lot early, then the gains flatten as people stop investing in new skills.

The schooling coefficient has an intuitive reading. Because the left-hand side is in logs, a coefficient of 0.075 means each additional year of school is associated with roughly 7.5 per cent higher hourly pay, holding experience constant. Economists call that 7.5 log points. Half a century of refinement later, it remains the default lens for asking what education is worth.

This matters for reading the new paper correctly, because the units are easy to garble. Levy Yeyati and his colleagues report that before ChatGPT, the return to a year of schooling in the most AI-exposed occupations was 7.5 log points. In the least exposed occupations it was just 1.7. After the release, the exposed-group figure fell by 0.55 log points relative to the control group. That does not mean wages fell by 0.55 per cent, nor that the degree premium collapsed by 7 per cent of your salary. It means the slope of pay against schooling flattened, from roughly 7.5 points per year to roughly 7 points per year. The 7 per cent figure is the decline in that slope relative to where it started: 0.55 divided by 7.5 is about 7.3 per cent.

A rough illustration helps. A four-year degree in a highly exposed occupation was previously associated with about 30 log points more pay than a high school diploma, all else equal (four years at 7.5 points each). At the post-shock rate, that becomes about 28 points. That arithmetic is mine, not the authors', and it ignores everything else that changed, but it conveys the order of magnitude. The degree still pays. It pays a little less, and in exactly the places where the technology bites hardest.

How a Degree Lost Half a Point

The study draws on the US Current Population Survey's outgoing rotation groups, the monthly household survey that asks a subset of respondents about their earnings. The authors use data from 2018 through June 2026, covering 655,919 observations of people aged 16 to 64 with a valid hourly wage. They date the shock to November 2022 and organise their years from November to October so that the ChatGPT release falls cleanly on a boundary.

To decide which occupations count as exposed, they use an index built by Edward Felten, Manav Raj and Robert Seamans and published in the Strategic Management Journal in 2021. Crucially, that measure predates ChatGPT, so it cannot have been contaminated by what happened afterwards. The paper compares occupations in the top quartile of exposure, which include software developers, financial managers and lawyers, with those in the bottom quartile, which include truck drivers, construction labourers and waiters. The middle two quartiles are set aside.

The core specification is a Mincer equation with the schooling and experience terms interacted with two switches: whether the occupation is exposed, and whether the observation comes after the release. The authors control for a long list of demographic and job characteristics, with fixed effects for month, state and occupation.

One technical choice deserves attention because it affects the result. High earners in the survey are top-coded: above a certain threshold, the Census Bureau records a cap rather than the true figure. That cap changed in April 2023, from a fixed value to a dynamic one, which happens to fall in the post-shock window. Top-coding is concentrated in the treated occupations: 11.5 per cent of that group is censored, against 0.7 per cent of the controls. The authors handle it with interval-censored maximum likelihood rather than imputation, and they test alternatives. Applying the pre-2023 cap throughout gives a schooling effect of minus 0.53 log points, almost identical to the headline. But a deliberately harsh check, which treats dynamically top-coded observations as exact values, shrinks the schooling estimate to minus 0.09. The authors flag this openly. It is the most important caveat in the paper, and anyone quoting the 0.55 figure should know it exists.

Other checks are reassuring. The pre-release schooling coefficients show no trend, and the break appears in the first year after release. A placebo that re-dates the shock to January 2020, to test whether the pandemic is doing the work, finds nothing. Dropping the technology sector “does little”. Swapping the Felten exposure index for the “GPTs are GPTs” measure developed by Tyna Eloundou and colleagues at OpenAI and the University of Pennsylvania gives a schooling decline of 0.42 log points, close to the baseline.

Experience Turns on a Hinge at Eighteen Years

The schooling result is the headline, but the experience result is stranger. In a standard Mincer setup, the value of an extra year of experience depends on how much you already have. A third year adds more than a twenty-third. What Levy Yeyati, Judzik and Barbiero find is that the shape of that curve changed after November 2022 in exposed occupations. At three years of potential experience, the return to an additional year rose by 0.26 log points. At five years, it rose by 0.23. At fifteen, the change is statistically indistinguishable from zero. At twenty-five years, it fell by 0.12. Under the baseline quadratic specification, the effect crosses zero at 18.1 years, with a standard error of 2.1.

The authors are careful about what this means. It is a change in the slope of the experience profile, not a statement that workers with 18 years of experience are the break-even point for winners and losers in pay. “Potential experience” is also a blunt instrument: it is simply age minus years of schooling minus six. It counts time since leaving education, not time spent doing the tasks AI now touches.

The heterogeneity analysis sharpens the picture. Among workers with an associate degree or higher, the early-career return rises by 0.43 log points at three years, and the late-career return falls by 0.12 at twenty-five. Among workers without a credential, the early gain is smaller and the late decline is not statistically significant. In other words, the rotation is strongest precisely among people who hold formal qualifications. The authors write that “wage differences by early-career experience become steeper after the shock” within that credentialed group.

Finally, the level effect. For a worker with 16 years of schooling and 15 years of experience in a treated occupation, the estimated wage change is minus 3.2 log points. That is a real cut, and it falls on exactly the profile of a mid-career graduate professional. But the authors stress that the level effect “is not itself a theoretical prediction”, and they say plainly that “the findings are not a forecast of long-run returns to education or experience.”

Codified Knowledge Was Always the Cheap Part

The theory behind the paper rests on an old distinction. In 1966 the chemist and philosopher Michael Polanyi published “The Tacit Dimension”, which contains the line “we can know more than we can tell.” Some knowledge can be written down, taught in lectures and tested in exams. Some can only be acquired by doing: the feel for when a contract clause will cause trouble, the instinct for which bug report is really an architecture problem, the sense of when a patient's symptoms do not add up.

In 2014 David Autor borrowed Polanyi's line for an NBER working paper titled “Polanyi's Paradox and the Shape of Employment Growth”. His argument was that computers had automated tasks that could be specified as explicit rules, and had struggled with tasks requiring tacit knowledge. That pattern, he argued, explained why employment had grown at the top and bottom of the wage distribution and hollowed out in the middle.

Generative AI scrambles that story. Large language models are not programmed with rules; they learn from enormous quantities of text, absorbing much of what humanity has managed to write down. They are, in effect, machines for supplying codified knowledge at near-zero marginal cost. Ask one to explain the doctrine of equivalents in patent law or the assumptions behind a discounted cash flow model, and it will usually produce a competent answer in seconds.

The Levy Yeyati model formalises three consequences. First, substitution: machine and worker codified knowledge are treated as perfect substitutes, so when the machine version becomes abundant, the worker version, proxied by schooling, loses scarcity value. Second, complementarity: practice-based judgement becomes more valuable when the codified knowledge it works on gets cheaper, steepening the early-career slope. Third, obsolescence: experience tied to the old way of doing the work loses value when the technology changes, flattening the late-career slope.

The paper concedes its estimates do not separately identify these mechanisms. The pattern is consistent with all three acting together, but does not prove it. Nor does the paper distinguish fields of study or institutional quality. A year of organic chemistry and a year of media studies count the same.

A Labour Market Splitting in Two

If the Levy Yeyati paper measures what workers are paid, PwC's 2026 Global AI Jobs Barometer measures what employers are asking for. Released on 15 June 2026, it analyses more than one billion job advertisements across 27 countries and territories on six continents.

Its central finding is a fork. In some occupations, which PwC calls professionalised, AI automates the routine parts of the job and pushes the remaining human work towards judgement and expertise. PwC's examples include radiologists and recruiters. In others, which it calls democratised, AI makes the work easier for non-experts to perform, lowering skill barriers and shifting roles towards less specialised activity. Its examples include IT service managers and medical secretaries.

According to PwC Belgium's release of the global results, “the 22% of jobs that are being professionalised are growing twice as fast as democratised jobs (52% of jobs)”, while “seeing 42% higher wage growth since 2021.”

Read alongside the earnings data, this is striking. The democratised track looks like the substitution story: AI takes over the codified core of a job, and the premium for having learned it shrinks. The professionalised track looks like complementarity: AI clears away routine work and leaves a residue of judgement that commands a premium. That the professionalised track is smaller but faster growing and better paid fits the idea that value is migrating towards tacit expertise.

PwC also reports that the average wage premium for AI skills in job postings rose to 62 per cent, from 57 per cent the previous year. Pete Brown, PwC's Global Workforce Leader, put the implication directly: “Organisations need to rethink how they develop talent if they want people to thrive in this new environment.”

Job advertisements capture what employers say they want, not what they pay individual workers, and PwC sells AI advisory services. Its findings are a large signal about demand, not a peer-reviewed causal estimate.

Junior Jobs That Ask for Senior Skills

The most pointed PwC finding concerns the bottom rung. Analysing 2.4 million entry-level job postings in the United States, the barometer finds that junior roles highly exposed to AI are seven times more likely to require “traditionally senior skills”, such as leadership and strategic thinking, than entry-level roles that are not exposed. Some accounts express this as 52 per cent of new skills against 7 per cent. That ratio fits the sevenfold headline, but the breakdown does not appear in PwC's public summaries, so the sevenfold figure is the safer one to quote.

Openings for these “seniorised” roles have grown 35 per cent since 2019, while other entry-level openings have fallen 10 per cent. The entry-level job is being redefined: employers want new hires who can do on day one what used to take years to learn.

Other data point the same way. Erik Brynjolfsson, Bharat Chandar and Ruyu Chen of Stanford's Digital Economy Lab have been tracking employment using payroll data from ADP, the largest payroll processor in the United States. Their paper “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence”, first released in August 2025 and revised on 12 August 2026 with data through June 2026, finds no evidence of widespread, economy-wide job displacement. But employment of workers aged 22 to 25 in AI-exposed occupations is now 19 per cent below where it would be had it kept pace with less exposed peers. Experienced workers show no comparable gap. The adjustment works mainly through reduced hiring of young people rather than layoffs, and it is concentrated where AI substitutes for human tasks rather than complementing them.

The Federal Reserve Bank of New York's tracker of the labour market for recent college graduates tells a similar story. In the third quarter of 2026, the unemployment rate for recent graduates eased to 5.2 per cent, but the underemployment rate, the share working in jobs that do not typically require a degree, rose to 42.5 per cent.

There is an apparent paradox here. If early-career experience is becoming more valuable, why are young people finding it harder to get hired? The Levy Yeyati paper measures returns among people who are employed. Once you are in the door, each year of practice is worth more than before. But the door is narrower, because the entry-level job, where codified knowledge was traditionally converted into judgement, is exactly what AI is eroding. The authors note that changes in who gets employed could partly explain their early-career estimates. The premium on early experience and the shortage of early jobs may be two faces of the same scarcity.

The Patent Attorneys Who Kept Their Gains

Which brings us to the most direct test of whether AI helps or hinders the acquisition of judgement. In September 2026 the NBER released working paper 35720, “Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting”, by David Autor, Tanya Rodchenko, Josh Martin, Zanna Iscenko, Scott Strand, David Pearl and Melissa Ferere. A revision followed in October.

The design is unusually clean for a workplace study. In a pre-registered randomised controlled trial, 133 practising patent lawyers at eleven US intellectual property firms were split into groups, with roughly two-thirds given access to a custom AI patent drafting assistant. Blinded expert patent attorneys scored all the work. The researchers measured performance with the tool and then, after three months, tested everyone on a core professional task without it: redlining an existing patent application.

With the tool, everyone got better. AI access raised the quality of work on benchmark drafting tasks by 0.34 standard deviations at 10 days and 0.38 at 90 days, with larger gains among junior lawyers. Dennis Crouch, the University of Missouri law professor who writes the Patently-O blog, noted that much of the improvement came from “avoiding awful work” rather than producing the very best applications.

Without the tool, the picture split. Treated lawyers outperformed controls by 0.32 standard deviations on the unaided redlining task. But that advantage came entirely from senior lawyers, whose gain was 0.45 standard deviations. Junior lawyers showed no average improvement. Their scores spread out: mediocre results became much less common, while both poor and good results became more common. The authors describe AI as acting as a “springboard” for some juniors and a “cushion” for others. Their conclusion is a sentence worth pinning above every graduate trainee's desk: “Foundational expertise may be a prerequisite for extracting durable skill from AI-assisted practice.”

Autor summarised the result to Fortune in a phrase: AI is “a performance equalizer, but a skill-disequalizer.” He added a warning aimed squarely at people starting out: “Young professionals need to beware of the illusion of competence.” Junior lawyers given the tool reported a surge in task satisfaction, the largest effect in the study. They enjoyed skipping the blank page and moving straight to a reviewer's role. The danger is that the satisfaction of reviewing a competent draft is not the same as acquiring the ability to produce one.

The caveats are substantial, and Fortune's reporting set them out. The paper is not peer-reviewed. Only 91 of the 133 lawyers completed the AI-free test. The firms declined a baseline skills test, so skill gains are inferred from random assignment rather than measured before and after. Fifteen of the 91 markups were flagged as possibly AI-assisted despite the ban; excluding them shrinks the senior advantage to 0.39 standard deviations at a looser statistical threshold, and the overall effect no longer holds. Five of Autor's co-authors are full-time Google employees and the sixth is a paid Google contractor, Google conducted and paid for the study, and the tool was Google's own. Autor is head of MIT's economics department and a Google Technology and Society Visiting Fellow. Three months is short compared with the years it takes to make a patent lawyer.

Still, the result rhymes with others. Erik Brynjolfsson, Danielle Li and Lindsey Raymond's study of more than 5,000 customer-support agents, published in the Quarterly Journal of Economics in 2025, found that AI assistance raised productivity by 15 per cent on average, with the biggest gains for less experienced and lower-skilled workers, while the most experienced saw small gains in speed and small declines in quality. And a field experiment by Hamsa Bastani and colleagues, published in the Proceedings of the National Academy of Sciences in 2025, found that Turkish high school students given unrestricted access to GPT-4 during maths practice scored 17 per cent lower once the tool was taken away, compared with students who never had it. A version with learning-protective guardrails largely mitigated the harm.

The pattern across all three is consistent. AI lifts novice performance in the moment. Whether it builds novice capability over time depends on what the novice already knows and how the tool is used.

Why Experience Expires

The other half of the rotation, the falling return at 25 years, connects to a literature on skill obsolescence that predates generative AI. In 2020 David Deming of Harvard and Kadeem Noray published “Earnings Dynamics, Changing Job Skills, and STEM Careers” in the Quarterly Journal of Economics. Using job vacancy data from Burning Glass Technologies covering 2007 to 2019, they showed that the earnings premium for graduates in technology-intensive subjects such as computer science, engineering and business declines rapidly as they gain experience.

Their model treats a career as a race between on-the-job learning and skill obsolescence. In fast-changing fields, the specific skills a graduate brings are replaced within a few years, which lowers the return to experience and flattens the age-earnings profile. Higher-ability STEM graduates also tend to leave STEM careers more often and at younger ages.

Generative AI may be turning a phenomenon that was confined to technology-intensive careers into something more general. If a large share of codified knowledge in law, finance, marketing and software is now supplied by a machine, then the experience of having done those tasks the old way may depreciate across the board. The Levy Yeyati paper's late-career finding is consistent with that reading, though the authors place less weight on individual late-career coefficients because the pre-trend test for them is weaker.

Here is the double bind for someone starting out. Early experience matters more than ever, because judgement is what AI cannot yet supply. But that experience may itself be technology-specific, and if the technology keeps shifting, its value will erode too. The patent lawyer study suggests one way out: seniors who already had deep foundations were able to absorb the new tool and come out stronger. Experience did not simply expire. It compounded, for those who had enough of it to build on.

The Debt Was Priced for a Different Market

None of this would matter so much if degrees were cheap. They are not. In the United States, Federal Student Aid reported in September 2026 that 42.3 million recipients hold federal student loans totalling more than $1.7 trillion. More than 9.3 million are in default, owing $234 billion. In England, the Student Loans Company's 2025-26 statistics put the higher education loan balance at £294.6 billion, and the provisional average balance for borrowers entering repayment in 2026 is £47,730. The House of Commons Library projects the outstanding balance could reach around £500 billion, in 2025-26 prices, by the late 2040s.

Those debts were taken on at prices set for a labour market in which the return to schooling was stable. If the premium is now shrinking in the fields most exposed to AI, the implied return on that investment shrinks with it. A loan agreement does not reprice when the asset it financed does.

It is worth being precise about the scale. A decline of roughly 0.55 log points per year of schooling, or 3.2 log points at the paper's illustrative mid-career profile, is a meaningful cut but not an annihilation. Even after the shock, the return to schooling in exposed occupations, roughly 7 points per year, remains far higher than the 1.7 points in the least exposed occupations. A degree is still associated with substantially higher pay. What has changed is the direction of travel and the reason for the premium. The share of the premium attributable to knowing things is falling. The share attributable to being able to do things is rising.

England's income-contingent repayment partly cushions graduates, because repayments fall when earnings do; many American borrowers have less protection. Either way, the risk sits with the person least able to diversify it: a young worker with a single human-capital asset and a large liability attached.

What the Numbers Do Not Say

First, the Levy Yeyati paper is a working paper, not yet peer-reviewed, and its headline schooling estimate is sensitive to how top-coded wages are treated. Its central identifying assumption, that greater exposure means a larger expansion of machine-supplied codified knowledge, is assumed rather than tested. The authors list possible confounds candidly: changes in who is employed, signalling and employer learning, and post-2022 shifts in worker composition.

Second, years of schooling are a crude proxy for codified knowledge. A degree also signals persistence, conscientiousness and the ability to learn. It provides networks, and it often functions as a legal or professional gatekeeper. None of those functions is obviously diminished by a chatbot, and the paper cannot separate them.

Third, each of the other studies has its own blind spots, from the Autor experiment's single tool to the descriptive nature of the payroll data. Their convergence is more persuasive than any one result.

Fourth, all of this describes the first three and a half years of a technology that is still changing quickly. The Levy Yeyati authors call their results a short-run repricing of existing stocks of human capital. Over the longer run, schooling choices, curricula, mentoring, occupational sorting and the organisation of entry-level work will all adjust. They close by asking “whether workers can continue to acquire the practice-based knowledge” that AI increasingly substitutes for in learning itself.

Building Judgement Without the Apprenticeship

So how should someone at the outset of a career think about a credential? The evidence suggests five principles, none of them comfortable.

Treat the degree as a foundation, not a product. Senior patent lawyers extracted durable skill from AI because they had foundations to build on, and the authors' conclusion that foundational expertise “may be a prerequisite” is an argument for deep formal education, not against it. What loses value is the degree as a certificate of facts possessed. What retains value is the degree as scaffolding for judgement. The goal is not to memorise what a model can recite, but to understand a field well enough to know when the model is wrong.

Test yourself without the tool. Autor's advice to Fortune was that the only reliable check on skill development is performing tasks without AI and evaluating the results. The Bastani study points the same way: students who used unrestricted GPT-4 as a crutch did worse once it was gone. If your employer gives you an AI assistant, the most valuable thing you can do for your own career may be to periodically do the work without it and compare.

Hunt for the practice, not just the job. Returns to early-career experience are rising while early-career hiring is falling. The scarce resource is not the qualification but the chance to convert it into judgement through supervised real work. Roles offering genuine apprenticeship, with feedback from experienced people on tasks that matter, are worth more than their starting salaries suggest.

Lean towards the professionalised track. Ask whether AI in a given role raises the bar for human expertise or lowers it. Roles where the machine handles the routine and leaves you the hard calls are growing faster and paying better. The question applies to specific jobs and employers, not just titles.

Plan for your experience to expire. Technology-specific know-how depreciates, so the defence is to keep renewing it, layering new techniques onto durable understanding, as the senior patent lawyers did, rather than swapping one set of specific skills for another.

For employers, the implication is sharper. Cutting entry-level hiring because AI can do the junior work is a decision to stop producing senior people. The juniors whose outcomes spread out in both directions in the Autor experiment are next decade's senior lawyers, or not.

A Credential Worth Holding, Priced Differently

What does it mean when the wage premium for education shrinks in the fields most exposed to the technology? The honest answer is that the premium was always paying for two things at once, and the market has started to separate them.

One part paid for possessing codified knowledge, and that part is falling, because a machine can now produce it in seconds. The other part paid for the capacity to learn, judge and build on that knowledge, and that part is holding up, perhaps rising, for those who get the chance to exercise it. The degree you paid for is not worthless. Its price has been revised, and the reason it is valuable has shifted from what it certifies you know to what it enables you to become.

For the worker carrying the debt, that is cold comfort, because the debt did not reprice. For the person deciding whether to start, it is a clearer guide than the noise suggests. The credential still pays, most of all to those who treat it as the start of an apprenticeship rather than the end of an education. Half a percentage point is a warning, not a verdict. The 18-year hinge is a reminder that judgement, too, has a shelf life, and the only defence is to keep building it.

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References and Sources

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17. Brynjolfsson, Erik; Li, Danielle; Raymond, Lindsey. “Generative AI at Work.” Quarterly Journal of Economics, 140(2), 889-942, 2025. Earlier version: NBER Working Paper No. 31161, 2023. https://www.nber.org/papers/w31161 ; https://econpapers.repec.org/RePEc:oup:qjecon:v:140:y:2025:i:2:p:889-942
18. Bastani, Hamsa; Bastani, Osbert; Sungu, Alp; Ge, Haosen; Kabakcı, Özge; Mariman, Rei. “Generative AI without guardrails can harm learning: Evidence from high school mathematics.” Proceedings of the National Academy of Sciences, 122(26), e2422633122, 2025. DOI: 10.1073/pnas.2422633122. https://econpapers.repec.org/RePEc:nas:journl:v:122:y:2025:p:e2422633122
19. Deming, David J.; Noray, Kadeem. “Earnings Dynamics, Changing Job Skills, and STEM Careers.” Quarterly Journal of Economics, 135(4), 1965-2005, 2020. DOI: 10.1093/qje/qjaa021. https://www.hks.harvard.edu/publications/earnings-dynamics-changing-job-skills-and-stem-careers
20. US Department of Education, Federal Student Aid. “(GENERAL-26-57) Federal Student Aid Posts Updated Reports to FSA Data Center.” Electronic announcement, 22 September 2026. https://fsapartners.ed.gov/knowledge-center/library/electronic-announcements/2026-09-22/federal-student-aid-posts-updated-reports-fsa-data-center
21. Student Loans Company. “Student Loans in England: Financial Year 2025-26.” Official statistics, GOV.UK, updated 2 July 2026. https://www.gov.uk/government/statistics/student-loans-in-england-2025-to-2026/student-loans-in-england-financial-year-2025-26
22. House of Commons Library. “Student loan statistics.” Research briefing SN01079, 2026. https://commonslibrary.parliament.uk/research-briefings/sn01079

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

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I have been waiting a bit to write my take on the election. I know a lot of people have already, and I wanted to let people make their views known while I refine mine. I am not going to make this a long post. But here is my take, with a little history so that you know where I am coming from.

I am currently, and have been for almost the last 20 years, a non-partisan registered voter. I started out when I registered as a Democrat when I first was able to vote at 18, because that was what my Grandmother was, and she was always influential in my life, especially with my love of history and politics in school (that was before computers 😊). The Democrat party then was like the Republican party before Trump, I would say. Then after Reagan, I said I identified with Republicans and switched parties. But after George W., I said, what is going on here? These parties are for themselves and not the voting public, not the ordinary citizen. That is when I changed to non-partisan.

I always like to research and listen to candidates and see how well they align with my visions and priorities. I don't care what party they are associated with, or no party.

That is my number one issue with both parties: they look out for and take care of the Party first. People's lives are not a football, soccer or any other kind of game. These are people's lives. Most people tune out politics (like my parents used to, but once retired I see people get more involved and “aware of politics”). I saw this coming, and the reason was prices more than anything. The second thing was the Iranian war, which contributed to the first, and tariffs, which again lead back to number 1. It is almost always the Economy. I have never seen prices for food, gas or anything else this high in 57 years of life, and definitely not since I started buying stuff on my own as an adult.

I also think the result of this election is a warning for both parties: in modern times people want to see results. I think they want to see results and are less concerned with our politicians worrying about social issues.

My frustration as a voter is to vote for the party in power if they aren't delivering. In my opinion the Republican party was not delivering on:

1. The Economy.
2. The rampant corruption.
3. Remembering that the Legislative branch makes the rules and the President is to execute them, not vice versa, and not the Executive branch running everything.
4. Everyone needs to follow the laws of the land, including immigration, and that includes those that enforce the immigration laws and rules.

Now that the Democrats have power, they need to fulfill the mandate, and this was a mandate, with priorities like this:

1. The Economy.
2. Do your job, don't allow the President, no matter what party they are from, to run everything, keep things equal, and keep number 1 going smoothly.

I think endless investigations will not be well received. I am not saying do nothing. I think the people working for Trump need to be held accountable for following the President and not the Constitution. The Constitution should always be the overriding factor, and if you are fired, you are fired; at least you can hold your head up. Trump is not ever going to be President again no matter what, so just ignore him. If Republicans have any chance, they need to tell Trump no and reach across the aisle more than they have, to help get the Economy and common sense back in vogue, because that is what it takes to override Trump's veto. The Founders set this up on purpose. They didn't think Party over Country, and they deliberately made things slow to evolve. While we do need refinements, I think overall our Constitution, on the majority of things, makes this Country run like no other powerhouse known. Yes, I do think there needs to be fine-tuning of the Amendments, and some new ones based on abuses by the Executive and Judicial branches and even the Legislative branch (I am looking at you for term limits for Federal offices).

These should be the priorities of the new Congress, and if the Democrats want to remain in power, they need to prove themselves. If not, in 2 years we could well see another wave swing things back to the other side. No-party voters like me are the deciding factor in elections now, not each party's extreme wings, but moderates and no-party voters. And no-party voters don't like what has been going on in either party, or at least this no-party voter doesn't.

#currentevents #opinion #politics

I've been using OBTF lately to keep track of my life, and this is a quick writeup of the things I've found.

First, I mostly like the format, but rather than just have one header per day, I've been adding one header per time I open the file and start writing. This is automated by a shell script which also syncs the file from a fossil, then commits the file after I'm done editing. See the script below (I'll pull this in as text at some point, but a screen-shot is fast right now, and you can OCR it if you need).

I'm also still using todo.sh, and have started poking at that so that when I finish a task, it will get archived, and also copied into the obtf.txt file, but that integration is a little tricky, as I'd like this to work from any of the machines I use on a regular basis. I'm also going to have to set up a fossil for my fork of todo.sh.

But the obtf.txt file is serving as a prod to get me to get all my various machines talking to my VPS so that there is a single source of TRVTH out there somewhere and I don't have to think about merging documents and such. So I've been writing scripts and such to do the things I mostly use the file for.

Specifically, here are the things I do with it:

• A daily journal. Most of the things I do that seem worth remembering get put in there.
• A place to stash ideas that I can search for later. I do this by putting IDEA somewhere in the line.
• A place to archive things I've completed from my todo list. (grep for DONE to find them).
• A place to leave random notes for myself.

Most of these are pretty simple, but as I'm using long lines in the file, I wanted to print things with a blank line between them. For example, to dump all the IDEAs out, I use the following ideas script:

#!/usr/bin/awk -f /IDEA/ {print $0, "\n"}

I also discovered that I've written over 400 entries in the OBTF file in 3½ weeks, so apparently it “works for me.” I don't go back to check things especially often, but just the act of writing them down has seemed to help my memory.

There's more coming, but mostly I'm working on getting scripts written to deploy fossils on each new machine I set up, and make them link back to the master fossil on my VPS.

In Summary: * Moving into the night meds and night prayers phase of my evening, I'm resolved to do things a bit differently tonight than for the last two nights. Rather than stay up as late (for me) as I can following basketball or football games, I'm going to make a determined effort to retire early and calmly. Tomorrow will find a Monday morning with its early chores that are never a part of the weekend mornings. So I'll want to have a good, restful sleep behind me to make the morning work better.

And I'm wishing a good, restful sleep for you all, too.

Prayers, etc.: * I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night.

Health Metrics: * bw= 220.90 lbs. * bp= 159/72 (62)

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, toe raises, wall push-ups, BP breathing exercises, pilates

Diet: * 06:15 – 1 banana, 4 little cookies * 08:20 – 1 ham & cheese sandwich * 12:00 – snacking on chocolate covered raisins * 13:45 – mashed potatoes & gravy, 4 hamburger rolls * 16:00 – 1 fresh apple

Activities, Chores, etc.: * 05:00 – wake * 06:00 – bank accounts activity monitored * 06:30 – read, write, pray, follow news reports from various sources, surf the socials, take daily meds, unpack, organize, and nap * 12:00 – watching FOXNFL broadcast of the Colts / Cowboys game – and the Cowboys win this one, 27 to 23 * 16:30 – listening to relaxing music * 17:00 – follow news reports from various sources

Chess: * 10:50 – moved in all pending CC games

I love writing, I think I’m ok at it, and I do it a lot. One area where I consistently seem to fail at writing is finding the words for sympathy cards. I love handwritten notes and often save them, but writing them myself is extra difficult. I often sit at my desk, with a pen hovering above a blank card and completely freeze. As deeply as I think about loss and ponder how people live their lives after loss, I fall embarrassingly short when trying to express my support after someone else’s loss. Truthfully, it almost brings up a feeling of shame because I feel I should have more skill and ease in this area.

Suffice it to say though, “I’m sorry for your loss” is hot garbage.

When I told people my dad was sick, I frequently got the response of “I’m so sorry!” These people meant well, of course, and this phrase is considered the socially acceptable thing to say. The challenge for me in these interactions was my response. I often became so uncomfortable, completely unsure of any response at all. I would freeze and give an awkward smile. Thanks, I guess? My mom started responding with, “Yeah, I’m sorry too.” And weren’t we all, facing the impending loss? Still, I have wished for more a more graceful way to answer.

This awkwardness of mine extends to writing sympathy cards. I don’t want to simply say, “Sorry for your loss” because there seems to be an ocean of feelings I’d like to express. “Omg, that sucks” only works for certain recipients (although it works quite well, when appropriate). How does one express the depth of feeling, and in a way that is actually helpful?

For some reason, my smallish team at work has experienced a surprising number of losses of family members this summer. Some of them have been old and sick, like my dad. Some just sick, from chronic illness. And some neither old nor sick, making the level of shock a noteworthy factor at play. For example, one of my coworkers recently joined what I tastelessly refer to as The Dead Siblings Club. She lost her sibling in a tragic and mostly unexpected way which had remarkable and awful parallels to the loss of my little brother. I’ve been a member of this club for 16 years already, and still, thinking of the early weeks and months after that loss, they were some of the most painful experiences I’ve ever had and probably ever will. And I somehow wanted to convey to my coworker that while I don’t precisely know how she feels, I have been walking a similar path for quite a long time.

Saying to this coworker, “I’m so sorry for your loss” felt hollow and cheap. I wanted to convey so much more to her, about how I know that the feeling of anguish seems like it will never leave, but eventually things do start to look different. Eventually you can sort of learn to breathe again. I have no magic advice for this. It took years for me to be able to talk about my brother without dissolving into sobs or becoming even a bit teary. Immediately after he died, I spent about two weeks straight lying on the sofa in my parents’ den, mostly staring at the ceiling. A lot of people reached out to me at the time, and of course I appreciated their love and support, but I had no words and no energy to respond. And no matter how amazing their written support, whether cards or emails, nothing seemed to penetrate the thick fog of grief that I wading through at the time.

I often avoid asking people who recently went through a loss, “How are you?” Because honestly, what kind of question is that? I’ve always hated answering that question in this context, and so I try to skip asking it. In the case of my coworker, I did ask her how she’s been doing since her loss, but I prefaced it with the disclaimer that the question was stupid and essentially meaningless. Fortunately, she laughed. It led to a conversation about how she has really been doing, given the chaos of her past few weeks.

Is there ever a truly correct answer to show support after someone else’s loss? Obviously it very much depends on who one is talking to, what their loss was, and one’s own relationship with that person to begin with. I strive for the non-generic. Probably I miss the mark more often than I’d care to. I’d like to include some helpful phrases here for others to use in these situations, but honestly, I’m not sure I have any. I think what I have found most helpful to read is an acknowledgment of how major of a change is in my own life. Nobody can do anything about that, but it feels helpful to have someone notice that this loss turns the world upside down.

And I think that’s the most important take away here: send the card. Say something, even if it is “Sorry for your loss.” Walking around carrying grief can feel like stepping onto an alien planet, and it’s nice to be noticed in this situation, rather than trying to blend in like nothing at all has happened. The best thing to say to someone who’s grieving? I see you.

From thousands of emails to inbox zero

I filed away all my emails of the past 10 years in a single evening while listening to a podcast with one ear. And I deleted a ton of them.

I find it easier to work in a tidy environment. Take my desk: you won't find much on it but some stationery, pens and minimal tech, like my keyboard. In my inbox, chaos reigned. Once the backlog of emails crossed a certain threshold, cleaning it all up became a monumental task for me.

Over the years I have tried my share of clients (web mail, Apple Mail, Outlook (on Mac!), Thunderbird and some more exotic choices). Without success.

Now I have given aerc another try. A second chance. And I have found a setup that helped me reach inbox zero and stay there.

Aerc is an open source terminal email client that uses familiar vim-style key bindings for navigation (Neovim, my editor of choice, where I am writing this post). It comes with the responsiveness of the command line and a minimal user interface.

This time I use aerc with mbsync, a tool that syncs my entire mailbox (or parts of it) to my disk. Avoiding slow calls to my mail server has made all the difference. Now working in aerc feels fast.

In short, I fetch all email and store it locally in a mail directory. I use aerc to “do email”. That means filing, sorting, deleting, answering email. All the good stuff. Mbsync then pushes the results back to my mailbox.

Speed wasn't my only problem. I've been putting off sorting through years of emails. The prospect of infinite-scrolling through thousands of messages, determining for each what to do with it, always had to make way for more appealing tasks. Almost anything else.

With aerc the job is manageable: Imagine I want to find all my insurance receipts from last month (like one does). I know my insurance mails always use some “my-insurance.com” subdomain. And the subject always says “something something receipt”.

:filter -f my-insurance.com -H "Subject: receipt" -d last_month

I get results instantly. Even when filtering through thousands of emails. I can then move them to folders easily. I select everything with :mark -a and move it to a folder with :mv 'Folders/Insurance Receipts'. I started out with a handful of folders and added more as I needed them. They are nothing more than IMAP directories that hold emails of a certain category.

These simple tools have been all I needed. With bulk filing and deleting, a podcast on D&D and a little bit of patience, I got there. At the time of writing my inbox has been zero for a good month.

If you feel inspired, go try aerc.

A very short movie (4mn) produced by Blender Studio.

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In a dystopian world where energy is scarce, a destitute man attempts to break into a battery factory. He soon finds himself cornered by a threat: a security droid…

https://youtu.be/UXqq0ZvbOnk?is=ORjTJkqQwUWZLm77

“Charge” © Blender Foundation / Blender Studio, dir. Hjalti Hjálmarsson — CC BY 4.0 https://studio.blender.org/projects/charge/pages/credits

#shortmovies

I’m journaling this mostly to try to just partially get it out of my system, but also to I guess digest my own emotions and understand a little bit more why I am feeling the way I am. Yesterday an and I spent almost the whole day, baking stuff, and I had started to get a crush on her again. We had also had a talking phase for a while when we first met, but the timing wasn’t right and so we did not end up dating, even though she was interested in me. But I wanted to kind of rekindle the situation because we were both kind of dating and I thought I saw a side of her that made me feel like she might be a really good match with me. But I also feel like it’s a little bit unfair for me to pass the judgment and so definitively say that that side of her that I saw was not genuine because I think it is heavily tainted by this frustration from my perceived rejection. She talked about how she dreamed of this guy that she had talked to before her last relationship and asked him out, and later she also talked about how she would think about what her future partner potentially was doing right now, and I guess I could’ve taken that as an invitation to say something like oh maybe baking for some joke about that because we were doing it together, but I think by then I pretty strongly had the gut reaction that she is not interested in me. And so I no longer really feel like I have a crush on her. And I find myself both pointing out reasons why I don’t necessarily want to be in a relationship with her, like certain icks, but at the same time, I also recognize that part of that for sure has to be me perceiving rejection, and then wanting to put the other person down in my mind as a defense mechanism the same way I think everyone does. And that’s why I’m not really trying to give too much weight to these thoughts before I have a chance to talk it out with friends or my therapist and also let it settle a little bit. But I do find that I kind of had a hit to my self-esteem in a way. And it’s this thought that I am kind of everything she wants, and also likely way more than that. I apologize for the arrogance, but I kind of want to butter myself up a bit here to protect my self-esteem. I think I am incredibly successful, I am incredibly smart, funny, attractive, I think kind and progressive in a lot of ways that she doesn’t even necessarily want, which is one of the incompatibilities, but for a lack of a better word, I guess I kind of feel like even as a provider I find it hard to think of someone else realistically being able to offer the same things that I currently do while also being kind, developed, mature, I like the other things that I take pride in myself. And I guess it’s this feeling of if I am all of these amazing things why does she not ask me on the date or something like that rather than another person. And so it feels like that must mean that in the direct comparison or competitive sense, I am less desirable. And I understand that there is so much more nuance to that and I am not being compared in any of that sense, but I think that’s kind of what leads to this gut reaction from me. And I have a feeling it would probably be smartest if I do this, so explicitly stating why that might not be true, first of all, there’s always a thing about you can be the sweetest peach on the tree, and someone just might not like peaches. But also there are our incompatibilities that also might indicate that she is looking for something different than me, and also potentially it is just one of those things where someone wants attention from people which I can also kind of understand. And there’s also the whole thing about us being friends for a while and so that makes it difficult to understand when the boundary of platonic is being pushed. And also potentially she just doesn’t want to cause drama within mutual friends or stuff like that. These are all just a couple of the reasons why she did not ask me on a date.

I think I also find myself having this feeling of betrayal or loyalty, being broken, in the same way that I originally felt when she seemed to be flirting with R, and it made me feel like we did not have something special, and that she is actively searching for this kind of connection with other people at the same time. And I feel like this is just an indicator in my mind for if we do get into a relationship, if I will be kind of constantly doubting the thing about loyalty or her interactions with other people. And I recognize that this makes me upset at her, even though we are not even dating at all. And I think that this is a bit of an extreme reaction for me because as I said, we are not dating or even going on any dates at all. I think this is just one of the cases where I potentially just have to have that self-respect of understanding that I am a catch, and I do not need to lose sleep or feel desperate towards someone who doesn’t want to pursue me either.

5 October 2026

Spending lots of time alone in Yenah's grandmother's house. Getting up early, morning coffee, and sitting down to work each day at the kitchen table. As the sun rises, the tall white satin curtain spanning the length of the living room window starts to glow; one half of the curtain is reinforced by another pink one, so the diffused light that floods into the living room is half pink and half white. It bounces off of the red-orange wood floor, which creates a warm, saturated, matte-finish environment in which highlights and edges are dulled. Magpies like to visit in the morning, and a handful of times I've seen them jockey for position on a persimmon tree through the window. They're pretty aggressive, hip-checking each other off branches. Only two small horizontally-sliding screened windows in the house open, and tree branches sprouting vibrant green cross in front of the view out of both, so the feeling is one of life in abundance outside. Plants grow well on the windowsills too.

My days here have been spent mostly in silence, but it's a busy silence. Just down the street is an elementary school, and I hear the rhythmic phases of its days—pale yellow buses snorting to a stop to deliver sleepy children in the morning, high-pitched screams as lunch hour arrives mid-day, and the frenzy of happy squeals and teachers repeatedly saying goodbye (“안녕히 가세요”) as school is let out for the day in the later afternoon. Some intermittent bells and layered chimes of groups of children singing throughout the day as well. On days where I do laundry, the laundry machine sounds like alternating white noise waterfalls and MRI-machine-like hollow knocks. Mosquitos are frequent visitors at this time of year, so a few times a day I'll also hear their sharp whines buzz by my ear (I've killed about thirty of them in the last month). The water here is so, so soft, especially compared to London, and the sinks (one in the bathroom and one in the kitchen) rush when turned on with a dutiful urgency that sounds like a mother shushing a baby. Similar to the Segokcheon Stream down the road from the house that runs all the way to the Han River.

https://youtube.com/watch?v=m3yqgRyHkSU&is=Kpu6uje8TmEht4kt

https://youtube.com/watch?v=tjpgJjdk52c&is=ogPZFUCOsNAwpNMp

https://youtube.com/watch?v=mV76WmC5I4s&is=ACA6jF19jFy2Gv6f

https://youtube.com/watch?v=vON8PIbz90E&is=CXSe1HvyKnaDjDa1

https://youtube.com/watch?v=JZLjTu3N2Uw&is=vxCqNh75by9RuBCH

Yesterday's Checkmate Win.

I won this correspondence chess club tournament game yesterday with a Queen, Bishop, Bishop Checkmate on my 32nd move. We started the game on 05 October and played with a comfortable 2 days allowed per move time control. My Queen to g5 delivered the checkmate to the Black King. She is protected from capture by her c1 Bishop, and her c2 Bishop covers the King's only possible flight square. The position of pieces at game's end is shown above, and the game's full move record follows: 1. d4 d5 2. h3 Bf5 3. Nc3 Nc6 4. Nf3 Nb4 5. e3 Bxc2 6. Qd2 Qd6 7. Bb5+ c6 8. Ba4 Be4 9. Nxe4 dxe4 10. Ne5 f6 11. Nc4 Qd5 12. O-O Qg5 13. Qxb4 h5 14. Nd2 Qd5 15. Qxb7 Qd8 16. Qxc6+ Kf7 17. Bb3+ e6 18. Qb7+ Ne7 19. Nxe4 a5 20. a4 Rc8 21. Rd1 f5 22. Ng5+ Kf6 23. Nxe6 g5 24. Nxd8 Rxd8 25. Qb6+ Nc6 26. Qxc6+ Bd6 27. e4 fxe4 28. Qxe4 Bh2+ 29. Kxh2 h4 30. Qe5+ Kg6 31. Bc2+ Kh6 32. Qxg5#

And the adventure continues.

In the space of a fortnight Europe got hacked freezers in hundreds of supermarkets, thirty-odd hoax bomb threats on airliners, and a British government telling families to keep three days of food and water at home. It all looked like one story. I spent days trying to work out whether it is – and the answer is: partly, and not in the way it looks.

In Sjöbo, in southern Sweden, on the morning of 2 November the staff of the local ICA Kvantum open the shop and find the frozen food thawed. No door forced, no alarm tripped, no power cut. Somebody, somewhere in the world, in the middle of the night, told the freezers to go to 50 degrees, and the freezers obeyed. The manager writes it on Facebook with the resignation of a man who has just thrown away a stockroom: we've been hacked, they set the temperature to 50.

In the same hours, in Brussels, Stephan Moelans, managing director of Sabcobel, the company that runs the refrigeration for Delhaize supermarkets, is waking up his technicians. At one in the morning. He sends them out across Belgium and Luxembourg to do something that in 2026 sounds almost medieval: physically unplug the fridges from the network, shop by shop, before the rest of the stock melts. As he told the Belga news agency afterwards:

We began mobilizing technicians at 1 a.m. to get the situation under control

Three days later an Aer Lingus Airbus from Dublin to Rome lands at a French military base at Évreux, under fighter escort, while bomb disposal teams search it. They find nothing. On the same day some twenty other flights across Europe receive the same threat, and meanwhile the British tabloids are explaining to their readers which fourteen items to buy in order to survive an emergency nobody has declared.

Within a week you get the feeling of being inside a dystopian novel that somebody is writing too fast. I spent days collecting the pieces. This article is an attempt to put them in a row, separating what we know from what we think we understand. Because the two, as we'll see, don't coincide.

---

The week

Let's rewind the tape. In mid-October, in France, the fridges of a few hundred supermarkets (between 250 and 350 stores according to the technical reconstructions, up to 700 according to others, across the Intermarché, Coopérative U, Carrefour Market and Leclerc chains) are driven overnight up to 50 degrees. Stock to throw away, and in a few shops the beginnings of a fire, because a fridge that heats is an appliance doing something it was never designed to do. The attack gets told as a French story, but the analysis by Sekoia picked up by Reuters finds units hit in Spain, Portugal, Poland, Germany and Belgium too: the continent was already in it, nobody had counted it yet.

On the night between 2 and 3 November it happens again, this time on a continental scale: at least nine countries. Ireland, Belgium, Luxembourg, Sweden, the Netherlands, Finland, Estonia. Among the brands hit, Ikea, Delhaize, Carrefour, SuperValu (thirteen shops in Ireland). In Estonia the technicians step in within minutes and contain the damage; in Sweden ICA talks of “a limited number” of stores, which is the formula you use when you'd rather not say the number. In Athens a butcher tells the TV that his display fridge was set to 150 degrees, and that it took the technician two hours to get it back under control. And it isn't only frozen food: the same night Coolworld is attacked, the refrigeration supplier of the Établissement français du sang, the French blood transfusion service. Blood bags are not something anyone resells on the black market.

Then the emails. On Monday 2 November Hungary scrambles a Gripen to escort a Wizz Air flight from Luton to Budapest, threatened while already airborne. By Tuesday 3 the threats are already around thirty, twenty-seven according to the AP, plus a cruise ship; a Warsaw airport closes for a few hours. On Thursday 5 at least twenty-six are reported across Europe, on flights departing from sixteen countries. On Friday 6 another seventeen by noon, nine in Prague alone. Hungary scrambles its Gripens three times within an hour to escort a Brussels-Sofia and two flights out of Prague bound for Cyprus and Romania. In Dublin the headquarters of RTÉ, the Irish public broadcaster, is evacuated, and two other broadcasters receive threats the same day. Not a single device is found. Anywhere.

And finally London. On 22 October the Cabinet Office launches “Be Ready”, a three-year campaign asking families to keep enough at home for three days of self-sufficiency: water, food, a torch, a wind-up radio, cash, copies of documents. The same day the Defence Secretary, Wes Streeting, backs it with a line about “increasingly sophisticated cyber attacks”, and the next day the Prime Minister, Andy Burnham, defends it in person at a wildfire summit (and tells the Guardian about his own stash: beans, soup and Twiglets). From 27 October the papers start turning the same page of the government website over and over: the Independent headlines on the “attacks”, the Express on the “14 items to stockpile”, one news site on the “4 foods to have at home” (declared source: a Reddit thread...), another on the “13 things” to buy. Barclays publishes a survey: one Briton in four is stockpiling.

Four facts in fifteen days. Three of them are true. One is half true. And the question worth asking is whether they have anything to do with one another.

---

The radiator

To understand what happened in the supermarkets you need to know something supermarkets would rather not tell you: the fridge in a modern shop doesn't have a thermostat, it has a computer. It's called a controller, and in this case it's almost always a Danfoss of the AK-SM 800A series, a Danish box whose job is to let the maintenance technician check the temperatures of fifty shops from his sofa instead of driving round in a van. Convenient, and sensible too: if a display cabinet fails at three in the morning, somebody sees it straight away.

The problem is that this computer has a web page, and that web page, in hundreds of shops, was reachable by anyone on the internet. It's as if the thermostat in your house had a door onto the landing, with the key left in the lock. And as if the key were also printed in the instruction manual: many of the logins used factory passwords, the ones written in the manual you download from the manufacturer's website. After the French attack, researchers put fake controllers online to see who came knocking, and whoever came knocking tried exactly those passwords.

There was no stroke of genius. The main flaw, catalogued as CVE-2025-41450, lets you skip the controller's login screen. It was found by researchers at a security firm, Claroty, along with two others. Danfoss disclosed them in March 2025, published the fix in August 2025, and the American CISA issued an advisory the same year; Claroty's detailed technical report came out in August 2026, complete with a count of the controllers reachable from the internet: thousands. It wasn't even the first time: back in 2023 Dutch researchers had found three vulnerabilities in the same family of devices. Danfoss itself admitted that most of the systems hit were old products no longer receiving updates, and another manufacturer, Copeland, found a flaw in its own end-of-life controllers. A researcher interviewed by the Associated Press put it better than I could:

Nobody broke into these refrigeration systems with a zero-day

And the NCSC, the British cybersecurity agency, in its statement to the AP:

The cyberattack on French supermarkets was a result of exploitation of known vulnerabilities

Translated for those who don't do this for a living: the door had been open for a year and a half, everyone who needed to know knew, and in the end somebody walked in. Surprising, isn't it?

Once inside, the attacker didn't even have to write a malicious program. They pressed “defrost”, the de-icing function every industrial fridge has as standard, and held it down all night. A security expert interviewed by Gizmodo, Lamplmair, put it like this:

A freezer should never accept an instruction to heat to 50°C

Who did it, nobody knows. Two pro-Russian groups, NoName057(16) and Z-Pentest Alliance, claimed it on Telegram, posting what they say are 2,500 lines of data stolen from Danfoss, and then deleted the posts. It's worth what it's worth: NoName habitually claims anything that happens in Europe, and no security agency has confirmed. What the agencies have confirmed is that this isn't a bored teenager: researchers at Lupovis saw days of reconnaissance before the night of 2 November, with login attempts coming from “bulletproof” hosting, the kind that doesn't answer police requests. Somebody did their homework, and chose targets that don't earn a penny. The Pentagon, meanwhile, is still investigating the freezers of more than half a dozen American military commissaries that went haywire in late August, and is coordinating with the French. The FBI and four other federal agencies have published an advisory to cold-chain operators. And the head of British cybersecurity confirmed that in the UK too there has been “a small number” of incidents of the same kind.

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The emails

The mechanism behind the threats against aircraft, as far as the police have said, is disarmingly banal: anonymous emails, sent in bulk to several airports with the list of “mined” flights. The Czech police said the email that reached Prague was addressed to the airport and that similar emails had reached other European hubs. The Danish police, on Friday, in a statement picked up by Reuters:

We are once again at Copenhagen Airport today in connection with threats directed at air traffic

And the office of the French Prime Minister:

An investigation is underway to determine the source of these alerts

In Spain the Guardia Civil received three in twenty minutes, on Air Europa departures from Madrid and Iberia arrivals from Rome and Milan. In Rome, on the other hand, one threat came by telephone to the control tower at Fiumicino. The protocol, at that point, leaves no room: the aircraft lands where it can, fighters escort it if needed, bomb disposal searches it, passengers wait on the apron. It costs tens of thousands of euros per flight and it's done anyway, because the alternative isn't on the table. In the Aer Lingus case, by the way, things went less smoothly than the press told it: according to Prime Minister Lecornu's office the fighters were sent after the pilot had failed to cooperate as expected, and pilot and co-pilot were questioned by the Évreux prosecutor before being allowed to leave. Aer Lingus says they acted impeccably. That too is part of the cost.

The number that puts things back in proportion came from Eurocontrol, the European air traffic body: the 14 flights affected on Thursday were 0.05% of the 26,300 flights on the European network that day. “Minimal” disruption, says Eurocontrol. The “flights in chaos” of the headlines never existed: the thousands of delays circulating in the same days were the normal delays of Heathrow, Charles de Gaulle and Schiphol, which produce them by the hundred every day with or without threats. The real effect of the emails isn't on air traffic. It's on people's heads, and on the coffers of the states.

Who did it, here too, nobody knows. The British government called them “malicious hoax threats”. The European transport commissioner said it's “too early” to say who is behind them, and even whether the episodes are linked to one another. Moscow denied, and there is no evidence of Russian or Iranian involvement, or of groups tied to them. There is actually one jarring note, reported by a single source and which I couldn't verify elsewhere: the threats against flights bound for Rome supposedly came from a group calling itself anti-feminist, which would suggest either several different hands jumping on the bandwagon, or a signature planted there to mislead. A private security analyst, Borie, told the AP that the European focus “could have a Russian angle”, adding straight away:

Iranian hybrid warfare is just as active in certain pockets of Europe

Experts from the various countries will meet in Brussels next week. Allow me to be sceptical: either the data exists, and then it should be made public, or it doesn't, and then there are only suspicions. And filling the headlines with a Russian threat on the basis of suspicions, I don't know whether that's more irresponsible or more reckless.

That said, the precedent everyone has in mind, without saying it too loudly, is 2024: waves of bomb threats against schools and courts in Czechia and Slovakia, about which the head of the Czech intelligence service Michal Koudelka spoke publicly like this:

There is clearly a visible Russian trace

And before that the incendiary parcels in DHL depots in Germany, Poland and the UK, where the European investigation identified 22 suspects recruited in Russia, the Baltics and Ukraine, often people in financial trouble paid for an odd job. That is evidence. This, for now, is an analogy. The difference between the two is the only thing that matters, and it's worth holding on to.

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The leaflet

And then there is the United Kingdom, where for two weeks you get the impression that the government is talking to its citizens non-stop. It isn't. The “Be Ready” campaign wasn't born this week. It had been planned at the start of the year by the Starmer government, announced in September, and was published on 22 October. And it's the British version of something the Nordic countries have done for decades: Sweden sends every household a leaflet titled “If crisis or war comes”, and has done so since 1943. A report by former Finnish president Sauli Niinistö to the European Commission, two years ago, recommended exactly those 72 hours of household self-sufficiency to all member states, and Brussels adopted it. The context is declared: last year's British national security strategy explicitly names Russian aggression, hostile cyber activity and sabotage. It's no secret, it's a public document.

On 23 October the Prime Minister defended the advice saying that “unexpected events” are becoming more common, and the Defence Secretary had his say. From there on, though, it's no longer the government talking. It's the press parroting (if only it were stochastic...) whatever sells copies. A site that checks these things, Prepared Britain, looked at the GOV.UK page on 3, 4, 5 and 6 November: no new guidance, no emergency instruction, no department telling anyone to prepare for a war. The “attacks” in the Independent's headline were a word lifted from the campaign's original text, which talks about bad weather, blackouts, water and phone outages. The Express's “14 items” were the list of 22 October. The “4 foods” came from Reddit. And in the middle of all this, the Met Office's ordinary weather bulletins ended up in the same notification stream, indistinguishable from the rest.

The only truly new thing on the British front is the speech by the head of the NCSC, the cybersecurity agency, who in the same week as the fridges talked about empty shelves and lights going out:

When food isn't on shelves, lights aren't on, businesses have gone under

He said that one day we might have to explain why we had seen the signs and not chosen well, and confirmed the British incidents tied to the controllers. That one is an explicit link between the fridges and the wind-up radio. Made by someone who has the data to make it.

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Three actors, but no director?

Having got this far, the temptation is strong, and I admit I was the first to feel it: all of this looks orchestrated. Fridges, planes, leaflets, all in the same fortnight, all pushing in the same direction: get used to it, get ready, something is about to happen that we know about and you don't. It's a legitimate hypothesis, and I put it on the table as such.

Let's call it hypothesis A: the alarms are manufactured, or inflated, to prepare the population for a crisis someone has already decided on or already sees coming. In its favour: the timing, the convergence of interests, the fact that Europe's military chiefs openly talk about a possible confrontation with Russia within a few years. The German chief of defence Carsten Breuer, in May:

Various indicators all point to one possible date of a Russian attack on NATO: 2029

and he adds “or even earlier”. His minister Boris Pistorius:

By 2029 or 2030, Putin could strengthen his army to the point where Russia would be capable of striking NATO

The French chief, Burkhard, says 2030. And the Czech general Karel Řehka:

Most of us, defense chiefs, share a similar view

Against it, though, weigh the fridges. There you have stock destroyed by the million, private companies losing real money, a supplier sending technicians out at one in the morning, blood bags at risk, American bases hit since August. It's a physical event, with real economic victims and a technical vector that anyone with a search engine for connected devices and the Danfoss manual can verify for themselves. No European government has any interest in burning its own supermarkets to educate public opinion, and it would be a strangely expensive and traceable way of doing it. The same goes for the emails: every diversion with Gripens in the air costs the state money and embarrassment, and the day one of those emails were traced back to a friendly service the political damage would be devastating. The cost-benefit ratio of “doing it to yourself” is terrible.

Then there's a number that weighs against the very premise of a “fortnight of stage direction”. Forescout counted more than twenty claimed attacks on refrigeration systems between January and October 2026, and the most active groups were precisely Z-Pentest and NoName057(16). This isn't a sudden escalation: it's the visible tail of a campaign that has been running for a year, and that only became news when it hit enough supermarkets on the same night. The feeling of orchestration comes from the media's attention threshold, not from the real density of events.

Hypothesis B: an adversary, or more than one, does real things that cost next to nothing. One email to twenty airports costs zero and moves the fighters of three countries. One manual password on a 2015 controller empties a hundred supermarkets in a night. Governments, which have long expected this phase and have written it into their documents, use the incidents to push a preparedness they already had on the agenda. It's called communicative opportunism, and it needs no director. And the media, which live on repetition, multiply the same web page into ten headlines. Three different trades, three different interests, nobody coordinating with anybody. It looks orchestrated because the interests converge, not because somebody aligned them.

And there's a third box the two-way scheme doesn't allow for. Call it hypothesis A': there is a single director, but it's the adversary. Fridges and emails are one package of low-cost hybrid warfare, calibrated to produce in democracies exactly the effect “the government is preparing us for something”. In that case the timing would be deliberate, and hypothesis B would be true for the governments and false for the attackers. It's cheaper than hypothesis A, because it doesn't require anyone to burn their own supermarkets, and more unsettling than hypothesis B, because the target isn't the stock but the trust.

The problem with hypothesis A is that it can't be refuted: any alarm confirms it, and the absence of alarms doesn't weaken it. That old genius Popper would say that a hypothesis which cannot be refuted is not a scientific hypothesis; I'd say, more simply, that it's a feeling. To keep it alive honestly you have to turn it into predictions that can fail.

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What to watch carefully, from here to six months out

If hypothesis A is true, we should see: threats that are never attributed to anyone, or attributed vaguely and without names; claims like NoName's taken at face value without verification; preparedness campaigns that accelerate regardless of whether the incidents continue or stop. Careful, though: the first two would happen even if B were true and the investigations were simply slow or classified. The only prediction that truly tells A from B is the third: if the incidents fall off and Be Ready accelerates anyway, changes tone or finds new emergencies to cite, column A fills up for real. If hypothesis B is true, we should see: arrests with first and last names, like the 22 of the incendiary parcels; a public technical report on the controllers, with the addresses and infrastructure of whoever got in; and a drop in the British alarms once the media window closes and the GOV.UK page goes back to being a GOV.UK page.

Keep count. I will too, and if in six months the column that has filled up is the wrong one, I'll try to write it here.

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References and further reading

The fridges

• Gizmodo, supermarket freezers across Europe hit with another cyberattack – the second wave, 2-3 November, with the Lamplmair quote.
• CNBC, supermarket fridges hack and Axios, Europe supermarket fridges attacks – overview of the countries and chains hit.
• PBS NewsHour, what to know about another cyberattack on European supermarket fridges – the AP piece with the NCSC statement and the “no zero-day” quote.
• The Hacker News, attackers heat French supermarket fridges – the October French attack, first technical account.
• SentinelOne Labs, Defrost and Disrupt – assessment of the refrigeration attacks, the Forescout count and the claiming groups.
• Aviatrix threat research, Danfoss controllers and Archyde, attackers target Danfoss controllers – the AK-SM 800A, CVE-2025-41450 and the default passwords.
• IndexBox, hackers targeted Europe's internet-connected fridges before the coordinated attacks and Tildee, cyberattacks target refrigeration systems – the Lupovis reconnaissance and the blood bank supplier.
• Newsweek, FBI issues warning as hackers target grocery store refrigerators and Latin Times, cyberattack on refrigeration systems – the FBI advisory and the US military commissaries.

The hoax threats

• CNN live, bomb threats on flights across Europe and Al Jazeera, hoax or bomb threats: what we know – day-by-day count of the threats.
• NPR, Europe flights hoaxes and ABC News, bomb threats targeting flights and media outlets continue – the AP reporting with the Eurocontrol figure and the Borie quote.
• NBC News, Dublin-Rome flight diverted, Euronews, Airbus from Dublin to Rome diverted to France and Irish Times, Aer Lingus pilots questioned – the Évreux diversion and what followed.

Be Ready

• Prepared Britain, government preparedness campaign and Prepared Britain, UK government stockpile food and water – the daily checks on the GOV.UK page.
• ADS Advance, UK national resilience campaign and The National, UK government advises stockpiling water and food – the launch of 22 October.
• Nation.Cymru, Burnham defends stockpiling advice and LBC, Burnham on flooding and stockpiling – the “unexpected events” line and the beans.
• NationalWorld, UK cyber attack warning and emergency kit – an example of how the page was re-headlined.
• Met Office, UK warnings – the ordinary bulletins that ended up in the same stream.
• Swedish government, the new edition of “If crisis or war comes” and MSB press release on the leaflet (in Swedish).
• EU Law Live, civil and military preparedness after the Niinistö report and European Parliament briefing on preparedness – the 72-hour recommendation.

The precedents and the generals

• Euronews, Slovakia detains two over alleged hybrid attacks – the 2024 bomb threats in Czechia and Slovakia.
• Yahoo News, Russia behind parcel fires in UK – the DHL incendiary parcels and the 22 suspects.
• European Pravda, Breuer on 2029, NV, Czech general warns Russia could attack NATO by 2029 and United24, French military chief warns Russia could strike NATO by 2030 – the defence chiefs' statements.

#Europe #Cybersecurity #HybridWarfare #BeReady #Danfoss #Infrastructure #Media #Journalism #Writing

La vie solitaire de É. Sambòko prend la suite des #Didascalies de Fenêtre sur ville. Un personnage est apparu, qui déplace la perspective de la ville et de son écriteur. Sambòko veut dire “chaussure” mais aussi “énigme” si l’on oriente autrement l’accent. Où va É. Sambòko ? L’on ne sait.

La vie solitaire de É. Sambòko – 5.1

Parfois rien n’advient du vide, celui de soi ou du dehors, qui est le même. Une forme de l’attente se glisse dans le corps d’Éros. L’œil se tient seul à la fenêtre, au bord du trou de la ville où débaroulent les choses. Et demeure à regarder le quoi, cette matière du monde, la multiple surface de ce quoi, aussi profonde que l’insensé d’un rêve. Durant des jours ou des semaines d’une éternité désœuvrée sous la pesanteur de l’air.

Courte liste d’oiseaux que dévorent les nuages, l’aréquier planté là dans une cour odorée par les eaux de vaisselle, les mousses d’un savon contre les vers de peau, le champ tendu des tôles entre manguiers : image devant Éros, que détrempent les pluies, racornit le soleil. Image dans la tête, trou de la ville ou puits des orpailleurs tombés sous le ciel blanc, on y traque le fil, la veine, on s’y ensevelit à déganguer les mots, en ne tirant souvent que terre et d’anciens os de captifs ou de chiens.

#LaviesolitairedeÉSambòko