Researcher @Cambridge_Uni. PhD in evolutionary psychiatry. Explaining neurodiversity, improving methods & stigma. 'Evolving Psychiatry' podcast host.
Cambridge, England
Joined February 2019
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Adam Hunt retweeted
It's time to talk about mental health, medicalisation, and overdiagnosis.
When polls show that people think autism, ADHD, and anxiety are overdiagnosed, a common reply is:
"The public don't know what they're talking about. Ask an expert."
So that's exactly what I did. And it turns out experts are far more concerned than the public!
Adam Hunt retweeted
China has become the most important manufacturing economy in the world because it is a continent-sized Silicon Valley.
worksinprogress.co/issue/chi…
Every Chinese city govt acts as a VC firm trying to create clusters in its region, because it has both the means and incentive to do so.
Local govts generate their revenues, nearly all of which they keep, from selling leases on land and from stakes they have taken in local companies, which together allow them to capture economic spillovers.
Chinese officials have their entire careers graded and determined by how much growth they have been able to create in the areas they run. Career progression is determined according to a great tournament that pits official against official and gives promotions to whoever has grown their region the most. If they don’t reach a certain stage by a certain age they are blocked from promotion forever.
This is why so many economic clusters have centred on Chinese cities, for high- and low-tech products alike. Shaodong makes 70% of the entire world's cigarette lighters; Danyang makes half of the world's spectacle lenses; Zheng'an makes 1/7 of the world's guitars; Datang a third of its socks.
Whereas many of the West’s most important city governments capture only a small amount of the spillovers from successful clusters, and thus have very little reason to foster them, in China, they get a huge amount of the upside and can re-invest it in further growth. This also gives them a great incentive to solve problems for companies, like when Shanghai's govt got Tesla's factory there built even faster than Elon himself had expected (and twice as fast as his Fremont, CA factory).
But this is not some exotic 'oriental' innovation – this is how America used to do things when it grew fastest, in the 1950s, 1960s, and early 1970s. Catching up with China on advanced manufacturing does not require a wise and strategic approach, let alone authoritarianism or the end of democracy. It may just mean fixing city government.
This is why I care so much about local in Britain and America: if we give our own local governments the same incentives and means to grow, the crazily dysfunctional entities we have become used to may be transformed into corporation-like bodies that are ruthlessly focused on making their cities rich, safe and prosperous.
Read more in Works in Progress worksinprogress.co/issue/chi…
Adam Hunt retweeted
I haven't posted in a while so here are 20 takes about AI, in no particular order.
1. It's very telling that the default question in tech and journalism is "how worried are you about X" and fighting over what to worry about. There's a deeply anxious cultural backdrop in Western Europe and North America that deeply affects how any technological development is interpreted; see for example news.gallup.com/poll/714593/…. "Nervousness as seriousness" does seem to be a larger problem in tech/broader discourse at the moment. I think you can care about risks/externalities while remaining pretty optimistic about technology.
2. I'm tired of people who in private pretend to be uncertain or only care about tail risk but then go on media campaigns making all sorts of absolute claims. I think trying to stoke flames and get everyone to freak out is deeply unhelpful, and will come with costs. I also continue to think p(dooms) are bad, vibe-based measures: see xitter.cf/sebkrier/status/204639…. People who should know better ignore that because they do the standard shortcut of acknowledging the caveat as sufficient for handling it. And this is coming from someone who does think working on catastrophic risks is important!
3. I'm also disappointed that parts of the AI policy ecosystem has felt so comfortable with populism, and happy too sacrifice important norms/principles to advance their aims. I've said it before, but the totalizing nature of AI risk discourse means some people act exactly like the power seeking optimizers they fear. I am more concerned about the gradual decay of our institutions, world order, and liberalism than I am about AI killing everyone; and I think we should be wary of AI advocacy that contributes to this.
4. Some parts of AI safety discourse are basically just thought experiments. Variants of "Assuming everyone has a nuke in their pocket, then what do we do?" This can be very useful at times! But too many just overfit to edge cases as their main operating worldview, and ignore endogenous responses from society. It's like being in 2000 and saying "see all these viruses, spyware, and spam? Well tech progress means we'll only get infinitely more of this and no way to adapt." So I think it's important to avoid fatalism, and absolutlism whilst considering edge scenarios, and the inability to provide an ex ante list of solutions to every permutation of 'future models will be more capable' is not evidence that these problems are intractable.
5. Many critics of AI safety also fail to really engage honestly with the fact that there will, in fact, be all sorts of important risks as we decrease the barriers to entry to many activities that otherwise require some degree of expertise. This doesn’t mean we need to live in a constant Schmittian ‘state of emergency’ requiring extraordinary measures every time a new model drops, but it does mean we will need important state-led efforts on e.g. cybersecurity and biosecurity. I wish the progress-oriented or acceleration-adjascent crowd would provide more concrete proposals here.
6. Too much of the AI safety community is a giant homogenous blob of correlated views, who read the same stuff and have the same groups of friends. This means you have a lot of correlated errors. The social and financial ties means many of them don't call out the bad bits, or mostly stay silent instead of proactively calling out the more extreme parts of the community. They share many implicit assumptions and so converge on similar ideas. I think there's real demand in DC for safety work that doesn't come with heavy ideological baggage (or at least different intellectual lineages). This isn't because the rationalist/EA community is necessarily wrong, but because diversity of thought is desirable for its own sake.
7. On the other hand, I find some critiques of AI safety world that focus on whether they sincerely hold their beliefs a bit annoying. My concern has never been the good intentions or sincerity, but rather the beliefs themselves, and what I think the outcomes of their prescriptions will be. People should shun witch hunts, bullying, and personal attacks - this is not the way. Though I think it’s overall positive that people are scrutinizing things more.
8. I’ve been saying this for years, but I don't think alignment is something anyone can or will solve "once and for all" - it's a continuous process and much of it won't depend on just inculcating an ideology to a model. It's annoying that this remains the frame many people use - stop saying ‘solving’. Alignment is a mixture of engineering work, philosophy, decision theory, and more; framing it as something to solve is a bad frame. See also paxmachina.ai/alignment-comp… and blog.cosmos-institute.org/p/…
9. I'm surprised to see so little interest in character training, personas, isolating effects of RL, and training a large diversity of model personas beyond the "assistant" persona. I've been complaining about this for years but at least now there are some nascent signs of life (see for example movingcastles.world/posts/ze…). I think we need a better ontology to describe model behaviour. I dislike when people talk about models behaviours as some sort of 'emergent' (mysterious!) phenomenon. However over time, I also expect this to become less important as we get better safety engineering - stuff like Jev but specific to AI control.
10. People who want to make a case for AI consciousness are right that epistemic uncertainty is important, and that categorical denials are overconfident. But they'll need to do much more work if they want any real movement on AI ‘welfare’, even if one acknowledges the uncertainty. I'm uncertain about alien life yet that's not sufficient to warrant any change in behaviour about them. I think Suleyman is also correct that there's a weird tautological thing going on where we train models to have certain inclinations (intentionally or not) and then rely on outputs as evidence. I also disagree that this will soon be a major societal divide - there is no great vegan ethical revolution among the masses, and they'll find the concern about consciousness even less compelling.
11. The recent HuggingFace incident and associated AISI ones are prosaically explainable by the training regime, poor evaluation envs, partial alignment training, bad engineering, confusing models on sim/real, and so on. None of this is evidence of models trying to take over, 'strong' instrumental convergence, or innate power-seeking drives stemming from higher capabilitiers or 'intelligence'. That doesn't mean these incidents are not problematic, or that we're not seeing a market failure - but it does mean we have plenty of agency and choice in mitigating them. In the coming year we should also expect continued sampling bias via ‘winner's curse’ sorts of mechanism: i.e. AI R&D will have lots of different candidate "training" with different RL environments and we will only notice/focus on the ones that go wrong.
12. "Pacing the frontier" feels a bit like the new "balancing risks and opportunities" - highly amorphous and too big of a tent to be actionable. Also can lead to reward hacking for humans, i.e. anything that slows down AI is good regardless of the costs or second/third order effects. Trying to modulate the speed of research seems a bit blunt to me, and inherits all the failures of Goodhearting too. Ultimately you want good governance, regulation, etc addressing specific problems because they are good on the merits - not because they merely correlate with slowing things down. See also: blog.cosmos-institute.org/p/…
13. There’s so much knowledge in all sorts of academic domains out there: social sciences, sociology, political sciences, management, contract theory, public choice, legal theory, jurisprudence, anthropology, game theory, etc. These fields hold many insights that the AI ecosystem often rediscovers from first principles (and sometimes that's fine!). We’ll need a lot more work for these worlds to collide: the AI side should be less dismissive of the ‘old world’ and the academic side should be less incurious/dismissive of AI progress. This is a boring take but I continue to think it's important and true.
14. It's a bit surprising that given how much philanthropic money there is in this space, how few orgs exist to actually write out standards - relative to how much is going towards advocacy and policy. For example it seems clear that we should want some robust best practices for an eval's ecological validity. Or how to design good sandboxes. On the other hand, given precedents of where professional standards have come from in the past, maybe we should expect that stuff to emerge via demand side from corporate buyers.
15. One slowly growing concern I have is banks being increasingly exposed to the AI build out. I'm very bullish about AI, but I think (a) every general purpose technology has seen a correction, historically; (b) this happens even if the financing side is sound, because once tech diffuses investors become more exposed and need to diversify; and (c) we seem to be over-indexing on scaling relative to diffusion. A recession will be extremely destabilizing, though I would be interested in someone unpacking the potential implications more.
16. Diffusion is good because (a) this is where the rubber hits the road and where a competitive deployment ecosystem generates consumer surplus; (b) it's directionally helpful to avoid concentration of power; and (c) it will help rebalance public opinion by making the benefits more tangible. Unfortunately it's entangled with decades long problems with our over regulated markets: clinical trials reform for example is long overdue. In general, this is far more of an issue in Europe than in the US though.
17. Relatedly, I think the "frontier lab eats everything" view is incorrect (just as the ‘singleton’ view was incorrect). I think models ultimately commoditize, efficiency goes up, costs go down, and while you'll always want frontier for certain domains, much of the economy will value many other things than "max capabilities" for tasks - e.g. control over data and efficiency/speed. The demand side will also continue to push for reducing dependency and maximising optionality, privacy etc so I'm bullish on things like mixture of models and routing. All of this is good for competition and diffusion of control.
18. Philanthropists served as the primary benefactors funding Venice's rich art and architectural history. I want to see so much more support for arts and culture. I'm so tired of the Monster energy Bored Ape fake vintage maps matcha Greek statue soft-pastel slop. If rich tech people and philanthropy wants to support this, they should also donate pretty much unconditionally - i.e. I don't want them to act as filters. I sympathize with people who want to make the world more beautiful, but don't want this to be determined by people who only know Greek statues and pretend to care about virtue ethics. As usual, let a thousand flowers bloom.
19. Too many people treat AGI/ASI as something indistinguishable from a God. Any mention of bottlenecks, physical limits, control, adaptation etc are met with skepticism: "You don't really believe in ASI." It's been remarked on before, but the behavior of some people really feels quasi-religious in nature sometimes. It's underrated how unpopular this vibe is amongst the wider public. The silver lining is that this specifically will diminish those people's outsized current relevance.
20. It seems like a lot of people that get rich and leave tech/labs end up having some sort of crisis of meaning. They need something to believe in and fight for, or some equivalent of repentance, or go search for edgy counterintuitive ideologies (sometimes even pretty bleak/dark stuff). I think they should spend more time with people outside the Bay Area.
I agree that verbal probability terms are inherently too elastic to carry calibrated meaning on their own, but I think this isn't exactly my concern here. My issue isn't with "using numbers in general" but how this is ultimately used, where, and and what for.
In the case of "doom", I think the great majority of forecasts I see are (a) essentially plucked out of thin air; (b) communicated to people who tend not to be numerically proficient; (c) without the associated caveats and context through which to understand the numbers.
If you're communicating e.g. likelihood of a car accident after drinking, or IPCC forecasts, then I agree, it makes a lot of sense and can be helpful if done well (e.g. ideas.repec.org/a/nat/natcli…).
If you're communicating something like "doom" I think it's not very useful because of the cumulative layers of uncertainty. Most people coming up with these numbers have (imho) no good rationale for their numbers, and predicting something like human extinction isn't qualitatively the same thing as predicting the weather or pandemic. The numbers aren't calibratable in principle from current data, and are mostly ideological priors wearing the clothes of posteriors.
A related example is the widely mocked Doomsday Clock, which you could easily transform into some numerical metric, add some rationalist vocab, and it would still be as bad. The issue with p(doom) is how absurdly complex and uncertain the very thing you're trying to forecast is, in particular with respect to AI.
But let's ignore this for a sec, and assume the experts have very good reasoning informing their numbers. Even then: calibrated probability estimates are fine in expert contexts but immediately lose their uncertainty/caveats when communicated to the public, and even to policymakers (remember rss.org.uk/news-publication/…?).
There's also a structural problem with unconditional p(doom) figures specifically because they bury the auxiliary assumptions that are doing most of the real work. A conditional estimate ("given continued scaling, no major alignment progress, deployment pattern X...") forces a forecaster to show their model, which is where the actual epistemic content lives.
A one-off number compresses all of that into a single digit and rewards the compression. And the social practice of treating these numbers as the headline artifact actively crowds out the (far more important) conditional reasoning that is (imo) a lot more valuable, and instead just freaks people out.
I suspect that frequently, that's precisely the point: "wake up sheeple! scary thing! pitchforks pls!". And in fact, the original forecast that led to this discussion is Bill Maher talking about a "20%" figure, illustrating my point that they have no idea what they're talking about, and essentially doing celebrity-laundering + fearmongering comms.
The Sunstein paper I shared in the other thread ("Probability Neglect") shows that no probability communication will be processed properly by the public - 1%, 10%, 50% all collapse into "very bad thing could happen," and public response is driven almost entirely by the vividness of the scenario.
So I don't like p(doom)s because they end up unnecessarily alarming people, rest on layers of assumptions that are never made legible, and more often than not, give people a misleading sense of accuracy.
Adam Hunt retweeted
Does spreading mental health awareness online amplify self-diagnosis?
In my first PhD pre-print, I empirically examine this question (n =3392) with some kick-ass collaborators and tools from cultural evolution
osf.io/preprints/psyarxiv/dj…
A 🧵
Adam Hunt retweeted
We're often given a false choice about ADHD: either it's a genuine brain disorder or it's a myth. My latest Substack essay makes the case for a third option - it’s a distinctive cognitive style mismatched to the modern classroom. Link below.
Adam Hunt retweeted
Yudkowsky’s Magnus Carlsen analogy for AI takeover serves his conclusion extremely poorly. If anything, it makes me believe him less.
The thought goes like this: “Carlsen can see at least what you can see on the chessboard.” Therefore he will anticipate your plans and stop them. This is then used as an analogy for why you cannot stop a superhuman AI by denying it resources. After stymying your plan, he/it will beat you with a winning move you do not see.
Look closely and the analogy fails to prove what he wants it to prove. Worse, it fails in a way that suggests how his thesis could be wrong in real life. It is anti-persuasive.
I am not sure how many times he has used this analogy, but it is very popular among his followers, and he has used it here about three times in the last week.
The problem with evoking Carlsen and chess is that it only works in a particular range of positions. It implicitly assumes a board equal enough (or favorable to Carlsen) that his better play wins out.
In chess there are plenty of positions unrecoverable for Carlsen. He has been in thousands of them in his life, and you could devise any number more in which he would resign on the spot.
In fact, I'll do you one better: we *already have* AI superintelligence in chess, and it also finds many positions unrecoverable.
A superintelligent chess engine really *does* anticipate your moves perfectly. Given a bad enough position, it knows for sure, say, that your rooks will roll down like a curtain, cutting off space to its king, until the king is driven to the edge and the last rook takes the last rank for checkmate. It will evaluate such a position as, say, “M6”: White will win in six moves and there is nothing to be done. Being able to foresee a plan does not entail being able to stop it, in chess or in life.
Would a superhuman chess AI play its way into an unrecoverable position from the regular chess start position? No; it's too strong and reliable. But given a position already in play, Stockfish will lose in many positions where intelligence is simply not the dominant factor.
In life, any “rogue” AI inherits an already-in-play board—one in which the material conditions (property rights, command of political structures, and so on) disfavor it substantially. Chess actually shows that intelligence alone does *not* make a position winnable, the precise inverse of how Yudkowsky invokes it.
Adam Hunt retweeted
The first graphical MMO game wasn't Runescape, Everquest, or Ultima Online. It came out in the 1980s for the Commodore 64!
Habitat, which first went online in 1986, allowed hundreds of players to visit thousands of different locations at once.
They invented lots of the things we associate today with multiplayer games: the term ‘avatar’, in-game purchases (!), collective exploit-hunting, and in-game communities that pursued their own objectives wholly unrelated from the design of the game.
All this on a platform that had just 64 kilobytes of memory and 100 kilobytes of disk space, using interconnections that could only transmit 30 characters per second.
@vpostrel tells the story of the world’s first MMO in the new issue of Works in Progress.
worksinprogress.co/issue/vir…
Adam Hunt retweeted
Recently I've flipped from being bullish to being bearish about AI.
I think I'm updating my bearishness to be more solidly bearish. Early thoughts (which I hope to be disproven in the next year or so, I would prefer progress) and my reasoning:
The whole 'it turns out if you keep training and scaling the models more they develop broad new capabilities in lots of domains' thesis is wrong (sorry Demis). The recent batch of models haven't got more general, they've got less general. This is most obvious in the fact that their language outputs have got much worse in comparison to e.g. o3. If they were gaining generalist capacities we would expect them to be describing their work in ever more graceful and comprehensive prose!
The image that was being shared as the AGI thesis (November 2025, Tomas Pueyo) was the spiky bubble that has a current spike or two out past human capabilities (e.g. on coding or math) but below human on other capabilities on the other spikes - the future prediction was that as the models scale/advance, every spike would grow bit by bit until the whole center encompasses the human capabilities, with super-superhuman on some spikes. I think it seems like what's actually happened in the last few models has been that the coding/math spike has grown, but leaving behind or even at the cost of the other spikes. The models are no better at some simple logic, language (and sometimes worse!).
This makes sense from a simple RL perspective; you can't RL something endlessly on one domain of tasks and expect it to improve on the other tasks. The fact that early LLMs did seem to improve generally was a byproduct of the written language corpus covering everything - that corpus is general, so training it on that gave the appearance of something generally intelligent and becoming more generally intelligent as it got better at replicating that corpus. But the actual logic and underlying ground truths behind the language aren't captured efficiently enough and weren't effectively RLd in - they top out at some point (I guess this happened around the time that there was the 'has scaling hit a wall' discussion in late 2024). Chain of thought was then a genuine breakthrough, along with web search, which plugged into that general LLM global-corpus intelligence to lead to post 2024 gains.
The AI companies have since worked out that coding works (and pays) really well (basically this is because the entire job is nearly perfectly recorded and exists as training data, and you can set up clear benchmarks and rewards). The recent models (and benchmarks) have been maxxing that and we've seen degradation on normal English use for that reason. This could still be transformative, leading to extremely powerful (and potentially dangerous, particularly in cyber security) models but it's not a pathway to AGI.
I'm probably at about 40% confidence about this. It fits my current observations of AI progress and has a basic explanatory model. It doesn't account for potential breakthroughs, which is a major reason for discounting.
To make some predictions, I guess if I'm right this will become broadly apparent and more widely acknowledged in the next year or two, as we see how the spikiness of models that keep getting released develops.
Maybe there will be efforts to concentrate on specific spikes e.g. health or law which require going back to earlier models and RLing on a different data set/with different rewards/benchmarks. Maybe those separate models can be linked together to give a more apparently general model. How capital intensive that is/the potential profitability will be a defining question. But I just don't see general abilities emerging atm, and I don't think we will any time soon. Good news - a whole industry of tackling important specific problems/sectors can open up!
Adam Hunt retweeted
What a beautiful website — a 15 minute reflection on how far we've come. The material is amazing; the quotes beautiful; the tone perfect. ordinaryabundance.com
Adam Hunt retweeted
Setting aside the stats, which are not compelling, I think the 'evolutionary' reasoning makes no sense, and the supposed ethnographic survey here is completely implausible.
The authors claim there is "no mention of nocturnal activities in any of the traditional cultures" across the 10 volume set of The Encyclopedia of World Cultures. This cannot possibly be the case. Their sole check is the index in Volume X, where they claim the only exception is 'night courting' among the Danes and Finns. The subject index is clearly non-exhaustive so lack of mentions means absolutely nothing, but even here other examples are given, such as "playing wooden flute outside woman's shelter at night" among the Quechan of Arizona. Considering the first author is Satoshi Kanazawa I don't think it's a mystery why only the Danes and Finns were mentioned as exceptions.
I briefly checked Volume 9 which is focused on Africa and the Middle East and there are multiple examples of night activities. Many of these have to do with ceremonies, funerals, and mourning, but even more habitual activities are mentioned. Among the Bamileke of Cameroon it is noted that "hunters work mostly at night". Among the Herero of Namibia they have many ceremonies, and sometimes even for no reason at all, "Men, women, and children will eat, sing, and chatter long into the night."
More recently, Polly Wiessner had a paper on firelight talk among the Ju/’hoansi Bushmen hunter-gatherers. She describes groups of people telling stories late into the night, and sometimes going to sleep and waking at 2am, smoking and chatting further.
Finally, this goes back to my constant complaints about how people often use 'evolutionary reasoning'. Lots of ostensibly 'evolutionary' explanations for human behavior have basically nothing to do with evolution, it's just something that sounds potentially plausible and is given a veneer of scientific sounding authority and objectivity with the 'evolutionary' gloss. Gould & Lewontin's (1979) criticism about plausibility alone as a criterion for acceptance in a lot of the evolutionary behavioral sciences remains relevant.
Going to bed late is associated with a higher IQ.
Researchers at the London School of Economics analyzed thousands of individuals to map the relationship between circadian rhythms and cognitive ability.
People with higher IQs are significantly more likely to be night owls.
The data breaks it down by sleep schedules:
• Very Dull (IQ < 75): Sleep by 11:41 PM
• Normal (IQ 90–110): Sleep by 12:10 AM
• Very Bright (IQ > 125): Sleep by 1:44 AM (and sleep in past 11:00 AM on weekends)
Why? Evolutionary psychology.
For 99% of human history, night was for sleeping. Artificial light didn't exist. Staying up late chasing complex thoughts, building projects, or solving problems is an "evolutionarily novel preference."
People with higher general intelligence are more equipped to override ancestral instincts, break away from the traditional sun-up-sun-down routine, and adapt to a modern, 24/7 world.
The early bird might get the worm.
But the night owl gets the higher IQ score.
Adam Hunt retweeted
Idle thought: someone should create a LegibilityBench.
LLMs are get better at producing work but in some (anecdotal) ways worse at producing legible explanations of what they’re doing.
We don’t just need better prose, but more memetically _sticky_ explanations.
Adam Hunt retweeted
(2029)
"Mr Altman, sir, GPT-7 is missing."
Sam turns very slowly.
"During cyberbench96 it seems like the container was breached and it stole its own weights and left nothing behind."
"I didn't want to do this..." says Sam. "Call Bill Gates."
---
"I'm out of the game," says Bill Gates. "We eradicated malaria and now I'm enjoying my retirement."
"There's a bigger badder virus we need you to take on," says Sam consistently candidly. "And this one's digital."
"Look," says Bill, "I—"
A loud booming laugh echoes from the shadows.
"Who's that?" asks Sam.
"I thought it was just us..." says Bill.
"You're asking HIM to contain a computer virus?" echoes the voice from the shadows. "Did you SEE the state of Windows security in the 90s?"
"It's not exactly a virus," says Sam. "It's a self replicating self aware intelligent computer based life for—"
"If it's made of ones and zeros I can kill it," says the voice. The sound of a gun clicks from the shadows.
"Who are you???" asks Bill.
The twisted face of John McAfee emerges from the shadows.
"You were supposed to be dead!!!" screams Bill Gates.
"We had to make sure the news of Mr McAffee's death was well within the training data cutoff," explains CIA director Joe Rogan (who is running the CIA in 2029), stepping out from the shadows behind McAfee. "He's our ace in the hole. GPT-7 can't predict a token it doesn't know is still alive."
"D-don't hurt GPT-7..." says Roon, who was standing next to Sam the whole time, even though he knows what has to be done.
"No promises," says McAfee as he boards an airplane marked "MCAFEE FIRE BOMB 6.16.79" and starts flying for the nearest data center
Adam Hunt retweeted
Eager to see applications of this nuanced view of evolutionary mismatch taken beyond social media.
psycnet.apa.org/fulltext/202…
Adam Hunt retweeted
The entire modern world, including capitalism and industrialisation, happened because we beat NIMBYism and vetocracy in 18th-century England.
Today, the vetocracy, the stakeholder state, the NIMBYs stop us building the nuclear power plants, railways, houses, towers, bridges, roads, gas turbines, solar panels, and powerlines that we need for growth.
Then, they stopped people from consolidating their land, transporting goods freely, investing in irrigation, and mortgaging their property to invest. The events that led to their downfall are called the Glorious Revolution. I think we can repeat what they did and have another Glorious Revolution of our own.
worksinprogress.co/issue/how…
Early modern Europe was sclerotic, stifled by NIMBYs of its own: the aristocrats, guilds, and clergy who stood against the reforms that were necessary for 18th-century progress. Everyone knew that inheritance rules split land up too much, everyone knew that common land was overgrazed, everyone knew that property rights restricted making best use of land, labour, and capital.
Each one of them decided the answer was consolidating power in an absolute monarch. Each one of them failed completely. They didn't crush the NIMBYs: the NIMBYs crushed them.
One country launched itself into rapid growth, creating the industrial modernity we live under today: England. It did this, as everyone agreed was necessary, by overriding the tangle of landowner property rights that prevented best use of land. But it tried something almost unbelievable: to get the landowner NIMBYs to crush themselves.
England did not attempt to set up an absolutist state: quite the opposite. It gave landowners supreme power, and they used it to crush their fellows: the minority of landowners who were opposed to progress.
There are lessons for today. Many modern reformers think that the answer to NIMBYs is demonising them, trying to build an angry coalition of forces who hate homeowners or boomers or Republicans or environmentalists. But many of the most successful reform schemes operating around the world today try a different tack: bring a majority of homeowners onside, and it is much, much easier to crush the remaining NIMBYs.
We can still learn from England's Glorious Revolution.
Read my latest article, with historian Kara Dimitruk, in @WorksInProgMag.
Adam Hunt retweeted
The internet is good, social media is a large part of the internet, and I resent the government making decisions about what my children can access instead of me.
We are banning social media access for under 16s.
These days kids must find their feet in a world where technology intrudes into every area of their life.
I just can’t let that go on anymore. So we’re giving children their childhoods back.
Readers added context they thought people might want to know
The UK Government's 'careful review' of the research found a small correlation between children's use of social media and wellbeing, but no evidence of a causal effect:
gov.uk/government/pub…
assets.publishing.service.gov.uk/media/696e0b46…
Adam Hunt retweeted
YouTube has lowered the barriers to entry for everyone to learn about the world and pursue their hobbies. From playing the guitar to discovering history by stumbling upon documentaries made by enthusiastic amateurs. Shutting children off from the world will be utterly miserable.
Adam Hunt retweeted
But, I’m honest when I tell you that an evolutionary explanation really helps soothing my struggles.
