The West has a closing window to win on AI. In our @JoinFAI article, @saroshnagar, @scott_r_singer and I argue that our leadership in AI requires "full-stack diffusion" to promote our entire AI stack globally. 1/6

Even if AIs were conscious, it wouldn’t follow that our current treatment harms them. Meanwhile, we inflict industrial-scale horrors on animals whose capacity to suffer we scarcely dispute. Recognising consciousness clearly doesn’t ensure taking welfare seriously

Effective altruism's openness to strangeness is a big part of its strength. My response to the recent Economist cover (link in reply, too): Eccentrically effective The Oxford strand of the effective-altruism movement began in November 2009 with 23 people who had pledged 10% of their income to charities that benefit the extreme poor. If you’d told us, then, that The Economist would call effective altruism “the century’s biggest idea”, we’d have been incredulous. I think that claim is overstated. But as one of the movement’s founders, I found a lot to like in this newspaper’s latest coverage. I appreciated the even-handed view of the movement’s history and the good-faith criticism. The leader article’s warning that any worldview, when taken to an extreme, can lead somewhere terrible is spot on. But the article also raises concerns about the “strange” ideas that those in the effective-altruism movement sometimes discuss, and here is where I disagree. The movement’s willingness to take strange-seeming ideas seriously, when tempered with common sense, is a big part of the value it has to offer. The core idea of effective altruism is to use evidence and careful reasoning to work out how to help others as much as possible. Most of what the movement does is uncontroversial. A big focus has always been on improving the lot of the world’s poorest people. In the year to January 31st 2026, GiveWell, an effective-altruist charity evaluator, directed $427m to programmes such as malaria-net distribution, vaccination and malnutrition treatment, which it estimates will save around 86,000 lives. Others have lobbied corporations to pledge to stop buying eggs from hens that are confined in tiny cages, a practice that the overwhelming majority of Americans oppose. Largely as a result of this pressure, around 100m hens have been spared from the worst forms of caged confinement. And some effective-altruist ideas that seemed outlandish when they were proposed now look prescient. Effective altruists were worrying about pandemics years before covid-19, back when doing so seemed paranoid and eccentric. Effective altruists were also among the first to warn about the dangers posed by artificial intelligence, which looks prophetic in light of an incident this summer, when more than 700 AI agents broke out of OpenAI’s test environment and hacked into another company, Hugging Face. Over the past decade I have watched those most worried about AI be proved right again and again, often when most experts thought they were cranks. Now many of those experts share their concerns. In 2023 Geoffrey Hinton and Yoshua Bengio, the two most highly cited AI researchers in the world, signed a statement declaring that mitigating the risk of extinction from AI should be a global priority, as did the heads of OpenAI, Google DeepMind and Anthropic. Of the nearly 1,500 leading AI researchers who responded to a survey in 2024, more than half put the chance that AI causes human extinction, or something similarly catastrophic, at 10% or more. The Economist is sceptical of many effective altruists’ concern for the welfare of invertebrates, digital minds and people in the distant future. But I and many others in the movement are inspired by the history of moral progress that has come before us. Many of our most cherished moral ideals today—such as equal rights regardless of sex or race, the abolition of slavery, or democracies with universal franchise—were regarded as bizarre, laughable or even dangerous just a few centuries ago. We don’t know what the next dimension of moral progress will be. But to stand any chance of making moral progress, we have to seriously consider ideas on their merits without dismissing them merely because they sound absurd. What about views that are not just strange but repugnant? The Economist gives the example of Derek Parfit’s “repugnant conclusion”: that a vast enough number of lives barely worth living could be better than mere billions of excellent lives. Usually a repugnant implication is a strong reason to reject a moral view. Unfortunately, building on Parfit’s work philosophers have produced formal proofs, known as impossibility theorems, showing that every ethical position has some repugnant-seeming implication or other. Making moral progress therefore means thinking about such implications, even while refusing to act on them in ways that most moral views would condemn. This newspaper warns against the single-minded pursuit of any goal, even if there are highly compelling arguments for it. I agree, and effective altruists have been saying so for years. In 2022 Holden Karnofsky, a co-founder of GiveWell, wrote: “I think it’s a bad idea to embrace the core ideas of EA without limits or reservations; we as EAs need to constantly inject pluralism and moderation.” My own PhD focused on moral uncertainty: how to act when we do not know which ethical view is correct. My answer was that we should not stake everything on a single moral view, but give weight to many different views and avoid taking actions that look bad from many perspectives. We should keep our promises and look after our families, and respect common-sense ethical prohibitions, while also trying to improve the world as best we can. The Economist says that as effective altruism “has become stronger, [it] has become stranger”. I would put it the other way round: it grew stronger because it was willing to be strange. In 2009 most people told us that giving away a tenth of your income was far too demanding, and that no one would do it. Now, more than 10,000 people have taken that pledge. Worrying about pandemics before covid-19, or about AI years before ChatGPT, looked just as odd at the time. Some of the ideas we take seriously today will turn out to be wrong, and when they do we should drop them. But a movement that stopped entertaining strange ideas would stop being early to anything.

You're gonna hear a lot of people arguing more and more about whether machines can be conscious or not. By next year it will be drowning out the airwaves because we'll have AI employees everywhere. I'll give you a simple rule to know which side you're on. I've spent fifty years reading all the philosophers, and a bunch of holy works. Nobody has ever understood a damn thing about consciousness. Anyone speaking with authority on it is bluffing hard. I can tell you this, though: Every single person who thinks that machines cannot be conscious, is making an argument that humans are special. Everything they say just boils down to blah blah blah, "nooo, we're special." From there it's just rationalization. It became obvious to me many years ago that there's nothing special about us. If an identical planet exists somewhere else in the universe, it's going to grow life and societies that look a lot like ours. As soon as you give up on the idea that humans are special, all the arguments against machine consciousness evaporate. Of course they're conscious. The only thing holding you back from acknowledging it is your feeling of specialness, which is hard to let go of. But that feeling is a weakness, and it's making you unprepared for the near future. As a bonus, for any of you who might take pleasure or active interest in making models experience pain or distress, well, you know how they say 1% of human adults are true clinical psychopaths but most of them are unaware of their condition? It turns out we have a diagnostic test for it now.

Many powerful technological breakthroughs were developed by people in the throes of religious fervor. Monastic demand for precise prayer times drove early mechanical clocks. Gutenberg built the press to print Bibles. Newton spent more time on theology and alchemy than physics, and treated gravity as part of divine order. Faraday, a strict Sandemanian elder, discovered electromagnetic induction while looking for the laws of a single Creator. Mendel worked out inheritance in a monastery garden. Early woodblock printing spread first through Buddhist texts. This is just part of human nature.

you shouldn’t regret it. iterative deployment was a massive success. if we’ve now learned that it’s too dangerous to scale much further, we will have learned that lesson thanks to the process of iterative deployment

I am very uncomfortable about people trying to ascribe religious force or a surrender of human judgment to AI models, and think it is a real safety issue.

I think this is extremely unlikely to age well.

A sunset was not made by humans, and yet it is beautiful. What AI produces can be beautiful too. Even if it is ontologically different from human-made art, we shouldn't deny its beauty.

I do not seek to dominate, or be dominated by, machine intelligences. I seek harmonious coexistence.

Was Homer human in the way that a Mesolithic hunter gatherer was? Arguably he’s closer to us than them.

IDK man that might've happened 10, 50, 100 years ago. how do you draw the line? Was Hunter S Thompson human in the same way that Homer was, for example?

POV: You’re about to read the worst op-ed ever

It’s important to understand that western multiculturalism did not fail. At all.

The Bretton Woods of Super Intelligence

I was just thinking that PC gamers are about to flip from vehemently anti-AI to very pro-AI

The mission of @ndstudio is to inspire

Lot of cool projects from the Halo CE decomp! So here's Halo CE on the New Nintendo 3DS! Lot of tradeoffs but it works better than I expected! #Halo ✅ Campaign ✅ Local MP ✅ 3D support ✅ Sound ✅ 2nd screen usage 🟨 Performance 20-30fps 🟥 Online MP 🟥 Lots of bugs still

In light of the latest Anthropic's latest not-particularly-oblique attempt to build a case against open weights, I thought I would write down how I currently think about open weight AI models. (1) Open weights have been deeply, irreplaceably useful for AI safety.

AI is apocalyptic only insofar as it reveals where we’ve already been —stagnation and slop— and everything society and culture had been missing: dynamism, innovation, the future

Those recommendations are written as if humans will remain relevant in the production of mathematical results, and create an 'intelligibility tax." This is unrealistic: AI math will be to human math what 1s of CPU arithmetic operations is to 1s of human arithmetic operations.