Philosopher, University of Sussex. Tweets in personal capacity. Interested in: Philosophy, Psychology, Society. Writes at: https://teapawt.net/t.co/MniDhzFVe4
Brighton England
Joined November 2010
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One of the most interesting things I've read recently. Recommend 👇
Dan Williams retweeted
There's a leftist/academic thing to constantly emphasize both the moral brutality of capitalist growth in the US and the surprising growth under brutal communism in China.
I think it's good to see the full picture of reality, but the emphasis is …. notable. Leftists/academics are never tweeting about how “did you know America’s economic growth was surprisingly robust when child labor was legal?”
Under “dictator” Mao, life expectancy in China increased by 30 years, literacy rates went from 20% to 70%, steel output grew from 1 million to 23 million tons, 47 million hectares of land was taken from landlords and given to peasants, and China was unified under a strong central state and got nuclear weapons.
Despite his failures, it does not take a rocket scientist to understand why Mao is revered in China.
Readers added context they thought people might want to know
Mao's Great Leap Forward and related policies caused an estimated 30-45 million famine deaths in 1959-1961 alone, with total excess deaths under his rule often estimated at 40 million or higher.
en.wikipedia.org/wiki/Great_Chi…
pmc.ncbi.nlm.nih.gov/articles/PMC43…
chinafile.com/library/nyrb-c…
Highlighting the distorting influence of negativity bias in media and public opinion isn’t to say that there is nothing in the world to worry about. It is to say that one thing we should be very worried about is an information environment so warped by alarmism and neuroticism that we fail to form an accurate model of the actual problems, risks, and opportunities we confront.
Dan Williams retweeted
AI could push back against public irrationality like conspiracy theories, fake news, & medical quackery. Whereas social media optimize for sheer engagement (clicks, likes, & reposts), AI is sold as a useful product that aids decision-making in the real world. For all the problems of LLMs, they're less likely to send users down a conspiratorial rabbit hole. This may restore the influence of epistemically responsible expertise. So argues the philosopher Dan Williams @danwilliamsphil open.substack.com/pub/persua…
The epistemic consequences of AI at all levels of society - from the impacts on scientists to ordinary voters - are hugely important and under-researched.
Dan Williams retweeted
✨"When we consider the large-scale impact of this technology on public opinion, its most consequential feature is simple: it greatly improves people’s access to accurate, evidence-based information." persuasion.community/p/ai-ca…
Dan Williams retweeted
Interesting result - "Analysts went with the agent's lean 86% of the time" - compare with literature on social learning where people usually do *not* follow others advice.
Dan Williams retweeted
@danwilliamsphil argues that far from supercharging disinformation, large language models are acting as an "anti-social media"—restoring public trust by quietly nudging discourse back toward nuanced, expert-aligned reality.
open.substack.com/pub/persua…
Dan Williams retweeted
New Anthropic research: How AI agents shape experts' judgment calls
When experts delegate work to an agent, do they still make the key decisions? We tested this in a randomized trial with 50 professional data analysts.
Dan Williams retweeted
Most work on AI and morality asks how AI should treat us, or how we should treat AI. But what about how AIs treat each other? Caspar Kaiser and I will present a research agenda on inter-AI morality on Nov 12. Join us online!
How do AI systems perceive and treat each other? In our next webinar, @LuciusCaviola and Caspar Kaiser will present an empirical research agenda for the emerging field of inter-AI morality.
Please join us!
nyu.zoom.us/webinar/register…
Dan Williams retweeted
Understanding how AI systems perceive and treat each other could be extremely important for both AI safety and AI welfare. Very excited to be hosting this webinar with @LuciusCaviola and Caspar Kaiser on how to study inter-AI morality empirically. Please join us!
How do AI systems perceive and treat each other? In our next webinar, @LuciusCaviola and Caspar Kaiser will present an empirical research agenda for the emerging field of inter-AI morality.
Please join us!
nyu.zoom.us/webinar/register…
Dan Williams retweeted
Progress in AI is set to reshape our understanding of human psychology.
As we learn to design intelligence, our own intelligence is bound to appear less special, and the challenges faced by evolution in designing us will become more intuitive.
optimallyirrational.com/p/wh…
Dan Williams retweeted
About 60% of experts believe that in social media "falsehoods spread faster than truth", a widely repeated over-generalisation of a single, carefully scoped result.
journals.sagepub.com/doi/10.…
It's psychologically difficult - for me, at least - to really internalise what this progress means and to think about what the trend implies for the future of intellectual work.
We are announcing three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.
openai.com/index/building-sc…
Dan Williams retweeted
Announcing the Call for Papers for Oxford Studies in Philosophy of AI and Computing!
Rapid AI progress is raising *so many* philosophical questions; but philosophers aren't as involved in the conversation as they should be, for many different reasons.
One is that, aside from some work in logic and philosophy of mind, philosophy of AI and computing has often sat on the margins of the discipline. One reason for *that* is that so many philosophers working on AI have had to do so basically on their own, figuring things out for themselves as they go along, without a real community around them.
OSPAIC is going to help fix this! We're going to have an annual conference and volume. The conference (in DC! where much of the future of AI will be decided) is especially important as we think about the nature of intellectual life in a world where AI systems can one-shot a superficially-plausible philosophy paper. OSPAIC sees philosophical progress as being about more than just the accumulation of true claims. The conference is a big part of our vision for how we contribute to philosophical progress.
And our aim is also to help philosophers be part of the broader public conversation! To that end we're also going to be launching, soon, a subcode on arXiv for philosophical foundations of AI (cs.pfai), and encouraging everyone who submits to OSPAIC to also upload their draft to arXiv (at present, use keyword PFAI).
We're also partnering with @cosmos_inst, who will be sponsoring an annual prize for the best paper on philosophy and AI, as well as helping fund the first round of the conference and Open Access publication for the volume. And with Cosmos we'll be highlighting some of the most interesting submissions to cs.pfai as they come in.
I'm the executive editor; Jeff Howard (UCL) and Rachael Sterken (University of Hong Kong) are associate editors; Ned Howells-Whitaker (JHU and Pittsburgh) is the assistant editor. We're grateful for the support of a wonderful advisory editorial board, including brilliant philosophers and computer scientists from academia, industry, and civil society.
The deadline for submissions is 11.59pm Feb 14, 2027, anywhere on earth. All details are at ospaic.org.
Dan Williams retweeted
I really enjoyed speaking at TAIS on meaningful US-China AI safety cooperation in May. Great event, and a fantastic attendee group - we talked long into the night. Talk is online below!
Is AI safety dialogue between the US and China possible — and what would it actually take?
At TAIS 2026, Seán Ó hÉigeartaigh @S_OhEigeartaigh (CFI, University of Cambridge) drew on a decade of work building China-West AI safety dialogue to lay out what genuine cooperation would require: channels of dialogue, shared topics of concern (like non-state misuse and loss of control), mechanisms for building trust through verification and monitoring, and a shared understanding of what AGI and superintelligence actually mean.
Watch the full panel on our YouTube channel: youtube.com/watch?v=y3veS3Kv…
Good article 👇 The psychological and social drivers involve what I call 'propagandistic cognition' and the marketplace of rationalisations in my work - eg conspicuouscognition.com/p/t…
My latest, brilliant illustration by Ben Hickey:
as.ft.com/r/50fc9dcd-6a07-47… (gift link!)
The world has incredible detail, friction, and complexity. People good at understanding machine learning and predicting benchmark performance of AI models don't necessarily have a good understanding of these factors and instead often couple impressive forecasts of AI capabilities with low-resolution folk models of society.
The result is many silly forecasts of AI's allegedly explosive societal impacts when it comes to economics, the information environment, etc, among AI experts and insiders. Good thread 👇
