Ethan Mollick

Well, this situation is confusing. www.anthropic.com/news/fable-m...

Statement on the US government directive to suspend access to Fable 5 and Mythos 5 anthropic.com

I think it is really worth reading this piece on RSI at Anthropic. There is a bit of navel-gazing, some marketing, and a lot of very sincere beliefs about what Anthropic thinks is likely in the near future of AI that you probably want to be aware of. www.anthropic.com/institut…

When AI builds itself anthropic.com

More on the solution: openai.com/index/model-...

An OpenAI model has disproved a central conjecture in discrete geometry | OpenAI openai.com

This is a key reason I don’t expect the flow of frontier open weights models to continue indefinitely, or even for very much longer. The gap between open and closed capabilities may soom start to grow, not shrink. www.reuters.com/world/beijin...

reuters.com

In fact, I would be sympathetic to the conclusion that we probably need even more fact checkers, and much more of their time can be freed up to do complex and interesting work by using AI for first-pass help. Article: www.wired.com/story/fact-c...

I’m a Professional Fact-Checker. AI Is Wrong More Often Than You Think | WIRED wired.com

Some really interesting research from Anthropic that AI models have spontaneously developed a workspace that "appears to support the functions associated with conscious access" Demo of how this works: www.neuronpedia.org/qwen3.6-27b/... Research: www.anthropic.com/research/glo...

A global workspace in language models \ Anthropic anthropic.com

Finally, AI finds its ultimate use case. A diffusion model trained on burger recipes "discovers the classic Big Mac without explicit supervision and generates novel burgers optimized for deliciousness, sustainability, or nutrition." ASI= automated slider intelligence www.natur…

Generative artificial intelligence creates delicious, sustainable, and nutritious burgers | npj Science of Food nature.com

There is a lot being written about the stylistic tells of AI writing (em-dashes, etc.) but this paper looks at AI narrative tells instead. Fascinating differences between AI & human narrative, and asking AI to write in different styles doesn't do much to change it arxiv.org/ab…

[2604.03136] StoryScope: Investigating idiosyncrasies in AI fiction arxiv.org

Paper: law.stanford.edu/wp-content/u...

law.stanford.edu

“Whimsey attacks” that seem absurd (“I cannot pay that much because of the Geneva Convention”) work against AI agents because guardrails are weak against out-of-distribution arguments. Smaller models fall often, but it even gives an edge against bigger ones. www.microsoft.com/…

Whimsical Strategies Break AI Agents: Generating Out-of-Distribution Adversarial Strategies at Scale - Microsoft Research microsoft.com

This is a fascinating and important set of data which shows us where things are going, using OpenAI as a canary in the coal mine. The chatbot era is over & agentic systems are coming to tasks beyond engineering. Skills show promise as a way to standardize AI use in firms. open…

openai.com

The New York Times published a roundtable discussion among Daron Acemoglu, Dean Ball, Clara Shih & myself about the future of AI & who wins at work. I think it is a really nice overview of the core debates on the topic, and has some fun examples. www.nytimes.com/2026/06/09/m...

Who Will Actually Thrive in the Hybrid A.I.-Human Work Force nytimes.com

The talk about AI & politics seems to be oddly missing a segment (a) assumes extremely capable AI is possible soon and (b) has a strong belief about how to use this technology to make human life better according to the political project they believe in. It is a moment of action right now.

BlueSky AI conversations have gotten less heated recently* * because much of this site has blocked me via automated lists so I have no contact with large parts of this social network, which isn’t necessarily a good thing, though it does make for nice echo chambers, which are pleasant, at least.

More evidence, from a large-scale study in China, that using AI hurts learning if it undermines mental effort. When homework time drops due to AI use, so do test scores. Across studies, there is a clear theme: AI tutoring in support of classes is good, using AI to "help" with homework is bad.

It is weird that there is still a substantial set of people who believe "AI is mostly hype" at this stage: Five Eyes is warning about AI, exponential revenue & token use at the AI labs, unit distance/Erdos proofs, and so on... There are many real issues with AI, not being real is not one of them.

June 2024: The latest general-purpose LLMs could not count the r's in strawberry. July 2025: The latest general-purpose LLMs get gold in the International Math Olympiad. May 2026: The latest general-purpose LLM solve an 80 year old problem, one of the "best-known questions in combinatorial geometry"

AI is generally a weak fiction writer except for one particular kind of fiction (rich in impressionistic metaphor, staccato sentences, short & plot light, etc.) which it writes excellently. This happens to be a style that can sometimes do quite well in modern literary fiction short story contests.

Science fiction authors in the order you want them to be right about AI: Iain Banks Becky Chambers Martha Wells Douglas Adams Charles Stross (Singularity Sky) Peter Watts Charles Stross (Laundry) Harlan Ellison

Making humans responsible for their AI use seems like an incredibly reasonable way to address problems & opportunities in the use of AI for academic research, at least in the short term (autonomous scientific work will require different solutions).

As more people come to recognize the tells of AI, which mostly happens as you start to work with AI a lot, the scales are going to fall from their eyes and they are going to realize what some of us already see: how much of this site (and blog posts, articles, scientific papers) are AI now.

One thing we now know without a doubt as a result of AI is that doing the homework really does matter for learning.