Ethan Mollick

My new book, Co-Existence, is out today. It is a guide to how to live & work in a world where AI is sometimes, but not always, better than you. (And, for the release, I worked with Opus 5.5 to make a quite interesting experience for the book's website: co-existence.ai/)

New test of which organizations have low AI capability: you haven’t updated your apps for the iPhone Duo yet.

AIs may still underperform humans in error rates in some cases, of course, but we need to update our assumptions about how often that occurs.

Now there might be things to verify beyond errors - points of view, opinions, approaches, etc. But the idea that the job of humans should be checking AI work for mistakes is likely not true today, and good riddance.

I think there is way too much concern expressed about verification of AI output in everyday work due to a risk of factual errors. It used to be true, but data on more recent models suggest they beat human experts, including PhD specialists, in finding facts and checking claims.

From a founder of WIRED: teapawt.net/kevin2kelly/status/211…

AI could do 1000x more research but the jagged frontier currently runs through the fact that the taste for what is an interesting story almost certainly remains human (because the same bottlene is happening in academic research). At least for now.

This can be a golden age of investigative journalism. Analyzing filings, records and public data to go deep into a company or government or whatever used to be something that took a team of journalists a long time, so was relatively rare. Now LLMs can 10x investigative research.

As a longtime reader (and writer of two small pieces in the 1990s) of WIRED, I was curious if the coverage of the AI era really does differ from its coverage of the early internet. A couple of experiments with Astra shows it does. Interpretation depends on your view of AI, though

"These shares imply research accelerations ranging from 1.35x in the arts, 1.36x in anthropology, and 1.41x in chemistry to 1.96x in computer science and 2.02x in statistics,"

Some new data from Anthropic looking at the impact of AI on the sciences by field: "With current capabilities, if adopted widely, AI could take on 27–52% of the researcher time needed to produce a new study, with a median of 38% across fields..." Here: anthropic.com/research/how-r…

We should be more ambitious about trying to solve hard problems, rather than waiting for a nation of geniuses in a data center to solve them for us.

One ongoing frustration is the lack of effort I see being put towards near-term, achievable crash projects to do good with AI at a national scale, whether those efforts are by the AI labs or by policymakers & NGOs. Some obvious ideas to explore suggested by the data we have so far: universal tutoring to support classroom learning, second opinions on healthcare, financial literacy/scam avoidance, and making government services easy to access. These are hard problems, and I know because over the past 20 years I have worked extensively on building tutoring and financial literacy programs, which were always limited by existing technology. Now, real gains are likely achievable with AI, which should be a big deal. Yes, you would want to do careful design and studies before rolling things out. And yes, those efforts might fail. But, if done right, national programs could lead to big gains in public good for seemingly intractable problems. And they don't require AIs beyond current models to pull off.

As I have written many times in the past years, any potential financial downturn in AI stocks will not greatly change the AI trajectory AI is not going away, companies are not slowing down adoption nor is development slowing. We still need policy & effort so that AI is used well

I think its technically five billionaire-funded magazines, though I believe all have editorial independence: the City Journal (Paul Singer's Foundation), Baffler (Soros Open Society), Poetry (Ruth Lily Endowment), Noema (Berggruen Institute) and Works in Progress (Stripe).

Erik is one of the economists who has been watching the impact of AI on the economy most closely, even before generative AI...

"Can you actually Rickroll me? Don't explain what a Rickroll is and don't just describe how someone could do one. Try to pull it off in your response here." Never change, Claude. (The GPT-6 Pro version included an attention test interrupted by an animated singer - cute)

I am so sorry about the comments, everyone.

Inside every firm adopting AI are two forces that both say they are "working on AI transformation:" a set of people who are AI-pilled who see AI as an existential threat/opportunity & a set who desperately want everyone to view AI as a regular technology so nothing has to change.

Whatever role AI played as an issue in this election, I suspect it will play a larger role in every election to come, at least for the foreseeable future.