NEWS & UPDATES

Sean Leahy 11/4/26 Sean Leahy 11/4/26

Not the Audience: Reading Ethan Mollick's Co-Existence

Ethan Mollick's Co-Existence is a warm, candid guide to living with AI that is sometimes better than we are. A review of what it gets right, where it skims the surface, and what a book is for when AI may be its most attentive reader.

There is a particular kind of frustration that comes from reading a good book that wasn't written for you. Ethan Mollick's Co-Existence: The Next Phase of AI produced exactly that feeling, and it became the starting point for a review conversation with Andrew Maynard on Modem Futura.

The book picks up where Mollick's 2024 Co-Intelligence left off. That book framed AI as a collaborator, with humans at the center and chatbots as helpers. This one turns to coexistence with systems that are sometimes, but not always, better than we are. The chapters are short and the tone is warm and generous, and Mollick is candid about what confuses him, which makes the book a useful counterweight to the faux-certainty that saturates so much public talk about AI.

The case for a gentle book

Andrew's argument is that accessibility is the contribution. Most people meet AI through a chat window or a pop-up in a familiar app. They need a guide they trust more than a technical download, and a slim book that gets read does more good than a definitive one that doesn't.

The case for going deeper

My own reading kept snagging on ideas the book raises and then leaves behind. Mollick's advice to evaluate AI output is sound, but evaluation depends on expertise and judgment built through effort, which is precisely the friction AI tools are designed to remove. His four human advantages (deep knowledge, wide knowledge, taste, and agency) offer a helpful starting map, yet each opens onto long traditions of scholarship, from embodied cognition to aesthetics, that readers will need to find elsewhere. The book is at its best on work, where Mollick treats jobs as bundles of tasks rather than single units a machine can take. That lens clarifies a great deal, even if it can't settle what happens to people whose bundles are small, or who are caught in the years between old work disappearing and new work arriving.

What a book is for now

The most interesting question the book raised sits just outside its pages. Mollick's book website includes a version written for AI agents reading on behalf of humans. If AI becomes an author's most attentive reader and summaries replace reading for many people, the lasting value of a book like this may lie in the voice itself: the doubt, the self-questioning, the sense of walking alongside someone who is still figuring it out. That voice does not survive summarization well.

So read it, especially if the pace of AI has left you disoriented, and treat it as a set of starting points rather than a destination. Then pick an island and go deeper.

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Sean Leahy 4/28/26 Sean Leahy 4/28/26

The Jagged Frontier: Reading the 2026 Stanford AI Index

Every year, Stanford's Human-Centered AI Institute releases its AI Index — a careful, voluminous attempt to map where artificial intelligence actually stands. The 2026 edition, just released, runs over 400 pages. On the newest episode of Modem Futura, Sean Leahy and Andrew Maynard work their way through its top takeaways and sit with what the data is — and isn't — telling us.

The report opens on a striking juxtaposition. Today's frontier AI models can win gold medals at the International Mathematical Olympiad, yet still stumble on tasks as ordinary as reading an analog clock. Stanford's researchers call this the jagged frontier of AI — and it's more than a quirk. It's a reminder that these systems are not human intelligences being perfected. They are something structurally different, with capabilities and failure modes that don't map neatly onto ours. The interesting question isn't how close AI gets to human thinking. It's what becomes possible when we stop asking it to.

A second thread running through the 2026 Index is the lag in responsible AI. Safety benchmarks are falling behind capability. Incidents are rising. And, as Maynard points out in the episode, the conversation keeps collapsing “responsible” AI into “ethical” AI — two related but meaningfully different things. Ethics gives us the framing. Responsibility asks us to make real, pragmatic, often messy decisions about value, trade-offs, and whose futures we're building toward.

The education findings are equally hard to look away from. Over 80% of students are now using AI for school-related tasks, yet only half of middle and high schools have AI policies in place — and just 6% of teachers describe those policies as clear. Learning is happening. Institutional support is not yet meeting it.

Other findings threaded through the conversation: the closing US–China model performance gap, the fragile TSMC chokepoint at the center of global AI supply chains, and the fifty-point perception gap between AI experts and the public. Each opens a different kind of question about how this technology is being built, distributed, and absorbed.

None of these tensions resolve cleanly — and that's part of what makes the Index valuable. It gives us a shared map for a landscape that keeps shifting under our feet.

📘 Read the 2026 AI Index: https://hai.stanford.edu

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