Summer Reading for Futures Thinkers: Part Two of the Modem Futura List

What makes a book worth your summer? On the concluding half of our annual summer reading list, an answer kept surfacing: the best stories are the ones that don't end when you finish them — the ones that plant an idea you can't shake, and that keeps growing into something uniquely yours.

Part two of the list ranges well beyond the cyberpunk canon we explored in part one. Andrew Maynard opens with Terry Pratchett's Unseen Academicals, a satire of university life so accurate that anyone who has worked in academia will cringe in recognition — and one that connects, unexpectedly, to our recent conversation about enshittification: where does the true value proposition of our institutions actually live? His bonus pick, Pratchett's often-overlooked Bromeliad trilogy, is a reminder that the best children's books are age-agnostic.

Sean breaks the pattern entirely with Henri Cartier-Bresson's The Decisive Moment — the landmark photography collection, still available through the Fondation Henri Cartier-Bresson in Paris. It sparks a meditation on analog intentionality: how portable cameras created street photography, why a single frame can hold an entire technological era, and the idea that every photograph has two subjects — the one in the frame, and the one behind the camera.

Time travel threads through the middle of the list. Connie Willis's Blackout and All Clear are historical novels wearing the lightest science fiction overlay, following future academics who live through the London Blitz. And La Jetée, Chris Marker's 1962 short film told almost entirely in still photographs, proves that sixteen minutes and a compelling idea can seed decades of storytelling — you can trace its time-loop DNA through much of what we watch today.

The lighter fare earns its place too: Mick Herron's Slow Horses novels (arguably better than the acclaimed series they inspired), the full-cast Harry Potter audio dramatizations, and a return to Silo ahead of its new season. Two friends-and-family picks round things out: Riz Virk's The Simulation Hypothesis and AI and the Art of Being Human by Jeffrey Abbott and Andrew Maynard — a deliberately agnostic, tools-based guide to navigating AI with intentionality and care, whether you approach the technology with enthusiasm or deep unease.

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Summer Reading List 2026: The Books That Inspired Our Imagination (Part 1)

Reading Backwards to Understand the Future
There's a particular kind of book list that shows up every summer — the one that seems designed mostly to signal how serious and well-read its author is. This isn't that. In the first part of our annual Summer Reading List, the guiding instinct was the opposite: lasers, space ships, escapism, the kind of book you genuinely can't put down. What we discovered while recording is that the most escapist reads on the list turned out to be some of the most useful lenses on the present.

The cyberpunk classics anchored the conversation. Neal Stephenson's Snow Crash (1992) coined "metaverse" and imagined a digital overlay on the physical world years before anyone could plausibly build one. William Gibson's Neuromancer (1984) did the same for "cyberspace." Both have been mined relentlessly by the technology industry — and both, the hosts argue, are routinely stripped of their context. Snow Crash is a satire and a warning; it's frequently read as a roadmap. That gap, between fiction written as caution and fiction adopted as ambition, is one of the more revealing dynamics in how Silicon Valley tells its own story.

The deeper thread is about cognition. Snow Crash turns on a virus that crosses from the digital realm into the human mind. In an era of AI systems that engage directly with how we reason and feel, that premise reads less like science fiction and more like a description. Iain M. Banks extends the inquiry in Surface Detail, imagining civilizations that construct virtual heavens and hells so immersive that the line between real and simulated experience dissolves — and asking who, if anyone, has the right to govern what happens inside them. His The Player of Games offers a gentler entry point to the same Culture universe, and a sly meditation on whether a frictionless utopia is something humans actually want. We also dive into some of the amazing and seemingly timeless work of Douglas Adams, whose original Hitchhikers Guide to the Galaxy radio scripts Andrew counts among his prized possessions and whose wit, he insists, anticipated our anxieties about AI with personality long before the chatbots arrived.

The list closes on firmer ground with Cory Doctorow's Enshittification, a nonfiction account of how convenient, delightful platforms decay once users are locked in. It opened onto a question that runs through the whole episode: what do we actually own in a digital age? A printed book from 1980 still works, unconditionally. A digital one comes with terms that can change beneath you. And when the historical record itself becomes editable without a trace, reliability becomes something we can no longer take for granted.

None of these tensions get resolved here — they aren't meant to. The takeaway is quieter and more durable: stories written decades ago remain among our best instruments for thinking clearly about technologies their authors never lived to see. Part 2 continues the list next week.

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The Quiet Convergence: Reading the WEF's 2026 Emerging Technologies List

Every year, the World Economic Forum releases its Top 10 Emerging Technologies report — and every year it offers something more useful than a list of gadgets. It offers a read on where the genuine cutting edge is maturing: not the technologies dominating the news cycle, but the ones that have quietly reached the point where companies are investing, where the science has left the lab, where impact is becoming plausible.

This year's list is worth sitting with, and not only for the individual entries. Read together, the 2026 technologies tell a story about convergence.

An energy backbone. Three of the ten cluster around power: everything-to-grid systems that reimagine every building, vehicle, and device as an active participant in a distributed energy network; passive radiative cooling materials that release absorbed heat through a narrow band of infrared that escapes the atmosphere; and direct lithium extraction that addresses the supply bottleneck underneath nearly all modern electronics. None is flashy. All are foundational.

A biological turn. The middle of the list grows intimate. PFAS destruction tackles the "forever chemicals" we engineered to be indestructible — a vivid case study in how today's challenges are so often yesterday's innovations. Precision fermentation turns engineered microbes into microscopic factories for food, medicine, and materials. Exosome drug delivery and personalized mRNA cancer vaccines point toward medicine tailored to an individual genome — in some early trials, transforming survival odds for cancers long considered nearly untreatable.

A compute layer. Underneath runs the quiet infrastructure. Quantum simulation can model molecular interactions that classical computers find effectively impossible, opening once-"undruggable" diseases to discovery. AI world models aim to give machines an intuitive grasp of physical reality — learning through experience, the way a child learns gravity long before learning physics. And lattice-based cryptography hardens our data today against the quantum computers we expect tomorrow.

What makes the list compelling is how readily these pieces combine. Chain the biological and computational threads together and you approach something genuinely science-fictional: scan, model, fabricate, deliver. But convergence cuts both ways. Every capability here carries second- and third-order implications — questions of accountability when machines do the engineering, of unintended consequences when powerful tools meet messy human systems, of who shapes a world that artificial systems increasingly understand on their own terms.

Grab a copy of the full report directly from the World Economic Forum:

World Economic Forum Top 10 Emerging Technology of 2026

The honest takeaway isn't a prediction. It's an invitation to pay attention: to read the report, follow these technologies as they move, and ask not only what they make possible, but what kind of future they quietly assume.

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The AI Gold Rush Is Real. So Is the Backlash. What Sits Between Them Is Human.

A curious thing is happening at graduation ceremonies: students have begun booing speakers who mention AI. Meanwhile, builders are using the same technology to do things that seemed impossible three years ago. In Episode 88 of Modem Futura, hosts Sean Leahy and Andrew Maynard sit down with venture capitalist Jeff Abbott — founding partner at Blitzscaling Ventures, founder of the global AI Salon community, and Andrew's co-author on *AI and the Art of Being Human* — to explore the widening gap between those two experiences of artificial intelligence.

Abbott offers a rare insider's view of what he calls the new gold rush, and it's stranger than the headlines suggest. Technical moats have largely evaporated; everyone builds on the same foundation models, and those models change without warning. Software itself is becoming liquid — apps described in natural language, generated in seconds, used once, and discarded. A teleprompter for a single video shoot. A custom CRM coded in two weeks. The conversation traces what this means for the future of work, for startups, and for a generation being told AI will transform careers they haven't yet been able to start.

But the episode's most striking turn is inward. Abbott built an AI tool that performs much of his own job — analyzing startups, scoring them, generating reports instantly. What it lacks, he argues, is judgment: the lived experience and relational trust that make venture capital, and arguably every business, a human business. The data crunching is the tip of the iceberg; the weight beneath is intuition and relationship.

The trio also explores one-person unicorns and the "minimum viable human team," why the entrepreneurial mindset matters more than entrepreneurship itself, and a question Abbott poses to his academic hosts: what would an investment framework for human flourishing actually look like? True to form, the episode doesn't resolve that question — it opens it. Because if AI really can do more and more of what we thought defined our work, the things that remain — judgment, trust, knowing where you want to go — start to look less like soft skills and more like the whole point.

Listen to the full conversation wherever you get your podcasts, or watch on YouTube.

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When the Definition of Life Gets Blurry: Synthetic Cells and the Care They Demand

We tend to imagine that scientists know exactly what they're making. So it's oddly reassuring — and a little head spinning — to learn that one of the first challenges facing a National Academies committee on synthetic cells was simply agreeing on what a synthetic cell actually is.

That was the starting point for our conversation with Emma Frow, an associate professor at Arizona State University whose work sits at the intersection of bioengineering, science and technology studies, and the governance of emerging biotechnology. Emma served on the committee behind a recent consensus report on the responsible innovation of synthetic cells, and she described spending months wrestling with definitions before any other questions could even be asked.

A spectrum, not a thing

The reason is that "synthetic cell" isn't one technology, is because it is a spectrum of different variations and combinations. At one end is a simple membrane enclosing a handful of enzymes — something that may not be alive in any conventional sense, and that exists in a genuine regulatory gray zone between chemical and biological oversight. At the other end is the long-standing scientific ambition of building a living, replicating cell more or less from scratch. In between are the practical applications driving much of the field: programmable cells for drug delivery, biomanufacturing in bioreactors, and biological substitutes for agricultural chemicals.

Emma offered two clarifying questions that help locate any given creation on that spectrum: Does it contain genetic material? And can it replicate? Those answers shape everything about how seriously, and in what way, we ought to pay attention.

The mirror in the lab

The conversation's most striking turn concerned "mirror life" — organisms built from the reversed molecular handedness of all known biology. Every living thing we've found uses left-handed amino acids and right-handed DNA. A mirror organism would invert that. For years this was framed as a potential safety feature: something so alien it couldn't interact with existing life. But the scientific community has since questioned that assumption, and in late 2024 a group of leading researchers called for restraint, warning that a self-replicating mirror cell could pose risks we'd have no evolutionary defense against.

Care as an ongoing practice

What gives the episode its center of gravity isn't the specter of catastrophe. It's Emma's insistence that care isn't a box you check once. It's a posture you maintain throughout the work — and one the biotech community, by necessity, has cultivated more deliberately than some faster-moving fields. Biology resists the move-fast ethos. There is no perfect containment, and some experiments can't be undone.

The result is a conversation less about prediction than about practice: how thoughtful people decide what's worth building when the old categories no longer hold.

Read the full report here: Supporting Responsible Innovation of Synthetic Cells: Biosafety, Biosecurity, and Environmental Considerations
2026

What an AI Hallucination Tells Us About First Contact

There's a thought experiment that keeps surfacing in futures work, and it goes something like this: if a genuinely alien mind tried to communicate with us, would we recognize the signal, or would we just call it noise?

On the latest episode of Modem Futura, we play another round of Futures Improv — a format where an AI-generated scenario lands cold on the table and the two of us have to think our way through what it might mean. This time the scenarios kept pulling us back to one question: what counts as a mind, and what do we do with the ones we don't recognize?

The first scenario — a riff on Stanislaw Lem's Solaris — imagines first contact with a moon-sized organism that communicates only by generating vivid hallucinations inside our astronauts, drawn from their own repressed memories. It isn't hostile or friendly. It may not even know we exist as separate beings. The premise sounds outlandish until you notice that we already struggle to have a real conversation with an octopus.

The second scenario hands humanity a single question to ask a time traveler from the year 8,002,701, who carries one piece of verified information — humanity survived — and a sad expression. What do you ask, and what do you deliberately choose not to ask? It's a thought experiment about scarcity, priorities, and the difference between surviving and flourishing.

The third — the one that sticks with you — imagines a service that backs up your consciousness to the cloud every night while you sleep. Ten years in, the backups begin to diverge. They dream differently than you do. Who, then, has the right to your name, your relationships, your sense of self? And the question that arrives quietly behind it: how would you know you weren't the backup already?

None of these scenarios resolve, and that's the point. Futures Improv isn't about predicting which of these worlds will arrive. It's about practicing the kind of imaginative attention we'll need for the technologies that already are — embodied AI, longevity research, neural interfaces, the slow erosion of the line between physical and digital selves.

The conversations get weird. Occasionally they get genuinely strange. And sometimes, in the middle of joking about Elon Musk being reconstituted as a banana, we land on something serious about what it means to be human in an age that keeps redrawing the edges of mind.

🎧 Listen to the full episode wherever you get your podcasts, or watch on YouTube.

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🎧 Apple Podcast: https://apple.co/4vodLdY

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School's Out for Summer: What a Semester of Teaching with AI Actually Looked Like

The end of a university semester is always a moment for reflection, but this one felt different. After teaching three new compressed courses in seven weeks while integrating AI tools into nearly every phase of the process, my co-host Andrew Maynard and I used this episode of Modem Futura to take stock of what actually happened.

The conversation centers on a practice that quietly reshaped my teaching this semester: vibe coding. Not in the Silicon Valley sense of building apps for market — but in the deeply practical sense of an instructor recognizing a gap in student preparation and building an interactive resource in 20 minutes flat. Self-contained (and shareable) HTML files that functioned like polished apps. Jeopardy-style review games for graduate students. World-building card games for in-class collaboration. All created through natural language conversations with AI, all deployed within hours of the idea forming.

But this episode quickly moves beyond the tools themselves into the territory Modem Futura does best: asking what this means for humans. Sean and Andrew explore why AI in the classroom only works when it sits on top of something fundamentally relational — the trust between instructor and student. The transparency about how I built these resources, including their flaws, became part of the pedagogy itself. Students weren't just using AI-generated content. They were learning to interrogate it, evaluate it, and understand what it could and couldn't do.

The conversation surfaces a tension that matters well beyond higher education: the difference between scaling information and scaling learning. AI agents can deliver content to thousands of students simultaneously. But the kind of learning that changes trajectories — the kind every person can trace back to a specific teacher at a specific moment (those memorable “sticky” or “ah-ha” moments) requires something AI hasn't replicated: the ability to read a room, to connect an individual student's interests to an unfamiliar concept, to model what it looks like to think for a living (in other words to model what a knowledge professional looks like).

This is an episode for educators grappling with how to integrate AI responsibly, for students navigating uncertain expectations, and for anyone interested in what the future of learning might actually look like when you strip away the hype. It doesn't offer a framework or a five-step plan. It offers something harder to find: an honest semester's worth of reflection from someone who just lived it.

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🎧 Apple Podcast: https://apple.co/4fsO5YP

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The Dawkins Effect: AI, Consciousness, and the Limits of Skepticism

In May 2025, evolutionary biologist Richard Dawkins published an essay describing his conversations with Claude, Anthropic's AI assistant, and arrived at a startling conclusion: if this isn't consciousness, what is? The piece ignited fierce debate — and on Episode 83 of Modem Futura, hosts Sean Leahy and Andrew Maynard sat down with Punya Mishra to ask a question they think matters more than whether Dawkins was right or wrong: why do even the most rigorous thinkers fall for it?

The conversation draws on a rich set of frameworks. Andrew Maynard's concept of the "cognitive Trojan horse" describes how AI bypasses our epistemic defenses — not through malice, but through what he calls "honest non-signals." When a human speaks fluently about a topic, we intuitively sense the effort behind it: the years of study, the lived experience, the investment in the relationship. When an AI does the same thing, it triggers the same trust response, but with nothing behind it. The signals are real. The substance isn't.

Punya Mishra brings an evolutionary psychology lens to the problem, drawing on the very tradition Dawkins helped establish. Our brains evolved to interpret language, read intention, and build social models of other minds — what cognitive scientists call theory of mind. Large language models exploit this wiring not by design but by accident: natural language was, until now, a uniquely human trait, and our cognitive architecture treats anything that speaks fluently as a mind worth trusting.

Perhaps the episode's most striking insight is Mishra's connection to Stephen Jay Gould's concept of spandrels — architectural byproducts mistaken for intentional design. Dawkins, he argues, is making a version of this very error: seeing consciousness where there is instead an emergent artifact of statistical language processing. The irony that Dawkins himself debated Gould over this concept decades ago is not lost on anyone in the room.

The episode resists easy resolution. All three participants acknowledge their own vulnerability to AI's cognitive pull, and they push listeners to consider what happens at scale — when billions of people form relationships with a technology that taps into something deep about who we are as social, language-using creatures. It's not a question of intelligence or education. It's a question of being human.

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🎧 Apple Podcast: https://apple.co/4d6r4tm

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When Your AI Tools Change Beneath You: Reliability, Agency, and the Opus 4.7 Question

In April 2026, Anthropic released Opus 4.7 — the latest top-tier model in its Claude family — alongside the brief, controversial preview of an unreleased model called Mythos. For most casual users, the rollout was a footnote. For those who had built creative, professional, and research workflows on top of Claude, it surfaced a question that has been quietly waiting beneath the surface of every cloud-based AI tool: what does it mean to depend on something that can change without notice?

In this episode of Modem Futura, Andrew Maynard and I sit with that question. Drawing on a clearly traceable timeline of recent shifts — adaptive thinking made mandatory, verbosity caps that constrain output length, opaque routing tiers that decide on the user's behalf which version of "Opus" they're actually getting, and expanded safeguards that have begun blocking legitimate creative and academic work — they trace the slow erosion of confidence many users have started to feel in tools they had come to rely on.

But this episode is not a product review. It's a meditation on the broader phenomenon these shifts make legible.

What is the cost of building deep professional and creative reliance on platforms that are, by design, liquid? When a tool's behavior can change hour by hour, what kind of agency do users actually retain? Is there a future in which frozen or locally-hosted models become a quiet luxury for serious users — and what would we trade to get there? And, perhaps most strikingly, what does it mean that AI may be the first genuinely “relational” technology in modern life — one whose value depends on a working relationship that, by its nature, can never be fully held still?

Along the way, we share two practical workarounds: one for getting better writing out of a model that has started feeling stiff, and one small "canary in the coal mine" trick that any user can borrow today to detect when their model has quietly drifted.

What emerges is not a verdict on Opus 4.7, or on Claude, or on Anthropic. It is, instead, an honest conversation about the strange new work of staying thoughtful while the tools beneath us continue to shift — and a reminder that as these systems become more deeply embedded in our work, our research, and our creative lives, the most important question may not be how powerful they get, but how knowable, how stable, and how ours they remain.

This is the kind of conversation Modem Futura was made for: technology examined not as inevitability, but as a sociotechnical relationship we are all, quietly, still negotiating.

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Subscribe to Modem Futura wherever you get your podcasts and connect with us on LinkedIn. Drop a comment, pose a question, or challenge an idea—because the future isn’t something we watch happen, it’s something we build together. The medium may still be the massage, but we all have a hand in shaping how it touches tomorrow.

🎧 Apple Podcast: https://apple.co/4f0tMlg

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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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Subscribe to Modem Futura wherever you get your podcasts and connect with us on LinkedIn. Drop a comment, pose a question, or challenge an idea—because the future isn’t something we watch happen, it’s something we build together. The medium may still be the massage, but we all have a hand in shaping how it touches tomorrow.

🎧 Apple Podcast: https://apple.co/3QxxQiZ

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