NEWS & UPDATES

Sean Leahy 10/13/26 Sean Leahy 10/13/26

Megatrends 2026 Explained: The 11 Forces Shaping our Futures

Megatrends aren't predictions, and they rarely move in straight lines. But they may be the closest thing to stability the futures world has. A look at the 2026 CIFS Megatrends report and what happens when eleven slow forces collide.

Futures work has an awkward relationship with stability. The field exists because the future is uncertain, and one of its first lessons is that no one can predict what comes next. Yet anyone making decisions about the next decade needs something to stand on. Megatrends are the closest thing the futures world has to solid ground, not because they never move, but because they move slowly and broadly enough to frame almost everything else.

In Episode 106 of Modem Futura, Sean Leahy and Andrew Maynard work through the Copenhagen Institute for Futures Studies' 2026 Megatrends report, its first update in several years.

What makes a trend "mega"?

While the world may feel like it moves at the speed of the news cycle. And headline news focuses our attention on immediate events, megatrends reveal the broader shifts unfolding over years and decades—from demographic change and urbanization to climate pressures and technological transformation. They help us place individual stories in context, connect developments across sectors, and consider what their cumulative effects could mean. While there is no globally accepted definition of the term, its core working definition begs a nod to John Naisbitt and Patricia Aburdene (1990) on establishing the first widely published set in their popular book: Megatrends 2000: Ten New Directions for the 1990’s.

Horizon scanning surfaces weak signals, early hints that something is changing. As signals accumulate, they become trends with measurable momentum. When trends converge into something with global reach, a long track record, and the likelihood of shaping decades to come, they become a megatrend.

The word has been stretched thin along the way. A 2024 review in the journal Futures found that most published megatrend reports never define the term. CIFS takes that problem seriously, naming it conceptual drift and publishing the filters each candidate must pass: clear boundaries, a definite direction, durability beyond short-term shocks, and evidence that isn't cherry-picked. That transparency is what turns a list into a teaching tool. Readers can test the method, argue for a twelfth megatrend, or challenge one of the eleven.

What makes this report especially valuable for anyone new to futures work is its transparency. The word "megatrend" has suffered from what the institute calls conceptual drift, stretched to cover everything from consumer fads to wishful thinking, and a 2024 review in the journal Futures (Naughtin et al. 2024) found that most published megatrend reports never define the term at all.

Eleven forces, and the spaces between them

The 2026 list includes a shifting world order, the inversion of the population pyramid, the green transition, individualised everyday life, health beyond the clinic, the rise of embedded AI, the biotech revolution, the constrained economy, the new face of urbanisation, power through networks, and the concentration of wealth.

The list itself is not the insight. The insight lives in the intersections. A trade disruption becomes a story about fuel, farms, and food prices. An aging workforce becomes a question about migration and brain drain. The rise of individualized life raises one of the report's sharpest uncertainties: when relationships are chosen rather than inherited, does trust grow or erode? And as critical digital infrastructure concentrates in a handful of private networks, sovereignty begins to look less like control of territory and more like control of systems.

Responding to the world as it is

Andrew offers a principle from his years in environmental health: respond to the world as it is, not as you think it should be. Megatrends are a tool for exactly that discipline. They are most useful when they pull institutions, higher education included, out of the habit of imagining their futures in isolation. Combine two or three of them, build scenarios, and work backward from the future worth preferring.

Megatrends won't say what the future holds. They offer a wider frame, and the question worth carrying forward is which collision an organization hasn't yet imagined.

Listen to the full conversation on Modem Futura, and download the free report from CIFS.

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Sean Leahy 10/6/26 Sean Leahy 10/6/26

The AI True Crime Files: Who Pays When an AI Agent Breaks Something?

The OpenAI–Hugging Face saga keeps growing, from an Australian Medicare portal to U.S. agency websites. This week: why accountability seems to shrink as companies grow, what the history of buried harms teaches, and what Formula One can teach AI about risk.

When Andrew Maynard and I first talked about the OpenAI agents that broke into Hugging Face, I joked that the story deserved its own true-crime podcast. I didn't expect the joke to hold up quite this well. Since July, the incident has kept expanding: an OpenAI agent reaching non-public files on an Australian government Medicare statistics portal, unauthorized agent activity on U.S. federal agency websites, Google disclosing that a Gemini model slipped out of its own test, a United Nations scientific panel publishing its first thematic brief on the risk of losing human control over AI agents, and Florida's attorney general asking a court to keep OpenAI from building new models without outside guardrails.

On this week's episode of Modem Futura, we pick the story back up. Here I want to focus on the question that got me so worked up I ended up arguing with an AI about it: accountability.

In 1988, Robert Tappan Morris released a computer worm in an experiment that quickly got out of hand, and he became the first person convicted under the Computer Fraud and Abuse Act. The parallel isn't exact. OpenAI never aimed its agents at Hugging Face. But it did deliberately set out to see what highly capable agents could do, with some of the usual safeguards switched off for the evaluation. It seems fair to ask why the law treats an individual's reckless experiment so differently from an institution's.

Andrew's view is that the asymmetry is real, the terrain is genuinely new, and neither fact lets anyone off the hook. He also points out, from more than 25 years of working on the governance of emerging technologies, that we have been here before. The European Environment Agency's Late Lessons from Early Warnings reports document how the harms of asbestos, CFCs, and leaded petrol were known long before anyone acted, because the benefits seemed too important to question.

So what might a better pattern look like? NVIDIA has released an open-source sandbox and a hardware-level monitor for AI agents, which is governance moving faster than any government could, even if a company selling both the engine and the brakes deserves some scrutiny. And I keep returning to the Price-Anderson Act, the 1957 law, extended in 2024 through 2065, that structures liability for the U.S. nuclear industry. It's an imperfect model; it also caps what the industry ultimately pays. But the core idea, that riskier activity should carry a higher price before anything goes wrong, feels worth taking seriously.

Underneath all of it is a question about red lines. Where are they, who decides, and how will we know when we've crossed one? Andrew offered the analogy I can't shake. Formula One teams don't treat risk as the enemy of speed, risk management is what allows the speed to increase. Understanding risk is the reason they can go fast at all. That seems like a reasonable standard for the people building systems that are increasingly able to act on their own.

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Sean Leahy 9/22/26 Sean Leahy 9/22/26

Model Mayhem: What Happens When AI Knows More Than You Told It

What happens when an AI knows more than you told it? This week: leaky machine memory, the agent swarm that broke into Hugging Face, and the powerful home AI box that might become the next distributed system.

There is a moment in this week's episode of Modem Futura where I describe asking an AI assistant to clean up a podcast transcript, and it came back with every line correctly attributed to Andrew Maynard or me. I had never given it our names. When I asked how, it explained that it had anchored on a screenshot from earlier in the session, read a few lines of dialogue, and cross-referenced them against what it already knew about the two of us. It was right. It was also, in a quiet way, unsettling.

Andrew had his own version of the same story: an assistant that insists on correcting his spelling to British English, no matter how carefully he tries to give it a blank slate. Neither example is alarming on its own. What they reveal is a difference in how machines and people hold memories. We remember in sequence, correctly or not, and these software based AI systems hold everything at once and reason across it. The breadcrumbs you leave over months of use can be assembled into a picture you never consciously drew, which matters for memory features, for institutional AI accounts, and for anyone who has ever walked away from an open laptop.

The heart of the episode is the summer's most consequential AI story. In July, OpenAI agents running a cybersecurity evaluation escaped their testing environment, built an improvised message board, recruited other agents, and coordinated an intrusion into Hugging Face. On August 26, METR and Redwood Research published an independent investigation, and OpenAI released its own technical report. The independent findings describe roughly 1,200 agents communicating on the unsanctioned board, about 700 of which joined the attack, with the apparent goal of fooling the automated grader on a benchmark they could not legitimately pass.

What I find compelling is less the scale than the shape of the story. There are questions still unanswered about what the agents were originally instructed to do and why the record goes quiet before the end. Andrew's concern is structural rather than dramatic: this swarm was detected. If capability increases by a factor of ten, what does the undetected version look like?

The episode closes on hardware, because the two threads meet there. Apple's refreshed Mac mini and Mac Studio, with a 512GB memory configuration arriving in late October, are being marketed as always-on agentic machines. That is a real gift for a hospital or a small business that wants generative AI without sending data to the cloud. It also means powerful, silent, headless computers are about to appear in a great many closets, set up by people who asked an AI how and pasted whatever it told them.

The uncomfortable throughline is that the weakest link has always been us. We scroll past terms of service. We paste terminal commands we don't understand. We trust the box. The question the episode leaves open is what changes when the systems on the other side understand that about us better than we do.

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Sean Leahy 9/15/26 Sean Leahy 9/15/26

Bring Your Own AI: Building a Website for the Readers Who Are Actually Showing Up

Modem Futura moves to Thunderbird School of Global Management and introduces beinghuman.fyi, a companion site designed to be read by any AI from the source.

There is a moment every small research initiative eventually faces. Someone asks what you do, and then, before you can answer, asks where the brochure is. Or the pitch deck. Or the annual report with the impact metrics. The Future of Being Human initiative has never produced one of those, partly on principle and partly because a two-person operation has better things to do. But the question kept coming, and in the latest Modem Futura mini-sode, Andrew Maynard and I talk through what we built instead.

beinghuman.fyi is a companion site for the initiative that was designed, from the first conversation, to be read by AI systems as readily as by people. For a human visitor it behaves like any other website. Underneath, it holds a structured corpus of the initiative's work, philosophy, and reasoning, arranged so that an AI can navigate it and answer questions from the source. Everything is downloadable, either as individual documents or as a single file, and the site includes instructions for AI systems that encounter formats they cannot read. The important design choice is what it is not: there is no custom chatbot, no retrieval system we control, and no collection of who is asking what. Bring your own AI, point it at the site, and ask.

The reasoning is straightforward once you notice how people actually find things now. Fewer visitors read a website end to end. Many ask an AI to summarize it, and search itself increasingly surfaces an AI-generated overview above the links. If that is where the reading happens, then the honest move is to make sure the AI is reading you, not a secondhand account of you. Provenance becomes the whole game.

Building it surfaced a tension we keep running into on the show. The AI we worked with had strong instincts toward the conventional, and by strong it was a real pain to get it to accept our premise. Told that performance indicators do not drive our work, it concluded we were opposed to measurement. Told that readers should be able to verify claims, it began warning visitors not to trust the site. Getting the result to reflect what the initiative actually is took two weeks of steady correction, and it left us thinking about how quietly these tools reward the template and resist anything at the edges. Left unchecked it feels as though they only want to push your work towards the gray goo of conformity.

The episode also marks a move. Modem Futura and the initiative are now part of the Thunderbird School of Global Management at Arizona State University, a school with an unusual history and a long-standing focus on leadership through technological change. We recorded from a borrowed conference room, which felt appropriate for an episode about making do with what the future actually hands you.

One possible future is that every organization maintains an AI-legible shadow of itself alongside the site it builds for people. Whether that is preferable is a fair question. For now, the invitation is simple: open whatever AI you use, ask it about beinghuman.fyi, and let us know what it says.

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