Fifty years ago this week, the Washington Post asked some of America’s brightest scientific minds to imagine 2026. What would the world look like at America’s 250th birthday? They were serious people. They were careful thinkers. And they were almost entirely wrong. Not because they were foolish. Because they were looking in exactly the wrong direction.

This week on RTHK Radio 3 Morning Brew, Phil Whelan and I spent time with that 1976 article. And sitting across from Phil in that conversation, something became very clear. The people in 1976 who got it most wrong were the ones who were trying hardest. The ones with the most detailed mental models. Because detailed mental models are built from what exists. What they needed to predict was something that didn’t exist yet, had no language yet, and left no visible trace of its coming.

Listen to the full segment with Phil Whelan on RTHK Radio 3 Morning Brew:

What They Actually Predicted

The Washington Post piece, published in July 1976 to mark America’s bicentennial, surveyed scientists and experts across disciplines. Their 2026 predictions were detailed, serious, and almost entirely hardware-focused.

Gene editing at scale. Nuclear-powered artificial hearts. Deep-sea mineral mining. Bigger rockets. Permanent colonies on Mars. High-fidelity video telephony in every home. Massive central computing systems owned by governments and large corporations.

Go down the list and you’ll notice something immediately: every single item is physical. Every prediction is about atoms, not bits. Every vision of the future involves something you could build with steel and engineering and enormous amounts of money. The future, in 1976, was a hardware problem.

Not one of them mentioned software. Not the internet. Not personal computing as something an ordinary person might own. Not smartphones. Not social media. Not AI as a mass technology. Not the idea that the most powerful companies on earth fifty years later would sell things you can’t hold, with billions of people carrying their entire professional and social lives in a device that fits in a pocket.

The revolution they were preparing for never quite arrived. The revolution that did arrive? They never saw it coming.

Why the Smartest People Get the Biggest Things Wrong

There’s a pattern here worth naming clearly, because it’s not a story about 1976. It’s a story about how prediction works, and why it consistently fails in the same way.

When experts sit down to predict the future, they extrapolate from what they can see. This makes sense. But it creates a structural blind spot: anything that’s genuinely new: anything that doesn’t yet have a name, doesn’t yet have a market, doesn’t yet have a visible form. It doesn’t show up in the model. You can’t extrapolate from something that doesn’t exist. You can only predict things that are already partially visible.

Hardware was visible in 1976. The transistor existed. Rockets existed. Nuclear technology existed. All those predictions were extrapolations of real things that could be seen and touched and funded. Software, the internet, personal computing. These existed too, in primitive forms, mostly in university labs and research institutions. But they weren’t visible to the general culture. They had no consumer form yet. And without a consumer form, they had no gravity in anyone’s mental model of the future.

This is what I think of as the visibility trap. We predict from what’s visible. The revolutions tend to come from what isn’t.

Phil made this point himself during our conversation. These were brilliant scientists, he said, and yet you never got the impression they thought any of it would be in everyday use. The technology existed. The insight that it would become democratised. That within two decades it would be in every home, and within five decades in every pocket. That insight was entirely missing.

And that’s the thing. In 1976, if you said “the next 50 years will be defined by invisible infrastructure,” you’d have been laughed out of the room. The future was supposed to be visible. Big. You’d see it coming.

The biggest shifts are usually the ones you don’t see coming.

The Australian Parallel: What We Also Got Wrong

I want to pause on something from that conversation that went beyond the technology predictions. Because the 1976 article also included social and economic forecasts, and those missed the mark in equally revealing ways.

In Australia in 1976, a woman couldn’t take out a bank loan by herself. She needed a male guarantor. This wasn’t an anomaly. It was the system. The banking sector, effectively controlled by three or four major institutions, said what happened. And people complied.

The experts predicting 2026 in 1976 predicted reduced working hours, better leisure, more automation. They didn’t predict the wholesale entry of women into economic life as full participants. They didn’t predict the transformation of Australia from a conservative, banking-sector-controlled economy into one of the more dynamic economies in the Asia-Pacific. They didn’t predict that the female workforce participation rate in Australia (which sat around 40% in 1976) would climb past 62% by 2026.

These aren’t minor details. They’re arguably more consequential than whether we got flying cars. And they were entirely invisible in the 1976 predictions because they required imagining social change that hadn’t been signalled clearly enough yet.

The pattern holds: the things that actually changed the most were the things nobody was modelling.

The Dictionary Knows What’s Already Survived

Phil and I also talked this week about another piece I’d written earlier in the week, about the Oxford English Dictionary’s latest update to Australian English. Twelve new words added. Yeah nah. Donkey vote. No wuckers. A cup of tea, a Bex, and a good lie down. And two First Nations words: yorga (woman, Nyungar language) and dooligah (a large hairy spirit of the bush, Dhurga/Dharawa languages of NSW’s south coast) are now formally part of the Oxford English Dictionary.

I explored what these additions tell us about how culture actually moves in a piece earlier this week.

What the OED update reveals is the opposite of the Washington Post problem. The Washington Post was trying to predict what didn’t exist yet, and got it wrong. The OED was doing the opposite: ratifying what had already been decided, what had already proved it was here to stay.

Yeah nah has been in Australian mouths since at least the 1970s. The OED didn’t invent it; they waited until they were certain it wasn’t going anywhere, then wrote it down. The dictionary follows culture by decades. Which means everything in this year’s Australian update has already survived. It was already here, it just hadn’t been officially acknowledged.

There’s a foresight lesson in that. What the dictionary shows you isn’t what’s coming. It’s what the culture decided, long ago, to keep. The future is already in the room, but it hasn’t been given a name yet.

This is Immediate Futures thinking. The question isn’t what might arrive. The question is what’s already arrived that we haven’t fully noticed or named.

What We’re Missing for 2076

Here’s the question I kept coming back to after that conversation: if the people in 1976 systematically missed software, what are the people in 2026 systematically missing?

This isn’t a rhetorical question. It has a structure, because the visibility trap is predictable. Whatever the next revolution is, it’s almost certainly something that currently looks too small, too experimental, too theoretical, too far from consumer form to seem important. The people most likely to miss it are the ones building the most detailed models of the current domain.

My best guess (and I want to be clear this is a guess, not a prediction, because that’s exactly the point) is that we’re missing several things simultaneously.

We’re missing the full scope of biological computing. Not AI as software, which everyone is watching obsessively. Something deeper: the intersection of biological systems and computational systems in ways that don’t look like technology yet. The 1976 scientists predicted gene editing. They got the technology right, but they imagined it as hardware (the gene is a physical thing you cut). They didn’t predict the invisible infrastructure of biological data: the computational models, the protein-folding algorithms, the genomic databases that would make the gene editing possible. The next revolution might be in that intersection, and it currently has no consumer form.

We’re missing cultural fragmentation as infrastructure. The 1976 predictions included “video telephony in every home.” They got the technology right. They didn’t predict that this connectivity would also fragment attention, atomise community, and create entirely new forms of social organisation with no precedent. That fragmentation is now infrastructure for everything: politics, commerce, information, identity. We talk about it as a problem. It might also be the platform for something we haven’t named yet.

We’re probably missing the second-order consequences of the longevity shift. People are already discussing the possibility of dramatically extended lifespans this century. Most who hear this think hardware, biology getting better. They’re not thinking about what dramatically longer lives do to career structures, to savings systems, to intergenerational transfer of knowledge, to the social contract between old and young, to the tax base, to what “retirement” even means. These are the invisible consequences. The ones nobody is seriously modelling at the scale they deserve.

I wrote about something related to this earlier this year, exploring how science fiction shaped our expectations of AI in hardware terms (the robot, the android) and left us largely unprepared for the software reality (the assistant, the agent, the invisible layer). We’re probably making the same category error with biology.

The Structural Problem With Prediction

At this point in our conversation, Phil made an observation that stuck with me. He said we never thought we’d have it in whatever we had in our pockets in those days. He was talking about computing. But “whatever we had in our pockets” is the key. In 1976, the mental category “pocket” and the mental category “computer” didn’t overlap. The thing that would collapse them had no precursor in consumer experience.

This is why I’ve largely stopped trying to predict specific technologies. Not because prediction is pointless, but because specific technology prediction is the wrong game. The more productive question is: what forces are already operating that haven’t yet found their form? What pressures are building that will eventually need an outlet? What human needs are currently unmet in ways that will eventually generate solutions?

In 1976, the unmet needs were obvious in retrospect. People wanted to communicate more easily. People wanted to access information without going to a library. People wanted to stay connected across distance. The technologies that answered those needs (the internet, mobile phones, search engines) were mostly invisible. But the needs were entirely visible. What nobody predicted was the form the solutions would take.

This is the distinction between a futurist and a foresight strategist, something I’ve written about at length here. The futurist is in the business of predicting. The foresight strategist is in the business of preparation: helping organisations understand the forces already operating and think through what those forces will eventually demand of them. One is about getting the future right. The other is about being ready for it, whatever form it takes.

In a piece I wrote earlier this year, I explored how the Apollo program gave us technologies nobody planned for: scratch-resistant lenses, memory foam, invisible braces, cordless tools, water purification systems. The moon mission was a hardware problem. Its ripple effects were almost entirely invisible from where the mission was launched.

That’s Ripple Effects thinking. The consequence of the decision is usually not the thing you were deciding about.

Three Things Worth Doing Now

The lesson of 1976 isn’t “don’t predict.” It’s something more nuanced and more actionable.

Stop watching the obvious signals and start watching the invisible ones. The 1976 experts were watching the visible signals: rockets getting bigger, genetics getting more sophisticated, nuclear technology getting more refined. The signal they weren’t watching (because it was invisible) was the decreasing cost of computing power and what happens to any technology when it crosses the affordability threshold into consumer reach. Watch the invisible signals. What’s becoming affordable this year that wasn’t three years ago? What’s crossing from institutional to personal? That’s usually where the revolution is.

Take your own blind spots seriously. Every mental model has a shape, and the shape determines what you can see and what you can’t. The experts in 1976 had excellent models of physical technology. They had poor models of information technology as a social force. Ask yourself: what is the shape of my mental model? What does it make visible? What is it structurally incapable of showing me? This isn’t rhetorical. It’s a genuine diagnostic. What do you know so much about that you’ve stopped questioning it?

Name the unmet needs, not the predicted technologies. If you want to understand what the next ten years will bring, don’t try to predict what technologies will emerge. Instead, identify the human needs that are currently going unmet, undermet, or met in ways that feel like friction. Those needs will eventually generate solutions. You don’t need to know what the solution will be. You need to know what pressure it will eventually answer. That’s where you prepare.

This is what I keep coming back to in the work I do with leaders and boards. The question isn’t “what’s coming?” It’s “what’s already here that we haven’t fully acknowledged yet?” And separately: “what pressures are building that will eventually need an answer?” Those two questions give you more preparation value than any prediction model.

The Lesson From Yeah Nah

I want to come back to the OED update, because I think it contains the most important insight of this entire conversation.

Yeah nah has been in use for at least fifty years. It evolved from practical necessity. Australian culture needed a polite but clear way to dissent, to say “I hear you, and no.” The OED didn’t create it. Nobody planned it. It emerged, survived, and eventually became official.

The same is true of donkey vote. When Australia made voting compulsory, the culture immediately started generating a workaround: a way to comply with the letter of the law while exercising a quiet protest. The word for that workaround survived because the need it served survived.

And dooligah, a large hairy spirit of the bush, from the Dhurga/Dharawa languages of NSW’s south coast, is now in the Oxford English Dictionary. Sixty thousand years of continuous language, and it survived. Not because someone planned it. Because it was resilient. Because it served something in the culture that couldn’t be replaced.

The lesson isn’t about language. It’s about survival as signal. The things that survive (the words, the technologies, the social forms) survive because they answer real needs. The things that get predicted but don’t survive (the nuclear-powered hearts, the permanent Mars colonies of 2026) were often extrapolations of capability rather than answers to genuine need.

If you want to know what will still be here in 50 years, don’t look for the most impressive technology on the list. Look for the thing answering the deepest human need. That’s what survives.

The lesson from 1976 is not that prediction is impossible. It’s that the revolution is almost always invisible before it happens. Which means right now, right this second, we’re probably missing the equivalent of software. Something that will be completely obvious to the people sitting here in 2076, looking back at us.

---

If this is landing close to home for your organisation, I work with leadership teams and boards on exactly these kinds of decisions — what the signals mean, what the ripple effects are, and what to do before the moment becomes a crisis. Get in touch.

You can also subscribe to my Immediate Futures briefing — a short, weekly read on the signals worth paying attention to, written for leaders who want to stay ahead of what is already arriving.

Choose Forward.

#MorrisMisel #RTHK #MorningBrew #ImmediateFutures #Foresight #ForesightStrategist #ChooseForward #TechPredictions #FutureOfLeadership #StrategicForesight

---