The Future Is Downstream of Philosophy

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I was scrolling on Saturday morning and stopped at the feed of a marketing specialist who had recently rebranded herself as a futurist. Every image was futuristic in the most familiar sense possible. A robotic hand rendered in transparent glass, lit from within with blue light. Robots exactly like the ones some of us photographed and actually spoke with at CES years ago, back before ChatGPT existed. Captions like "AI is the future" sitting next to "I build the future," the kind of phrase that's been recycled at every technology conference for a decade without anyone asking what it's actually claiming. 

Something that had been forming in me for months  in the kitchen, in bed, in the car, with my husband, with a few close friends finally pushed all the way up, and I opened the notes app on my phone. It almost became an Instagram post. I had too many thoughts for a caption, though, and the character limit saved me — and saved the space, and probably saved that futurist-marketer too. I wrote an essay instead.

Here's why that particular feed made me so sad.

Imagine San Pablo Avenue, in Albany, a small town beside Berkeley. It's known locally for the encampment running along both sides of it — tents, shopping carts pulled from stores, people living exactly there, in public, block after block. A few meters away sit buildings, real infrastructure, mostly empty. I don't know who owns them or why, and for this question it doesn't matter. 

Here's what almost no professional futurist's rendering of this street would actually show, and it isn't "the same." Left alone, without anyone deliberately imagining and building something different, things don't hold steady. They tend to get worse. So the honest extrapolation of San Pablo Ave isn't an unchanged street with better interfaces. It may also mean more people displaced economically as AI reshapes who work is designed for — a consequence these futurists rarely render, because job displacement doesn't fit the robot-hand aesthetic, so it never makes it into the image at all. They can't imagine it, or won't. And even the one honest technological detail they might include — something replacing the smartphone, maybe a robot delivering packages door to door — stops short of the actual scene that detail implies. Robot delivery to a paying customer with an address and an account is already ordinary; it barely counts as innovation anymore, it's a refinement problem, a logistics line item. A robot bringing food or aid to someone with neither an address nor an account is a category of innovation nobody is meaningfully discussing at all. Because the person was never the customer the technology was imagined for.

So the actual scene an honest rendering would have to show isn't a robot failing to notice a person in a tent. It's a robot, on its ordinary, well-funded route, reaching a tent, and continuing past it — not out of malice, but because the person inside it was never a variable in whatever future that robot was designed to serve.

Could any of these futurists have actually imagined that moment — the specific one, the robot and the tent occupying the same three feet of pavement — and rendered it anyway?

I don't think many have tried.

Our imagination is built from what we've already seen: existing technologies, stories, economic systems, cultural assumptions about which lives are worth designing for. Even trying to move past them, we carry them with us. So most of what gets called "imagining the future" is the present, extended forward with better materials. But I don't think the missing piece is only an absent philosophy. It's more specific than that, and it has at least three parts.

The first is extrapolation standing in for imagination — simply continuing a trend line and calling the result a vision, rather than actually asking what could exist that the trend line doesn't predict at all.

The second is that imagination is a capacity that can be trained, yet most of us are never taught to train it deliberately.

The third is structural. We are investing enormous resources in increasing the capabilities of AI systems, while the capacity of the human imagination directing those systems is barely treated as infrastructure at all. We benchmark models relentlessly. We have no comparable urgency around asking whether the people using them are becoming better at imagining beyond the assumptions they inherited. This is part of why I keep returning to a question underneath my forthcoming book, Imagine Next: what if we trained imagination as endurance, the way we train a body for distance, rather than waiting for it to arrive as a flash of inspiration?

I came to this question through invention, not through futurism.

Starting in May 2023, I ran a challenge that became 365 sustainable innovation concepts, finished in January 2025 — 616 days in total. Over time I developed a method for putting myself into a state where I'd notice things that fed imagination — small provocations I started calling sparks. A spark would turn into a raw idea. And almost every time, the raw idea turned out not to be original enough. It rarely existed in a vacuum; someone, somewhere, had usually already built a version of it. So I'd research further, try to shift the frame I was perceiving the problem through, and try again.

That process was gradual and often genuinely painful. More than once it brought me to something close to an existential crisis — moments where I seriously considered stopping the challenge, and later, moments where I considered abandoning the entire Imagine Next book. The difficulty wasn't producing ideas. It was learning how far I had to keep going after the first plausible idea appeared. I wanted all 365 concepts to contain something genuinely worth exploring, and over time my standard for what counted as original kept rising. Each concept at that stage of the project meant to genuinely contribute to solving specific Sustainable Development Goals.

The hardest part was a specific, recurring humiliation: believing I'd finally reached something original, researching it properly, and discovering it was still the same thing dressed differently. It happened again and again, closely enough to what happens to Alice in Through the Looking-Glass that I don't think the comparison is decorative. The Red Queen tells Alice, "it takes all the running you can do, to keep in the same place" — and that's exactly what months of that process felt like. Running as hard as I could, arriving at what felt like new ground, and finding I'd never left. There's another Wonderland scene that also felt painfully familiar: the Drink Me and Eat Me bottles, where Alice's whole sense of scale keeps changing underneath her, so nothing she's just adjusted to stays trustworthy for long. That's the specific texture of revising my own bar for what counted as "original enough" — the bar itself wouldn't hold still.

For a long time, I thought my worldview was already fairly radical. I worked inside regeneration, deep ecology, systems thinking. Those frameworks had changed how I saw the world, and I still value them.

But eventually I realized they were also frames. I used design thinking too, and systems thinking — tools I was trained in, still respect, and use professionally. They didn't get me much further either.

The questions that moved me furthest were often almost embarrassingly simple — questions that ignored something everyone else in the room had already quietly agreed to treat as fixed. Eventually I began allowing myself to work from premises that current science had not yet established—not treating them as facts, but as design hypotheses. What would become possible if this turned out to be true? What research would be required to find out? That temporary suspension of the known opened territory I could not reach by extrapolating only from what had already been demonstrated.

From there it was another long stretch of trial and error before I could look at a concept and say, with real confidence, that it held a substantive, undescribed idea that didn't collide with what already existed and might genuinely be worth developing as research, a startup, a mechanism, even a patent.

The method that emerged from this practice became what I now call the Inventiveness Ignition Loop. What I can say is that it didn't end when the 616 days did. Most of what came after was returning to my own earlier concepts — evaluating them again, analyzing them harder, running novelty checks I hadn't been rigorous enough to run the first time, iterating further — and finding new ceilings I hadn't been able to see before, even in ideas I'd already believed were finished. The proof was never that it got easier. It was that going back with sharper tools kept exposing limits the earlier version of me genuinely couldn't have found.

Imagination and invention, at the start, can feel like moving through dense fog, holding onto every branch just to keep from falling. Step by step, you build your own map. The fog doesn't necessarily disappear — mine certainly hasn't, even now — but eventually you stop needing to hold onto every branch. You learn how to move through it anyway.

Looking back, my earliest concepts weren’t failures of originality. They revealed where most people’s imagination begins—mine included. Most people stop there — one step, maybe two, often not even that, just repetition of whatever's already circulating. I don’t think that’s a failure of intelligence. It’s simply where the process starts. Most people are never told there is more beyond that point, or shown how to keep going.

When I sat down to imagine “One Day”—a full day inside a future where many of these concepts already existed together—it was still difficult. I had never tried to hold a future at that level of complexity before. But once I tried, something became clear: nobody had ever taught me that this kind of imagining was even possible, much less that it was a skill you could practice and strengthen.

AI makes all of this more urgent, not less. We can now generate almost unlimited images and ideas of the future. But abundance has never guaranteed originality. Ask an AI for a thousand future cities and you may get a thousand different images built on nearly the same assumptions: glass, light, seamless interfaces, familiar streets, and the same realities kept just outside the frame. AI radically changes how much we can produce. It does not, by itself, change the frame we are thinking inside. And when the imagination of the person directing it is undertrained, scale simply reproduces that frame faster, more beautifully, and with greater confidence.

So perhaps the real question was never whether humans or AI will imagine the future. It is this: from what philosophy, and with what capacity to imagine, will we ask ourselves—and AI—to do it?

Philosophy doesn’t stay in philosophy books. It changes what enters our field of attention. From there, different questions become possible, and entire categories of invention can appear or remain unseen. Some of those ideas eventually become companies, infrastructure, policy—the ordinary texture of somebody’s childhood. A child born into that world experiences none of it as philosophy. It is simply how things are.

We may never imagine entirely outside our own moment. But we can learn to see its edges, and become much more deliberate about what we carry forward. Before asking what the future will look like, perhaps we should ask what it assumes. Who disappeared from the picture before the rendering was even made? What have we already decided not to question?

And underneath those questions is the one I keep returning to:

What understanding of life made this future seem desirable in the first place?

This question eventually became central to Imagine Next: The Atlas and Method of Planetary Innovation: what if imagination could be trained as endurance, the way we train a body for distance, rather than treated as a flash of inspiration we either happen to receive or don't?