This year marks the 40th anniversary of the MIT Media Lab, a place I helped create not to organize what was already known, but to make space for what wasn’t.
It was interdisciplinary before the word became decor. It was designed for people who didn’t fit into departments. In fact, many of its founding faculty were misfits in the most productive sense: outsiders in their own disciplines, a veritable Salon des Refusés. We weren’t solving problems. We were developing solutions without knowing the problems. That’s how breakthroughs happen, at the edges, where curiosity is free to wander and orthodoxy is politely ignored.
The Lab’s purpose then, as now, was to explore what computers might mean for everyday life. Not computing, but living. It was never only about technology. It was about perspective. As I’ve said before, the best vision is peripheral vision.
The same could be said of Bauhaus, Black Mountain College, and Bell Labs. These were not just institutions of instruction. They were catalysts that attracted visionaries and outsiders, bringing together brilliant minds who might otherwise never have collaborated. They treated form as a form of inquiry. They questioned the boundaries between disciplines and then blurred them deliberately. They approached taste as methodology. And they did it by creating space—not just physical space, but cultural permission—for experimentation without expectation.
Today, we find ourselves in a moment that requires a similar response.
AI is not simply a faster way to do what we’ve already done. It’s a medium shift, a new substrate for thought, interaction, and aesthetics. But instead of treating it that way, we’re drizzling it onto legacy systems in ways that feel fundamentally mismatched. A few assistants here, a couple auto-completes there. More productivity, less imagination.
What we need is not more apps. What we need are new models, ones that challenge assumptions rather than reinforce them.
The environments that foster true innovation combine friction between disciplines, treat computation as a raw material, and allow design to lead rather than lag. One such effort is unfolding in New York: AIR, short for AI Residency, a new kind of accelerator for design-led AI products. Founders are encouraged not to chase metrics, but to ask better questions. What does it feel like to use this? What kind of world does it assume? What kind of relationships does it create?
Too much of today’s AI conversation revolves around scale: How many users? How fast is the inference? How good is the ROI? These are fine questions, but they are not the interesting ones.
The interesting questions are more fundamental: What new literacies will we need? What new misuses will emerge? Can this technology help us understand ourselves better?
History tells us that significant ideas rarely come from the center. They begin at the margins, where ideas are allowed to be incomplete, even incorrect. Places where success is not the goal, but learning is.
Efforts like AIR matter because they create the conditions where breakthroughs tend to happen. The next big thing often starts as something strange. It does not arrive fully formed, or announce itself with clarity or consensus. It is shaped by small, curious groups, exploring the paths others have overlooked.
The Media Lab taught me that the future doesn’t start with a plan; it starts with an experiment. If history is any guide, the future of technology won’t be determined by incumbents or insiders. It will be authored by small groups with unusual perspectives and the freedom to follow them.
We should support that pursuit. We should build the spaces that make them possible.
Because what comes next is not a product. It is a provocation.