I’m drawn to projects that look “impossible”.
My innovating story began making AI work where it isn’t supposed to. I’ve invented AI systems in security, telecom, finance, genetics; founded businesses; taught, set up, and managed my innovating process worldwide in industry and academia; helped 150+ MIT technologies find a path to solve real-world problems; and shepherded thousands of people to innovate.
You pick up a few things helping machines acquire intelligence: there’s nothing intuitive to the world we’ve built; like humans, computers struggle with mindsets borne of centuries of laborious understanding powered by pencil and paper. Kids go about with unrestrained spirit of inquiry and untold aptitude for frustration—curiosity and tantrums. By the time education tames us, we have formulas, recipes, coping strategies—none of which makes for a particularly intelligent computer.
The same with innovation: recipes abound that conflate innovation and what to do with one; you’re expected to recognize innovation at sight. It never happens. Innovating takes learning and doing.
My book, Innovating: A Doer’s Manifesto for Starting from a Hunch, Prototyping Problems, Scaling Up, and Learning to Be Productively Wrong (MIT Press, January 2017) is my guide. It draws from mindsets and principles from science, engineering, AI, game theory, management, economics, and behavioral science, but requires no technical knowledge. It is written so you may begin innovating with what you already have; all you need is a hunch. You can keep waiting for an earth-shattering idea, or you can start right away.
My goal for the book: restore that spirit of inquiry; get us talking about daring to venture into the impossible and solving real-world problems, not just “innovation.”
Today, I’m an educator and researcher at MIT, I advise organizations on AI and Innovating. I’m an explorer, I don’t yet know what’s next.