A couple years ago I wrote about an effort to emulate analogous thinking in order to tackle difficult problems and drive innovation. The research, conducted by computer scientists at Carnegie Mellon University and Hebrew University in Jerusalem, sought to harness the power of a deceptively simple intellectual trick: Solving a complex problem by making unlikely connections to known problem-solution sets that might seem unrelated on the surface.
If you could train AI to “think” analogously, the premise holds, you’ll drive an explosion of innovation.
The researchers are back, abetted by scientists from the Bosch Research and Technology Center in Pittsburgh, the University of Maryland, and New York University Stern School of Business, with a new report published online this week by the Proceedings of the National Academy of Sciences. The report describes a process for utilizing remote workers and AI in concert to identify analogies. The possible upshot is a machine learning toolkit that could accelerate innovation and lift us past what some describe as an innovation plateau.