Edited by Ben Shneiderman, University of Maryland, College Park, MD, and accepted by Editorial Board Member Eva Tardos November 7, 2018 (received for review May 20, 2018)
Analogy—the ability to find and apply deep structural patterns across domains—has been fundamental to human innovation in science and technology. Today there is a growing opportunity to accelerate innovation by moving analogy out of a single person’s mind and distributing it across many information processors, both human and machine. Doing so has the potential to overcome cognitive fixation, scale to large idea repositories, and support complex problems with multiple constraints. Here we lay out a perspective on the future of scalable analogical innovation and first steps using crowds and artificial intelligence (AI) to augment creativity that quantitatively demonstrate the promise of the approach, as well as core challenges critical to realizing this vision.
Author contributions: A.K., L.Y., T.H., J.C., K.G., R.E.K., and D.S. designed research; A.K., L.Y., T.H., J.C., K.G., F.N., R.E.K., and D.S. performed research; A.K., L.Y., T.H., J.C., K.G., F.N., R.E.K., and D.S. contributed new reagents/analytic tools; A.K., L.Y., T.H., J.C., K.G., F.N., R.E.K., and D.S. analyzed data; and A.K., L.Y., T.H., J.C., H.L.-A., K.G., F.N., R.E.K., and D.S. wrote the paper.
The authors declare no conflict of interest.
This paper results from the Arthur M. Sackler Colloquium of the National Academy of Sciences, “Creativity and Collaboration: Revisiting Cybernetic Serendipity,” held March 13–14, 2018, at the National Academy of Sciences in Washington, DC. The complete program and video recordings of most presentations are available on the NAS website at www.nasonline.org/Cybernetic_Serendipity.
This article is a PNAS Direct Submission. B.S. is a guest editor invited by the Editorial Board.
Published under the PNAS license.
