In one giant leap for AI and innovation, researchers at Carnegie Mellon University and the Hebrew University of Jerusalem have come up with a method that allows computers to mine databases of patents, inventions and research papers, to create new products and solve problems.
What scientists have done is devise a way for computers to find analogies, that is comparisons between very different methods and problems that have underlying similarities.
Analogies have played a huge part in many scientific discoveries. According to John Pollack, former Bill Clinton speechwriter and author of Shortcut: How Analogies Reveal Connections, Spark Innovation, and Sell Our Greatest Ideas, they are at the root of innovation.
The Role of Crowdsourcing
The researchers devised their novel method with a combination of crowdsourcing and a type of AI known as deep learning. They observed how people found analogies – specifically, how crowd workers hired through Amazon Mechanical Turk would look for analogous products in the Quirky.com product innovation website.
The many insights they gleaned from their observations were used to train computer software, which was then able to find even more analogies.
“Once you can search for analogies, you can really crank up the speed of innovation,” said Dafna Shahaf, a CMU alumnus and a computer scientist at Hebrew University. “If you can accelerate the rate of innovation that solves a lot of other problems downstream.”
The research team presented their findings on Ag 17 at KDD 2017, a Conference on Knowledge Discovery and Data Mining, in Halifax, Nova Scotia.