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Harnessing the Human Diversity of Mind

What is the compelling question or challenge?

Enabling the next leap in advanced computing approaches, including artificial intelligence, through incorporation of neurodiverse modes of thinking.

What do we know now about this Big Idea and what are the key research questions we need to address?

A team of computer scientists, neuroscientists, and data scientists at Vanderbilt are developing artificial intelligence (AI) algorithms that "look at" geometric patterns in tests of fluid intelligence such as Raven's Progressive Matrices, deciding which missing shapes would be most likely to fit in. These AI algorithms currently perform about as well as a human 17-year-old would, and they're only getting smarter, thanks to a study of the way certain people on the autism spectrum see the world.

Inspired by the writings of perhaps the most famous person on the spectrum, Temple Grandin, our team has been working on code that emulates the kinds of image-based thinking that Grandin used to design complicated farm equipment. The result is a form of AI that allows researchers to study a model of human cognition, determine how it problem-solves and then tweak it to perform better.

Most humans think in a combination of lots of different things. We think in words, we think in pictures, we think in smells and feelings. What we see in some people with autism is that they’re very much on the visual side. Temple Grandin talks about how she thinks really strongly with images, and certain kinds of language-based thinking are a little more difficult for her.

Our team of computer scientists and neuropsychologists is working to turn that system of thinking into code. Computers are programmed to solve various different types of human cognitive tests (such as Raven’s Progressive Matrices) that normally involve human subjects visually looking at a series of patterns. The new AI approach works only with "pictures" and pictorial manipulations, not symbolically or mathematically as in traditional AI approaches.

Major questions to be addressed include:

  • What are the varieties of ways in which humans think and approach problems?
  • What are the differences in approaches to problem solving, reasoning, ideation, and discovery employed by neurodiverse and neurotypical individuals?
  • How can these differences inform novel design of AI and other advanced computing approaches?
  • How can understanding these differences, and the development of computational tools based on them, support and improve quality of life for all people?
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