Designing Alien Artificial Intelligences
Programming Beyond the Limits of Human Knowledge and Reason
Director, Knowledge Lab
University of Chicago
About the Lecture
The wisdom of crowds hinges on the independence and diversity of their members’ information and approach. This lecture will explore the wisdom of scientific crowds for discovery and invention, showing how findings established by more distinct methods and researchers are much more likely to replicate, how a population of diverse small teams advances science more rapidly than large ones, and how diverse prior experiences are critical for punctuated advances.
Artificial Intelligence has typically been designed to substitute for human expertise rather than complement it, limiting its capacity for human benefit. This lecture will demonstrate how incorporating a wide distribution of human expertise into AI models allows design diversity that complements and corrects for collective human bias, generating “alien” hypotheses unlikely to be imagined or pursued without intervention. The lecture will describe how AIs developed with this approach are leading to advances in materials discovery, drug development and effective COVID-19 vaccines. The lecture will discuss how to design diverse human and artificial intelligence collectives that will expand our imaginations and reach past current limits – of both human and machine intelligence and insight.
About the Speaker
James Evans is Professor of Sociology, Faculty Director of Computational Social Science, and the Director of Knowledge Lab at the University of Chicago and the Santa Fe Institute.
James uses large-scale data, machine learning and generative models to understand how collectives think and what they know. His research involves inquiry into the emergence of ideas, shared patterns of reasoning, and processes of attention, communication, agreement, and certainty. Thinking and knowing collectives like science, Wikipedia and the Web as a whole involve complex networks of diverse human and machine intelligences, collaborating and competing to achieve overlapping aims. His work connects the interaction of these agents with the knowledge they produce and its value, both internally to them and externally. He also works to design artificial collective intelligences that draw on discovered principles in areas ranging from science and technology to entrepreneurship and civic discourse.
James is an author on numerous peer reviewed publications and technical reviews.
James earned a BA in Anthropology at Brigham Young University, and an MA and PhD at Stanford University.