Data Science/Computational Social Science Seminar: James Evans
Intelligence Technologies to Design Diversity for Sustained Innovation
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Abstract
The talk will feature this forthcoming Nature Communications article on science and technology driven by surprise (attached as a downloadable link here: Innovation v5R SHARE small.pdf), two short papers on socially-aware AI coming out as a duet in Nature Human Behaviour (here a preprint as https://arxiv.org/abs/2104.05188) and a longer paper on complex systems and entrepreneurship under review at ASQ.
For the curiosity of the audience, I will also allude to a number of other papers in my talk: an attached piece forthcoming at PNAS on automatically searching for social technologies, and a short piece under second review at JAMA about uncertainty in medical knowledge, as also the following recent or forthcoming papers about innovation across teams, fields and societies: cover article in Nature on team size and innovation, recent article in PNAS on team structure and innovation, another recent article in PNAS on field size and slowing innovation, recent article in Nature Machine Intelligence on predicting reproducible science, recent review essay on innovation and disruption, opening article for the IEEE Journal of Social Computing I recently launched on social computing, piece forthcoming at Brain & Behavioral Sciences, piece under second review at Nature about integrative and high-throughput experiments. This doesn't include work on large-scale cultural analytics in sociology and computer science that forms a background (e.g., ASR, AJS, Poetics, EMNLP).
Speaker bio
James Evans is the Max Palevksy Professor of Sociology, director of Knowledge Lab and the Institute for Trusted Intelligence in Society, and Founding Faculty Director of Computational Social Science at the University of Chicago and the Santa Fe Institute. Evans' research uses large-scale data, machine learning and generative models to understand how collectives think and what they know. This 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, the web, or modern commercial enterprises involve complex networks of diverse human and machine intelligences, collaborating and competing to achieve overlapping aims. Evans' work connects the interaction of these agents with the knowledge they produce and its value for themselves and the system. His work is supported by numerous federal agencies (NSF, NIH, DOD), foundations and philanthropies, has been published in Nature, Science, PNAS, and top social and computer science outlets, and has been covered by global news agencies from the Economist and New York Times to Le Monde and Die Zeit.