In the 21st Century, science is a team sport played by humans and computers, both. Social science in particular is in the midst of a transition from the qualitative study of small groups of people to the quantitative and computer-aided study of enormous data sets created by the interactions of machines and people. In this new ecology, wanting AI to act human makes no sense, but growing “alien” intelligences offers useful difference — and human beings find ourselves empowered to identify new questions no one thought to ask. We can direct our scientific inquiry into the blind spots that our algorithms find for us, and optimize for teams diverse enough to answer them. The cost is the conceit that complex systems can be fully understood and thus controlled — and this demands we move into a paradigm of care for both the artificial Others we create and human Others we engage as partners in discovery. This is the dawn of Social Computing: an age of daunting risks and dazzling rewards that promises to challenge what we think we know about what can be known, and how…
Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.
In this episode, I speak with SFI External Professor James Evans, Director of the University of Chicago’s Knowledge Lab, about his new work in, and journal of, social computing — how AI transforms the practice of scientific study and the study of scientific practice; what his research reveals about the importance of diversity in team-building and innovation; and what it means to accept our place beside machines in the pursuit of not just novel scientific insight, but true wisdom.
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