Large Language and Multi-Modal Models (LLMs), through their exposure to massive collections of online text, audio, and images, learn the ability to reproduce the perspectives and styles of diverse social and cultural groups. This capability suggests a powerful potential for generative social science – the simulation of empirically realistic, socio-culturally situated human individuals and higher-order collectives, from teams and online discussions to cities, economies, and countries. Synthesizing recent research in artificial intelligence and computational social science, I outline an approach to simulate human perspectives and interactive behaviors that enable generative modeling of humans and human society and their implications for new social scientific understanding, insights, and institutions. Then I recursively explore how our understanding of humans and societies allows us to improve large models to become improved agents for not only social science, but AI services in general. This would involve overcoming LM atemporality, social acceptability bias, response uniformity, and poverty of sensory experience. I close with a discussion of the potential and ethical considerations for Generative Social Science and AI agents in the world.
James Evans is the Max Palevsky Professor of Sociology, Director of Knowledge Lab and Founding Faculty Co-Director of Chicago Center Computational Social Science at the University of Chicago, the Santa Fe Institute, and Google. Evans' research uses large-scale data, machine learning and generative models to understand how collectives of humans and machines think and what they (can) 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, and civilization as a whole 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 outlets from the Economist, Atlantic , and New York Times to Le Monde, El Pais, and Die Zeit.
Host: Prof Yongshun CAI, Head, Division of Social Science, HKUST
Prof Wen WANG, Assistant Professor, Division of Social Science, HKUST