【Scientific Research】Tang Shiping: The Future of Computational Social Science and Scientific Decision-making

Introduction

Executive summary: The development of computational social science brings the potential for change in complex decision-making. While expert knowledge and judgment will continue to be an important basis for decision-making, judgments based on objective data and calculations will have the potential to make decisions more scientific. There are two major technical paths in computational social science: one is machine learning and artificial intelligence technology based on "imitation" (imitate/mimic); The second is the Agent-Based Modeling (ABM) technique based on "simulate". An important direction in the future should be the combination of machine learning and ABM technology. According to this characteristic of computational social science, researchers need to go beyond the thinking of "big data computing" and adopt the thinking of "all-data computing", and establish different combinations of data requirements according to different problems to be solved, rather than letting the amount or source of data determine the research problem. In view of the positive role of computational social science in decision-making, China should make a difference in the "computational social science for decision-making".

Keywords: computational social science, imitation, simulation, all-data computing, complex decision-making

About author:Tang Shiping is a distinguished professor at the School of International Relations and Public Affairs, Fudan University, and director of the Center for Complex Decision Analysis.

Source: International Political Science, Issue 3, 2023

Typography | Zhao Shuhan

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