社會學是對社會行動提供詮釋和反事實因果解釋的科學。社會學定量研究的因果性解釋,必須能夠作為預測社會現象的基礎。受到數據和算力限制,多年來社會學定量研究的主要取徑是通過統計檢驗實現關聯和因果分析,而無力進行預測。本文對"社會預測"這一概念的歷史脈絡進行梳理,闡述了通過機器學習方法實現社會預測的科學原理和當代路徑,并對社會預測進行了再定義。在此基礎上,本文進一步探討了社會預測的學術價值、治理價值和話語價值,并闡述了其作為定量社會研究前沿的范式突破意義。我們認為,利用機器學習實現社會預測,是中國社會學特別是計算社會學引領國際前沿的重要契機,對于加快構建中國特色哲學社會科學具有重要意義。

Sociology is a science concerning itself with interpretive understanding of social action as well as causal explanation. A causal explanation should be the foundation of prediction. For many years,constrained by data and computing power,quantitative research of social science has primarily focused on statistical test to analyze correlation and causality, leaving predictions largely ignored. By sorting out the historical context of"social prediction",this paper redefines this concept by introducing why and how machine learning can help prediction in a scientific way. This paper further summarizes the academic value and governance value of social prediction,and suggests that it be a potential breakthrough in contemporary social research paradigm.We believe,through machine learning,we can witness the advent of an era of paradigm shift from correlation,causality to social prediction,providing a rare opportunity for sociology in China to lead the international frontier of computational social sciences,and accelerating the construction of philosophy and social science with Chinese characteristics.