摘要
大数据要求人们改变对因果关系的追问,转而追求相关关系;要求人们改变对精确性的苛求,转而追求混杂性;行业专家及其专业知识的重要性都会因为统计学家和数据分析的出现而变低。这些说法虽然刻画了大数据时代的新特点和动向,但论证不够深入全面,可能会引起误解。其中,第一个论点涉及因果关系与相关关系,第二个论点涉及决定论和概率论,第三个论点涉及统计分析和意义理解。从哲学理路上考察上述论点,我们会发现,尽管大数据时代开辟了一条模糊地利用数据的途径,但如果没有通过理想型的理论对大数据中的相关关系的意义的理解,我们就不知道如何去应用这些相关关系。如果我们不考虑社会理论的价值观念和人生指导意义,而沉湎于预测和操控,就会存在被彻底物化的危险。数据库再大,也是依据已经积累的过去的资料来预测将来,而将来是开放的,所以决策和预测总是存在风险,因此,机器的决策永远不能够取代人的决策。
The Age of Big Data illustrates the changes brought about by big data through many vivid cases.As far as the thinking method is concerned,the author believes that big data requires people to change the inquiry into causality and pursue correlation instead;people are asked to change their demanding of accuracy and to pursue confounding;the importance of professional experts and their knowledge can be reduced by the presence of statisticians and data analysts.I think these statements,while charactering new features and trends in the era of big data,are not sufficiently thorough and may cause some misunderstanding.Among them,the first argument involves the causation and correlation;the second argument involves the determinism and the theory of probability;the third argument involves the statistical analysis and understanding of meaning.These are all philosophical questions.My essay tries to examine the above arguments from the perspective of social science methodology,with a view to making these problems more penetrating in philosophical reasoning.
出处
《社会科学》
CSSCI
北大核心
2018年第9期69-77,共9页
Journal of Social Sciences
基金
教育部哲学社会科学研究重大课题攻关项目"当代国外社会科学方法论新形态及中国化研究"(项目编号:17JZD041)的阶段性成果
关键词
大数据
因果关系
相关关系
统计分析
意义理解
Big Data
Causality
Correlation
Statistical Analysis
Understanding of Meaning