摘要
在大数据中,数据化使因果关系量化为变量之间的关系,在获得关系强度和正负性质的同时,丧失了原有的必然性和方向性。大数据的相关关系,进一步展开了因果概念的重新刻画:因果关系是对因素相互作用过程与其效应之间关联的描述;而相关关系所描述的则是因果派生关系。作为因果派生关系,相关关系根植于因果性;作为未进入相互作用过程凝固为因果关系的因素关系,相关关系提供了由因素创构结果的广阔空间,这正是数据物化的因果性根据;而作为因素分析,相关定量分析的因果派生依据则构成大数据分析的因果基础。大数据中因果关系的厘清,晓示了其深层哲学内涵。因素关系的未来空间凸显创构认识论,因果派生关系的全数据定量分析呈现量的整体把握,而因果关系从描述到创构则彰显哲学以满足人的需要为最终目的。
In big data,datamation quantifies causal relations into relations between variables.This represents a gain in relationship strength and positive and negative properties,but a loss in terms of inevitability and direction.Big data correlation goes further in that it redefines the concept of causality:causality is a description of the process of interaction between factors,and what these correlations describe is causal derivative relationships.As causal derivative relationships,correlation is rooted in causality;as factor relations that have not yet entered the causal interaction process among factors and become fixed into causal relationships,correlation provides substantial space for factors to produce results,which constitutes the causal basis of data materialization;and as factor analysis,the causal derivative basis for the relevant quantitative analyses builds up the causal foundation for big data analytics.Big data's clarification of causality reveals its underlying philosophical content.The future space of factor relationship highlights creative epistemology,the holistic grasp of quantities shown in total data quantitative analysis of causal derivative relationships.From description to creation,causal relationships highlight the fact that the ultimate purpose of philosophy is to meet human needs.
出处
《中国社会科学》
CSSCI
北大核心
2016年第5期22-42,204-205,共21页
Social Sciences in China
