大数据时代因果关系的重构及认识论价值

Reconstruction of Causality in the Era of Big Data and Epistemological Value

大数据时代最重要的认识变革就是由探究事物的因果关系转向关注相关关系。实际上,相关关系的挑战早在"休谟问题"和"量子理论"就已经开始,但它们并非要彻底否定因果关系,而是提出要重新刻画因果关系的历史重任。朱迪亚·珀尔首次重构"因果关系之梯",强调因果关系有三个不同层级即关联、干预和反事实,并对应三种认识能力即观察能力、行动能力和想象能力。相关关系只是因果关系的最低层级,人类要想改变世界和创构世界,就要迈上因果之梯的更高层级,呈现出人类的主动行动和对虚拟创构物的想象。大数据因果关系的重构意味着一场人类的认知革命,不仅意味着整体上实现创构认识论的发展,彰显个性化知识的价值,而且意味着强人工智能的可能性。

The most important cognitive change in the era of big data is the shift from exploring the causal relationship to focusing on the correlation relationship. In fact,the challenge of correlation has been started as early as"Hume problem"and"quantum theory". They are not to deny causality completely,but to put forward the historical task of redescribing causality.Pearl first reconstructs the"ladder of causality",emphasizing that causality has three different levels:correlation,intervention and counterfactual,and corresponding to three cognitive abilities, namely,seeing,doing,imagining. Correlation is only the lowest level of causality. To change the world and create it,humans need to step up to the higher level of causality,showing human initiative and imagination of virtual creations. The reconstruction of causality in big data means a revolution in human cognition,which not only means the development of creative epistemology on the whole,highlighting the value of personalized knowledge,but also means the possibility of strong artificial intelligence.