大数据科学的因果解释性理论难题刍议

On the humble opinion of the Difficulties of Causal Explanatory Theory in Big Data Science

大数据的提倡者们认为,我们正处于一个认识论革命的过程中,主张替代因果分析和理论生成的现代方法论支配地位。安德森断言大数据意味着“理论终结-经验主义重生”和“因果性的消解”,这揭示了许多大数据辩论中的傲慢暗流。大数据经验主义的认识论虽然很有吸引力,但是它建立在错误思考基础之上,大数据不仅致力于相关性关系,而在实质上针对因果性知识,这些更迫切需要对于大数据和数据分析的认识论影响的更广泛的批判性思考,由此重申科学研究的基本原则的重要性,例如建立因果关系以及借鉴现有理论。

Advocates of Big Data assert that we are in the midst of an epistemological revolution,promising the displacement of the modernist methodological hegemony of causal analysis and theory generation.Anderson asserts that big data means“the end of theory-Empiricism reborn”and“the digestion of causation”,which reveals many arrogant undercurrents in many big data debates.Although the epistemology of large data empiricism is attractive,it is based on erroneous thinking,and big data is not only devoted to the relationship.In essence for causal knowledge,there is an urgent need for broader critical thinking of the epistemological influence of big data and data analysis,thereby reaffirming the importance of basic principles of scientific research,such as establishing causal relationships and drawing on existing theories.