Multidimensional reflections on using big data analytics for criminal trial factfinding
With the emergence of big data technology and its application in judicial proceedings,using big data analytics for factfinding has become an unavoidable topic for fact-finders,especially in the field of criminal proceedings.However,due to the application of big data technology in judicial proceedings,the way of factfinding has changed significantly.Moreover,the factfinding based on big data analytics would put criminal trials at risk.For example,the panoramic application of big data analytics would affect the trial and factfinding;The secret application of big data analytics would easily lead to algorithm black box,data dictatorship and algorithm hegemony;The formality of factfinding and incompatible data expression would affect the realization of big data functions;The relevancy analysis would face the risk of bias and failure;The factfinding would face the systemic risk in the difficulty in obtaining and proving full samples.In view of such situation,it is necessary to re-deconstruct the"crime reconstruction theory","case structure theory"and"mirror of evidence theory"involved in criminal trial factfinding,and improve these theories from the dimensions of the subject,the process,the application and the logic.As adhering to the people-oriented approach,the effectuation of visible justice and the application of big data analytics reports in judicial proceedings would be promoted,and the causation analysis based on relevance would be established.Accordingly,the scientific and accurate criminal trial factfinding can be guaranteed.
Big dataCriminal casesFactfindingPrincipleProblemMultidimensional reflections
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NSTL
万方数据
