人工智能风险分析技术研究进展

doi:10.11959/j.issn.2096-0271.2020005

Abstract

Abstract:

The predictions of the deep learning models are still uncertain and uninterpretable.As a result,their deployments bring unavoidable risk to business decision making.Firstly,the study on risk analysis was motivated,and the three desirable properties of risk analysis techniques were described:quantifiability,interpretability and learnability.Then the existing work on risk analysis was reviewed,and the newly proposed framework to enable quantifiable,interpretable and learnable risk analysis was introduced.Finally,the existing and potential applications of risk analysis,and its future research direction were discussed.

Key words: artificial intelligence, risk analysis, uncertainty, interpretability

CLC Number:

TP391

Qun CHEN, Zhaoqiang CHEN, Boyi HOU, Lijuan WANG, Yuchen LUO, Zhanhuai LI. Research progress on risk analysis for artificial intelligence[J]. Big Data Research, 2020, 6(1): 47-59.

Figures/Tables 5

References 31

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