大数据 (Jan 2020)

Research progress on risk analysis for artificial intelligence

  • Qun CHEN,
  • Zhaoqiang CHEN,
  • Boyi HOU,
  • Lijuan WANG,
  • Yuchen LUO,
  • Zhanhuai LI

Journal volume & issue
Vol. 6
pp. 2020005 – 1

Abstract

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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.

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