可信AI治理框架探索与实践

doi:10.11959/j.issn.2096-0271.2022036

Abstract

Abstract:

Artificial intelligence (AI) has further improved the automation of information systems, however, some issues have been exposed during its large-scale application, such as data security, privacy protection, and fair ethics.To solve these issues and promote the transition of AI from available systems to trusted systems, the T-DACM trusted AI governance framework was proposed to improve the credibility of AI from the four levels of data, algorithm, calculation, and management.Different components were designed to solve specific issues such as data security, model security, privacy protection, model black box, fairness, accountability, and traceability.T-DACM practice case provides a demonstration of the trusted AI governance framework for the industry and provides a certain reference for subsequent product research and development based on the trusted AI governance framework.

Key words: trusted AI, governance framework, AI ethics and fairness, AI interpretability, AI supervision

CLC Number:

TP311.13

Zhengxun XIA, Jianfei TANG, Shengmei LUO, Yan ZHANG. Exploration and practice of trusted AI governance framework[J]. Big Data Research, 2022, 8(4): 145-164.

Figures/Tables 8

References 75

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