负责的人工智能测量数据集用于对人工智能系统的伦理评估
Shalaleh Rismani1, Leah Davis2, Bonam Mingole3
1McGill University, Montréal, Canada. shalaleh.rismani@mail.mcgill.ca.
Scientific data
|December 20, 2025
概括
一个新的数据集整合了791个人工智能 (AI) 伦理原则的评估措施,如公平和透明度. 该资源有助于研究人员评估人工智能系统,并改善负责任的人工智能治理.
科学领域:
- 人工智能的人工智能
- 计算机科学 计算机科学
- 伦理学 伦理学 伦理学
背景情况:
- 人工智能 (AI) 系统的有效治理需要强有力的评估和监测.
- 全球努力正在建立人工智能道德原则,如治理公平,透明和隐私等.
- 对人工智能规范性质的现有措施往往是分散的,原则特定的或范围有限的.
研究的目的:
- 通过创建一个综合数据集来解决人工智能道德措施的分散问题.
- 为了使从业者能够探索和批判性地分析测量AI规范性质的当前方法.
主要方法:
- 提取了12067个数据点,涉及791个评估措施的11个道德原则.
- 从257个计算文献出版物 (2011-2023) 的数据库中编译数据.
- 包括措施的详细描述,AI系统特征和出版物元数据.
主要成果:
- 开发了负责任的人工智能措施数据集,这是一个全面的AI道德评估方法集合.
- 该数据集涵盖了11个关键的伦理原则,并包括广泛的元数据.
- 创建了一个交互式可视化工具,以提高数据的可用性和解释性.
结论:
- 负责人工智能措施数据集为了解人工智能道德评估提供了一个集中资源.
- 促进对计算领域如何衡量人工智能伦理的批判性分析.
- 通过改进的评估实践,支持推进有意义的AI治理.
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