建立和评估可信的人工智能:概述和研究挑战
Dominik Kowald1,2, Sebastian Scher1,3, Viktoria Pammer-Schindler1,2
1Know Center Research GmbH, Graz, Austria.
Frontiers in big data
|December 16, 2024
概括
本文综合了可信的人工智能 (AI) 原则,概述了负责的人工智能开发和部署的六个关键要求. 它解决了研究挑战,以确保人工智能系统以道德和有效的方式为社会带来好处.
科学领域:
- 计算机科学 计算机科学
- 伦理学 伦理学 伦理学
- 技术政策 技术政策
背景情况:
- 人工智能 (AI) 技术正在改变社会,需要专注于可靠的AI系统.
- 对人工智能的意想不到结果和滥用的担忧激起了关于人工智能的可信度的讨论.
研究的目的:
- 综合现有的可信的人工智能概念.
- 在学术和公共论坛中巩固对人工智能可信度的讨论.
- 为广大受众提供参考资料,并指导未来的研究.
主要方法:
- 综合现有的关于可信的人工智能的文献.
- 识别和定义六个核心AI可信度要求.
- 分析研究挑战,具体针对每个要求和总体问题.
主要成果:
- 确定了值得信赖的人工智能的六个关键要求:人类代理和监督,公平和非歧视,透明度和可解释性,稳定性和准确性,隐私和安全性以及问责制.
- 定义,评估方法和特定需求的研究挑战是每个方面详细的.
- 综合性的研究挑战包括跨学科的合作,概念的清晰度,上下文依赖性,系统动态和现实世界的验证.
结论:
- 为值得信赖的AI提出了巩固的框架,综合了不同的观点.
- 突出了关键的研究差距和发展负责任的人工智能的未来方向.
- 旨在作为研究人员,政策制定者和公众的基础参考.
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