人类对人工智能系统的控制:从监督到团队合作
Andreas Tsamados1, Luciano Floridi2, Mariarosaria Taddeo1,3
1Oxford Internet Institute, University of Oxford, Oxford, UK.
概括
这项研究比较了人工智能系统的监督控制和人机合作. 它认为,理解人工智能控制作为多代理系统中的协作机构,比独家的人类监督更有效.
科学领域:
- 人工智能的人工智能
- 人与计算机的交互
- 认知科学 认知科学
背景情况:
- 人工智能系统,特别是基础模型,表现出非决定性行为.
- 确保有效的AI部署需要强大的人类控制机制.
- 对于先进的人工智能来说,现有的人类控制方法可能不足.
研究的目的:
- 审查和比较人工智能系统的监督人类控制和人机合作.
- 评估这些方法对控制基础模型的充分性.
- 为人工智能的人类控制提出一个改进的框架.
主要方法:
- 对人工智能中人类控制方法的文献综述.
- 监督控制与人机合作的概念分析.
- 检查来自国防和安全领域的案例研究.
主要成果:
- 监督控制和人机合作在人类和人工智能行为之间的操作互动方面有所不同.
- 基础模型对传统的控制范式提出了独特的挑战.
- 实际的例子凸显了在防务环境中人工智能的人类控制方面的困难.
结论:
- 人类对人工智能的控制更好地被概念化为在多代理系统中的协作机构.
- 对于复杂的,非决定性的AI来说,人类的独家监督效果不太好.
- 建议转向将人工智能控制理解为一个联合努力.
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