在评估人工智能风险的复杂系统视角
Daniel Kondor1, Valerie Hafez2, Sudhang Shankar3
1Complexity Science Hub, Vienna, Austria.
概括
人工智能 (AI) 系统需要社会政治背景研究,以了解复杂的社会影响. 对人工智能的风险评估应采用复杂的系统方法,整合公众参与,以获得更好的结果.
科学领域:
- 社会技术系统 社会技术系统
- 人工智能伦理学 人工智能伦理学
- 公共政策 公共政策
背景情况:
- 了解人工智能 (AI) 与社会结构之间的复杂关系至关重要.
- 现有的风险评估框架可能无法完全捕捉到人工智能部署的复杂性.
- 人工智能发展的长期后果受到社会不平等和决策的反循环的影响.
研究的目的:
- 识别人工智能系统与社会之间相互作用的关键挑战.
- 倡导在AI的社会政治背景下研究AI.
- 为AI风险评估提出一个改进的框架.
主要方法:
- 对人工智能的社会政治背景及其新出现的结果的分析.
- 复杂系统视角应用于风险评估.
- 强调公众参与和参与过程.
主要成果:
- 由于复杂的相互作用,人工智能系统在风险评估中存在独特的挑战.
- 一个社会政治镜头对于欣赏各种AI结果至关重要.
- 目前的风险评估需要改进,以建模反循环和长期影响.
结论:
- 人工智能风险评估必须整合复杂的系统视角,包括短期和长期影响的模型.
- 增加公众参与和参与对于负责任的AI治理至关重要.
- 在AI的社会政治背景下研究AI是导航其社会整合的关键.
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