找出差距:人工智能,负责机构和脆弱性
Shannon Vallor1,2, Tillmann Vierkant1
1School of Philosophy, Psychology and Language Sciences University of Edinburgh, Edinburgh, Scotland.
Minds and machines
|June 10, 2024
概括
人工智能和自主系统 (AI/AS) 的责任差距不是由于知识或控制问题,而是脆弱性差距. 解决这种关系不对称性是可信的人工智能和人类代理的关键.
科学领域:
- 技术的哲学技术的哲学
- 认知科学 认知科学
- 人工智能伦理学 人工智能伦理学
背景情况:
- 责任差距是人工智能和自主系统 (AI/AS) 治理和信任的一个关键挑战.
- 传统观点将这种差距与认识 (知识) 和控制在道德责任方面的失败联系起来.
研究的目的:
- 重新评估对AI/AS.责任差距的传统理解.
- 探索认知科学对人类行动的见解如何能为AI/AS发展和治理提供信息.
- 为了确定AI/AS责任的新型脆弱性差距.
主要方法:
- 对道德责任概念的哲学分析.
- 整合了认知科学关于人类代理的发现.
- 研究人类与AI/AS之间的关系不对称性.
主要成果:
- 认识和控制条件对于理解AI/AS责任挑战是误导性的.
- 个人面临着与知识和控制相似的挑战.
- 对责任的工具主义观点,强调代理培养,为AI/AS整合提供了希望.
结论:
- 由于人类和AI/AS之间的关系脆弱性不对称,存在着一个显著的,研究不足的责任差距.
- 解决这种脆弱性差距对于开发可信赖的AI/AS至关重要.
- 维护负责任的人类代理的条件需要注意这种脆弱性差距.
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