What counts as legitimate AI ethics labor, and consequently, what are the epistemic terms on which AI ethics claims are rendered legitimate? Based on 75 interviews with technologists including researchers, developers, open source contributors, and activists, this paper explores the various epistemic bases from which AI ethics is discussed and practiced. In the context of outside attacks on AI ethics as an impediment to ``progress,'' I show how some AI ethics practices have reached toward authority from automation and quantification, and achieved some legitimacy as a result, while those based on richly embodied and situated lived experience have not. This paper draws together the work of feminist Anthropology and Science and Technology Studies scholars Diana Forsythe and Lucy Suchman with the works of postcolonial feminist theorist Sara Ahmed and Black feminist theorist Kristie Dotson to examine the implications of dominant AI ethics practices. By entrenching the epistemic power of quantification, dominant AI ethics practices -- Model Cards and similar interventions -- risk legitimizing AI ethics as a project in equal and opposite measure to which they delegitimize and marginalize embodied and lived experiences as legitimate parts of the same project. In response, I propose\textit{ humble technical practices}: quantified or technical practices which specifically seek to make their epistemic limits clear in order to flatten hierarchies of epistemic power.

翻译：何为合法的AI伦理劳动？相应地，AI伦理主张赖以合法化的认知基础是什么？基于对包括研究人员、开发者、开源贡献者和活动家在内的75位技术人员的访谈，本文探讨了讨论和实践AI伦理的各种认知基础。在外部将AI伦理视为"进步"障碍的抨击背景下，我展示了部分AI伦理实践如何借助自动化和量化寻求权威并由此获得一定合法性，而基于丰富具身且情境化生活经验的实践则未能如此。本文结合女性主义人类学与科学技术研究学者Diana Forsythe与Lucy Suchman的著作，以及后殖民女性主义理论家Sara Ahmed和黑人女性主义理论家Kristie Dotson的思想，审视主流AI伦理实践的影响。通过强化量化的认知权力，主流AI伦理实践——Model Cards及类似干预措施——在将具身和生活经验边缘化并剥夺其作为同一合法性组成部分的同时，存在同等程度地使AI伦理自身作为项目合法化的风险。作为回应，我提出"谦逊的技术实践"：即有意识地阐明自身认知局限以消解认知权力层级结构的量化或技术性实践。