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, artists, and activists, this paper explores various epistemic bases from which AI ethics is 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 scholarly authority, automation and quantification and achieved some legitimacy, while those based on richly embodied and situated lived experience have not. This paper draws the works of feminist Anthropology and Science and Technology Studies (STS) scholars Diana Forsythe and Lucy Suchman together with the works of postcolonial feminist theorist Sara Ahmed and Black feminist theorist Kristie Dotson to examine the implications of dominant AI ethics practices. I argue that by entrenching the epistemic power of quantification, dominant AI ethics practices risk legitimizing AI ethics as a project in equal and opposite measure to the extent that they delegitimize and marginalize embodied and lived experiences as legitimate parts of the same project. In response, I propose and sketch the idea of humble technical practices: quantified or technical practices which specifically seek to make their epistemic limits clear, with a view to flattening hierarchies of epistemic power.

翻译：什么构成合法的AI伦理劳动，进而，AI伦理主张在何种认识论基础上获得合法性？基于对包括研究人员、开发者、开源贡献者、艺术家和活动家在内的75位技术从业者的访谈，本文探讨了实践AI伦理的各种认识论基础。在外部将AI伦理视为"进步"障碍的批评背景下，我展示了部分AI伦理实践如何借助学术权威、自动化和量化方式获得一定合法性，而那些基于丰富的具身化情境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戴安娜·福赛斯和露西·萨奇曼的著作，以及后殖民女性主义理论家萨拉·艾哈迈德和黑人女性主义理论家克里斯蒂·多森的研究，审视主流AI伦理实践的影响。我认为，通过强化量化的认识论权力，主流AI伦理实践存在这样的风险：其赋予AI伦理项目合法性的程度，恰恰与其将具身化生活经验排斥和边缘化于同一项目之外的程度成正比。作为回应，我提出并勾勒了"谦逊技术实践"的理念：这些量化或技术实践专门致力于明确揭示自身的认识论局限，以期消解认识论权力的等级结构。