This paper presents a series of feminist epistemological concepts as tools for developing critical, more accountable, and contextualised approaches to machine learning systems design. Namely, we suggest that the methods of situated knowledges or situating, figurations or figuring, diffraction or diffracting, and critical fabulation or speculation can be productively actualised in the field of machine learning systems design. We also suggest that the meta-method for doing this actualisation requires not so much translation but transposition - a creative and critical adaptation to speak to machine learning contexts.

翻译：本文提出一系列女性主义认识论概念，作为开发更具批判性、更负责任且情境化的机器学习系统设计方法的工具。具体而言，我们建议将情境化知识或情境化、具象化或具象化、衍射或衍射以及批判性虚构或思辨的方法，有效地应用于机器学习系统设计领域。我们还提出，实现这一应用所需的元方法与其说是翻译，不如说是转置——一种创造性的批判性改编，以适应机器学习语境。