Artificial intelligence is quietly shaping social structures and private lives. Although it promises parity and efficiency, its computational processes mirror biases of existing power even as often-proprietary data practices and cultural perceptions of computational magic obscure those influences. However, intersectionality—which foregrounds an analysis of institutional power and incorporates queer, feminist, and critical race theories—can help to rethink artificial intelligence. An intersectional framework can be used to analyze the biases and problems built into existing artificial intelligence, as well as to uncover alternative ethics from its counter-histories. This paper calls for the application of intersectional strategies to artificial intelligence at every level, from data to design to implementation, from technologist to user. Drawing on intersectional theories, the research argues these strategies are polyvocal, multimodal, and experimental—suggesting that community-focused and artistic practices can help imagine AI’s intersectional possibilities and help begin to address its biases.

中文翻译：

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交叉AI必不可少

人工智能正在悄悄地塑造着社会结构和私人生活。尽管它保证了奇偶性和效率，但是它的计算过程反映了现有能力的偏见，即使通常专有的数据实践和对计算魔术的文化理解也掩盖了这些影响。但是，交叉性是对制度力量进行分析的基础，并结合了酷儿，女权主义和批判性种族理论，可以帮助人们重新思考人工智能。交叉框架可用于分析现有人工智能中存在的偏见和问题，以及从其反历史中发现替代伦理。本文呼吁将交叉策略应用于从数据到设计到实施，从技术人员到用户的各个层次的人工智能。