Artificial intelligence (AI) can reproduce and amplify the structural inequities faced by minoritized communities. Participatory AI has been proposed as a response, but participation typically starts after problem definitions and success criteria have been set, leaving limited room for minoritized communities to reshape what an AI system is for. We propose AI From the Margins (AIM): a methodological stance that articulates the conditions under which lived experiences of minoritized communities can be elicited, centered, and carried forward to inform participatory AI design. AIM is not a fixed protocol; it articulates a set of preconditions that can be enacted through different techniques in different settings. We applied AIM in a Dutch healthcare context in eight sessions with 13 women and non-binary people of color and five municipal policy workers, namely through (1) narrative elicitation using the Biographic Narrative Interpretive Method (BNIM); (2) co-constructed rule-making; (3) participants' determination of whether, where, and how AI should be involved; and (4) translating lived experience into AI policy through dialogue with policymakers. In their reflections on the sessions, participants described the engagement as substantive and called for its continuation, demonstrating how preparatory orientation fundamentally grounded in lived experience shapes what participatory AI design is for.

翻译：人工智能（AI）可能再现并扩大边缘化社区面临的系统性不平等。参与式AI被提出作为应对方案，但参与通常始于问题定义和成功标准设定之后，留给边缘化社区重塑AI系统目标的空间十分有限。我们提出“边缘之声AI”（AIM）这一方法论立场：阐明边缘化社区的切身经验如何被激发、聚焦并延续以指导参与式AI设计的条件。AIM并非固定协议，而是阐明一系列可通过不同情境下的不同技术加以实施的先决条件。我们在荷兰医疗健康场景中，通过八场会议对13名有色人种女性及非二元性别者、5名市政政策工作者应用了AIM，具体包括：（1）采用传记叙事解释法（BNIM）进行叙事激发；（2）共同构建规则制定；（3）由参与者决定AI是否、在何处以及如何介入；（4）通过与政策制定者的对话将切身经验转化为AI政策。在会议反馈中，参与者将这一参与过程描述为实质性参与，并呼吁其延续性，这展示了根本植根于切身经验的预备性引导如何重塑参与式AI设计的目标。