AI From the Margins (AIM): Rethinking Participatory AI Design Through the Lived Experience of Minoritized Communities

2026-05-31 · Source: Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Social Sciences & Behavioral Studies, Emerging Technologies & Innovation · Depth: Expert, quick

Summary

AI From the Margins (AIM) is a methodological stance designed to integrate the lived experiences of minoritized communities into participatory AI design, addressing how AI can perpetuate structural inequities. Unlike typical participatory approaches that begin after problem definitions are set, AIM establishes preconditions for eliciting, centering, and carrying forward these experiences. It is not a fixed protocol but a framework for enactment through various techniques. AIM was applied in a Dutch healthcare context across eight sessions, engaging 13 women and non-binary people of color alongside five municipal policy workers. The process included narrative elicitation using the Biographic Narrative Interpretive Method (BNIM), co-constructed rule-making, participant-led decisions on AI involvement, and translating lived experience into AI policy through dialogue. Participants reported the engagement as substantive, highlighting how a preparatory orientation grounded in lived experience reshapes the purpose of participatory AI design.

Key takeaway

For AI project leads or policymakers designing systems for diverse communities, you should adopt a "preparatory orientation" like AIM. This means centering minoritized lived experiences before defining problems or success criteria, fundamentally reshaping AI's purpose. Implement narrative elicitation and co-constructed rule-making to ensure your AI initiatives genuinely address community needs and avoid perpetuating inequities.

Key insights

AI From the Margins (AIM) centers minoritized lived experiences early in participatory AI design to counter systemic inequities.

Principles

• AI can amplify structural inequities.
• Participatory AI needs early community input.
• Lived experience must define AI's purpose.

Method

AIM involves narrative elicitation (BNIM), co-constructed rule-making, participant-led AI involvement determination, and translating lived experience into AI policy via dialogue with policymakers.

In practice

• Use BNIM for narrative elicitation.
• Facilitate co-constructed rule-making.
• Engage policymakers in experience translation.

Topics

• Participatory AI Design
• Minoritized Communities
• Lived Experience
• AI Ethics
• Healthcare Policy
• BNIM

Best for: Research Scientist, AI Scientist, AI Ethicist, Policy Maker

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.