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Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and Stir"

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arxiv 2111.01122 v1 pith:BHC73776 submitted 2021-11-01 cs.AI cs.CYcs.HC

classification cs.AIcs.CYcs.HC
keywords designresearchempiricalparticipatorystakeholdersfindingsliteratureparticipation
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There is a growing consensus in HCI and AI research that the design of AI systems needs to engage and empower stakeholders who will be affected by AI. However, the manner in which stakeholders should participate in AI design is unclear. This workshop paper aims to ground what we dub a 'participatory turn' in AI design by synthesizing existing literature on participation and through empirical analysis of its current practices via a survey of recent published research and a dozen semi-structured interviews with AI researchers and practitioners. Based on our literature synthesis and empirical research, this paper presents a conceptual framework for analyzing participatory approaches to AI design and articulates a set of empirical findings that in ensemble detail out the contemporary landscape of participatory practice in AI design. These findings can help bootstrap a more principled discussion on how PD of AI should move forward across AI, HCI, and other research communities.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 22 citations worldwide. Full citation record

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    A systematic review of 202 papers shows equity is usually mentioned without definition and is studied through different, often unconnected approaches across HCI and fairness venues.

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