Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and Stir"
It addresses the need for more principled stakeholder engagement in AI design for researchers and practitioners, but is incremental as it builds on existing work without introducing new methods.
This paper tackles the problem of unclear stakeholder participation methods in AI design by synthesizing literature and conducting empirical research, resulting in a conceptual framework and findings that detail current practices to guide future discussions.
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.