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

TL;DR

This paper synthesizes literature and empirical data to analyze current participatory practices in AI design, aiming to guide more principled stakeholder engagement across AI and HCI communities.

Contribution

It introduces a conceptual framework for analyzing participatory approaches and provides empirical insights into current practices in AI stakeholder participation.

Findings

Current participatory practices are diverse and often lack a unified framework.

Empirical data reveals gaps and opportunities in stakeholder engagement methods.

The framework facilitates systematic analysis and improvement of participatory AI design.

Abstract

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.