Stakeholder Participation for Responsible AI Development: Disconnects Between Guidance and Current Practice
This highlights a critical gap for AI practitioners and policymakers in aligning industry practices with responsible AI principles, though it is incremental in addressing implementation challenges.
The study examined the disconnect between stakeholder involvement (SHI) practices in commercial AI development and responsible AI (rAI) guidance, finding that current SHI is driven by commercial priorities and largely fails to contribute to rAI goals like redistributing power and anticipating risks.
Responsible AI (rAI) guidance increasingly promotes stakeholder involvement (SHI) during AI development. At the same time, SHI is already common in commercial software development, but with potentially different foci. This study clarifies the extent to which established SHI practices are able to contribute to rAI efforts as well as potential disconnects -- essential insights to inform and tailor future interventions that further shift industry practice towards rAI efforts. First, we analysed 56 rAI guidance documents to identify why SHI is recommended (i.e. its expected benefits for rAI) and uncovered goals such as redistributing power, improving socio-technical understandings, anticipating risks, and enhancing public oversight. To understand why and how SHI is currently practised in commercial settings, we then conducted an online survey (n=130) and semi-structured interviews (n=10) with AI practitioners. Our findings reveal that SHI in practice is primarily driven by commercial priorities (e.g. customer value, compliance) and several factors currently discourage more rAI-aligned SHI practices. This suggests that established SHI practices are largely not contributing to rAI efforts. To address this disconnect, we propose interventions and research opportunities to advance rAI development in practice.