From Coded Bias to Existential Threat: Expert Frames and the Epistemic Politics of AI Governance

From Coded Bias to Existential Threat: Expert Frames and the Epistemic Politics of AI Governance

연구 분야: Artificial Intelligence

학회: AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

While the knowledge produced by experts has been widely recognized to play a salient role in shaping policy on technological issues, the interaction between AI expertise and the evolving AI governance landscape has received little attention thus far. To address this gap, the present paper leverages insights from STS and International Relations to explore how different expert communities have constructed AI as a governance problem. More specifically, it presents the preliminary results of a qualitative frame analysis of 90 policy documents published by experts from industry, civil society, and the research community. The analysis finds that AI expertise is a highly contested field, as experts not only disagree on why AI is problematic and what policies are required, but, more fundamentally, about which artifacts, ideas, and practices make up AI in the first place. The paper proposes that the epistemic disagreements concerning AI have political consequences, as they engender protracted ontological politics that jeopardize the development of effective governance interventions. Against this background, the findings raise critical questions about the prevailing tendency of governance interventions to target the elusive and contested object 'artificial intelligence.'