Deep Learning Meets Deep Democracy: Deliberative Governance and Responsible Innovation in Artificial Intelligence
Responsible innovation in artificial intelligence (AI) calls for public deliberation: well-informed “deep democratic” debate that involves actors from the public, private, and civil society sectors in joint efforts to critically address the goals and means of AI. Adopting such an approach constitute...
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Veröffentlicht in: | Business ethics quarterly 2023-01, Vol.33 (1), p.146-179 |
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description | Responsible innovation in artificial intelligence (AI) calls for public deliberation: well-informed “deep democratic” debate that involves actors from the public, private, and civil society sectors in joint efforts to critically address the goals and means of AI. Adopting such an approach constitutes a challenge, however, due to the opacity of AI and strong knowledge boundaries between experts and citizens. This undermines trust in AI and undercuts key conditions for deliberation. We approach this challenge as a problem of situating the knowledge of actors from the AI industry within a deliberative system. We develop a new framework of responsibilities for AI innovation as well as a deliberative governance approach for enacting these responsibilities. In elucidating this approach, we show how actors from the AI industry can most effectively engage with experts and nonexperts in different social venues to facilitate well-informed judgments on opaque AI systems and thus effectuate their democratic governance. |
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subjects | Algorithms Artificial intelligence Civil society Collaboration Corporate governance Decision making Deep learning Democracy Design specifications Epistemology Ethics Experts Governance Innovations Learning Social responsibility |
title | Deep Learning Meets Deep Democracy: Deliberative Governance and Responsible Innovation in Artificial Intelligence |
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