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AI Governance

Artificial Intelligence (AI) has become a crucial social concern, far beyond its technical roots, including calls for AI governance and the emergence of Critical AI Studies. AI governance includes AI policy, but it goes far beyond regulation. It includes a wide range of mechanisms such as international collaboration and frameworks, certifications and labels, ethics review boards and auditing, public engagement and stakeholder involvement, best practices, standard setting, and ethics guidelines. Salient issues are, for instance, algorithmic bias and discrimination, social risks of automated decision-making, and the danger of ignoring the dimensions of human labor, social inequality and existing political institutions in the context of the current AI hype. A sociotechnical perspective is therefore essential to an accurate understanding of the dynamics and challenges of contemporary AI and its governance initiatives.