AI Governance encompasses the policies, frameworks, standards, and institutional mechanisms for overseeing the responsible development, deployment, and use of artificial intelligence technologies, including regulatory compliance, organisational accountability structures, risk-based assessment, algorithmic transparency requirements, and stakeholder engagement processes that balance innovation with societal protection.
Semantic Classification
Content
Key Characteristics
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Establishes oversight mechanisms and accountability structures
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Implements risk-based assessment and audit frameworks
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Defines roles and responsibilities across AI lifecycle
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Ensures compliance with regulatory requirements
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Facilitates stakeholder participation and public discourse
Overview
AI Governance encompasses the policies, frameworks, standards, and institutional mechanisms for overseeing the responsible development, deployment, and use of artificial intelligence technologies. This includes regulatory compliance (GDPR, AI Act), organizational policies for ethical AI, risk management protocols, accountability structures, and stakeholder engagement processes. AI governance addresses concerns around algorithmic transparency, human oversight, impact assessments, and the establishment of AI ethics boards. Effective governance balances innovation with risk mitigation, ensuring AI systems align with societal values and legal requirements.
Related Concepts
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References
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European Commission (2021). Proposal for a Regulation on Artificial Intelligence (AI Act).
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OECD (2019). Recommendation of the Council on Artificial Intelligence.
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Cath, C. et al. (2018). Governing artificial intelligence: ethical, legal and technical opportunities and challenges. Philosophical Transactions of the Royal Society A.