AI auditing that targets system integration is emerging but fragmented, and can be categorized into inter-component, system-environment, and multi-system sites serving four audit functions.
Advancing AI Audits for Enhanced AI Governance
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abstract
As artificial intelligence (AI) is integrated into various services and systems in society, many companies and organizations have proposed AI principles, policies, and made the related commitments. Conversely, some have proposed the need for independent audits, arguing that the voluntary principles adopted by the developers and providers of AI services and systems insufficiently address risk. This policy recommendation summarizes the issues related to the auditing of AI services and systems and presents three recommendations for promoting AI auditing that contribute to sound AI governance. Recommendation1.Development of institutional design for AI audits. Recommendation2.Training human resources for AI audits. Recommendation3. Updating AI audits in accordance with technological progress. In this policy recommendation, AI is assumed to be that which recognizes and predicts data with the last chapter outlining how generative AI should be audited.
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cs.SE 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
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A Chain Is Only as Strong as Its Weakest Link: A Scoping Review of System Integration Audits in AI
AI auditing that targets system integration is emerging but fragmented, and can be categorized into inter-component, system-environment, and multi-system sites serving four audit functions.