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Stakeholder groups have produced various guidelines on ethical Artificial Intelligence (AI) in recent years. However, translating principles into practice continues to be a massive challenge, as AI markets expand and AI risks are heightened. AI audits—or the process of investigating an algorithm against existing regulations and known harms—are emerging as a way of bridging the gap between principle and practice. This paper scans the landscape
