An IAPP article examines the difficulties of defining AI governance despite the widespread calls for comprehensive regulations. Although helpful definitions have emerged, defining AI remains challenging for technology experts and legal and policy professionals. IAPP AI Governance Center Fellow Uzma Chaudhry suggests that understanding the mechanics of AI algorithms is a more helpful approach to grasping the concept of AI governance. She explains that AI governance targets the life cycle of the AI system, from input to output, to address risks associated with each component of the algorithm. These risks include the black-box problem, data input risks, data processing risks, and output risks. Chaudhry emphasises that AI governance should be implemented throughout the life cycle of the system to ensure comprehensive AI regulation.
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