Introducing a Practice-based Compliance Framework for Addressing New Regulatory Challenges in the AI Field

By Mona Sloane (New York University) & Emanuel Moss (Data & Society Research Institute)

Over the past years, regulatory pressure on tech companies to identify and mitigate the adverse impact of AI systems has been steadily growing. In 2022, we can expect this pressure to grow even further with transnational, national, federal, and local AI regulation kicking in. Many of these regulatory frameworks target both the design and the use of AI systems, often with a sector focus. AI practitioners and regulators alike are in need of new approaches that allow them to effectively respond to these regulations, and to enforce them competently. In this contribution, we will map out a Practice-Based Compliance Framework (PCF) for identifying existing principles and practices that are already aligned with regulatory goals, that therefore can serve as anchor points for compliance and enforcement initiatives.

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