Anticipatory regulatory instruments could be potentially important and impactful tools for regulators to anticipate risks arising from AI systems. They may also support development of regulatory capacity, knowledge, and stakeholder engagement. Regulatory sandboxes are the anticipatory instrument used as the focus of this work to empirically research their existing methodologies, design, and application. A comparative approach will be adopted to isolate the causal dimensions of different sandbox schemes, consider the influence of the regulatory systems, and test such analysis through empirical research. It is hoped that this research will support further understanding of the utility, and potential design of sandbox schemes for AI.
AI Governance, Regulation and Policy.
Science and Technology Studies (STS).
Socio-Legal Studies.
Data Protection Law.
AI Standards.
An interest in both the implementation and theory of public policy has underpinned Deborah’s career, she was previously a corporate projects lawyer, worked within industry and then developed her interest in social policy to research the role of technology within education through a master’s degree at Cambridge prior to joining ART-AI. Her research interests span AI governance, regulation, and digital policy.
Prof Hugh Lauder
Dr Julian Padget
