Navigating AI Governance: A Pilot Experiment on How Regulatory Models and Entrepreneurial Decision-Making Shape Creativity

Artificial Intelligence (AI) offers significant developmental opportunities, but it also raises profound governance challenges, including opacity (“black-box” algorithms) and ethical failures. Although AI safety is widely recognised as a core priority, global agreement on governance frameworks remains limited, resulting in markedly different regulatory approaches across countries. This macro-level divergence in governance logic raises a central question: how do different governance regimes shape creativity in AI innovation, and do individual differences in decision-making logics amplify or dampen these effects? To address this question, we will employ an experimental design to generate rigorous evidence that can inform more adaptive and effective AI innovation policy. Using a comparative framework, the study will examine how regulatory intensity influences innovation outcomes and will identify principles that may generalise across contexts. The findings will provide practical guidance for policymakers seeking to design AI governance frameworks that move beyond one-size-fits-all regulation. This pilot will also inform the design of a future full-scale randomised controlled trial (RCT).

Key facts

Principal Investigator: Chen MEI
Co-PI: Dr Xiangming (Tommy) Tao
Affiliation: PhD Candidate, Shanghai University of Finance and Economics & University of Sussex Business School (incoming research visiting)