The process of making laws and policies is largely obsolete. To a great extent, this process is not based on empirical foundations nor conducted through scientific methodologies. Instead, it is mostly driven by intuition, media hype, guesswork, and politics. The traditional lawmaking process is also static and slow. It is resistant to technological contributions and evidence-based approaches. As a result, laws are released into society without being tested or assessed. Once released, they are incredibly difficult to change, even as technology continues to evolve rapidly. In contrast, technology is created through a continuous and iterative process of trial and error, with experimentation at its core. These two processes are fundamentally incompatible. This is especially problematic in the field of technology regulation, where laws and policies need to keep pace with rapidly evolving technologies like artificial intelligence (AI).
Experimental governance is emerging as a promising approach to provide that missing evidence, and to render policy and law making processes more empirical, data driven and evidence-based. Regulatory sandboxes, for example, provide a controlled environment for companies to test their AI products and services under regulatory supervision. These programs can foster a deeper understanding of the interplay between emerging AI technologies and the regulatory frameworks that will govern them.
In the Experimental Governance seminar, students will study and explore the application of experimental governance methodologies and approaches (like policy prototyping, testbeds, foresight, and AI-powered simulations) into existing or hypothetical tech policy and lawmaking processes. Students will have the opportunity to simulate the application of different experimental governance techniques in key areas (privacy and data protection, intellectual property, cybersecurity, content moderation, etc), and sectors (technology, education, transportation, etc) of their own choosing. The seminar is aimed at contributing to a much-needed cultural and procedural shift into how we technically go about proposing, drafting and enacting future tech laws and policies, rendering this process more empirical, evidence-based and future proof.
