Collaborative Approaches to AI Policymaking

Courtney Lang, Matthew Reisman, Laura Galindo

AI poses novel and complex challenges to existing legal frameworks, and deciding what appropriate, feasible, and balanced regulation should look like is not easy. Given the rapid advancement of new and emerging technologies and the difficulty of fully understanding and anticipating their effects, there is a need for effective policies to govern their development and use. However, new rules will be most effective when they’ve been developed in collaboration with multiple stakeholders from a variety of sectors. Policy prototyping, sandboxing, and design jams are all examples of innovative new ways to test effective ways to regulate and govern a complex technology such as AI. This panel brings together some of the pioneers in this field to share their learnings.

Courtney Lang, Senior Director of Policy, Trust, Data, and Technology, Information Technology Industry Council (ITI)
Matthew Reisman, Director of Privacy and Data Policy, Centre for Information Policy Leadership (CIPL)
Laura Galindo, Privacy Policy Manager, AI Policy and Governance, Meta

PDF Materials:

Readings:

• Open Loop website: www.openloop.org

• Current Open Loop Programs:

  • On the EU AI Act

  • On Privacy Enhancing Technologies in Uruguay

  • On Privacy Enhancing Technologies in Brazil

  • On human-centred AI in India 

  • On AI transparency and explainability in Mexico

• Open Loop Reports:

  • “AI Impact Assessment: A Policy Prototyping Experiment” (2021)

  • “AI Transparency and Explainability: A Policy Prototyping Experiment” (2022)

  • “Artificial Intelligence Act: A Policy Prototype Experiment” (2022)

  • “Towards an Experimental Governance Framework for Emerging Technologies. Chapter 1: Learning from the Past” (2022)

• Program launch blog post: Introducing Open Loop, a global program bridging tech and policy innovation