Keywords:  Security Engineering and Design, Public Policy,

2020

Crafting Public Policy for Reinforcement Learning Applications

Thomas Gilbert, Postdoctoral Researcher, Cornell Tech Digital Life Initiative, Cornell University
Sarah Dean, PhD Student, Department of Electrical Engineering and Computer Sciences, UC Berkeley
Tom Zick, PhD Candidate, College of Letters & Science, UC Berkeley
McKane Andrus, Graduate Student Researcher, Berkeley Artificial Intelligence Research, UC Berkeley

A team of graduate students, Graduates for Engaged and Extended Scholarship around computing and Engineering (GEESE), will build on their prior CLTC-funded project and develop suggested interventions in the design, training, and deployment of reinforcement learning (RL) systems that can be integrated into social infrastructure. These deliverables will include a preliminary survey paper that specifies a landscape of possible medium-term outcomes, a purposeful convening of RL experts and policymakers to identify shared concerns, and a final research paper that proposes regulatory policies to ensure system accountability and sociotechnical safety. Throughout, GEESE will leverage its extensive experience facilitating cross-disciplinary discussion to integrate the perspectives of developers, policy makers, and the existential risk community around the medium-term trajectory of RL.