CSET Events

Privacy, Security, and Innovation – Friends Not Foes

New privacy-enhancing technologies for AI

On September 19, 2024, we hosted a discussion with CSET's Helen Toner, OpenMined's Andrew Trask, and Irina Bejan on how privacy-enhancing technology infrastructure supported better AI innovation.

Responsible AI development necessitates balancing the risks and rewards of open or closed-source development, respecting data privacy while promoting innovation, and supporting national security while protecting individual liberties.

CSET’s Foundational Research Grants program has provided support to the work of OpenMined, an organization developing novel privacy-enhancing technology infrastructure that helps researchers get answers from data without needing direct access to the data, potentially addressing many of these ongoing concerns. On September 19, 2024, we hosted a discussion with Andrew Trask and Irina Bejan of OpenMined and CSET’s Helen Toner on the implications of these technologies for AI innovation. The webinar featured an audience Q&A session.

Webinar Highlight

Final Recording

Participants

Helen Toner is the Director of Strategy and Foundational Research Grants at Georgetown’s Center for Security and Emerging Technology (CSET). She previously worked as a Senior Research Analyst at Open Philanthropy, where she advised policymakers and grantmakers on AI policy and strategy. Between working at Open Philanthropy and joining CSET, Helen lived in Beijing, studying the Chinese AI ecosystem as a Research Affiliate of Oxford University’s Center for the Governance of AI. Helen has written for Foreign Affairs and other outlets on the national security implications of AI and machine learning for China and the United States, as well as testifying before the U.S.-China Economic and Security Review Commission. Helen holds an MA in Security Studies from Georgetown, as well as a BSc in Chemical Engineering and a Diploma in Languages from the University of Melbourne.

Andrew Trask is the Founder and Executive Director of OpenMined, a non-profit and community of over 17,000 members (AI researchers, cryptographers, engineers, product managers, data scientists, etc.) dedicated to building open source software for facilitating safe access to non-public information. He is also a PhD candidate at Oxford, Term Member at the Council on Foreign Relations, Senior Research Scientist at DeepMind, founding member of the United Nations Privacy Enhancing Technology Lab, and author of three AI courses and an intro AI textbook, each of which has served 10,000+ students.

Irina Bejan is a Technical Product Manager at OpenMined, where she leads pilots demonstrating how institutions, companies and the research community can collaborate to govern and utilize non-public, sensitive data to drive new scientific advancements. Prior to this role, Irina completed her master’s degree in Machine Learning at Swiss Federal Institute of Technology Lausanne (EPFL). She has held engineering and research roles at Google and led non-profit initiatives to empower student founders at Founderful and bridge the gender gap in tech through her work with Girls Who Code.