Randy Cantz is a Washington, DC-based technology policy professional specializing in AI governance, privacy law, and emerging technology regulation. He currently serves as a Policy Associate at Freedom Technologies, where he consults with federal government clients on spectrum policy, telecommunications law, and AI policy developments.

Prior to Freedom Technologies, Randy worked at the Future of Privacy Forum as a Policy Intern for Ethics and Data Sharing, where he conducted original research on emerging technologies, policies, laws, and regulations, including a published blog post on international neuroprivacy regulation in Latin America and a working group call with Dr. Yoel Roth, former head of Trust and Safety at Twitter, on mitigating the harms of misinformation and disinformation in research. He also supported over 400 corporate members navigating complex compliance challenges across GDPR, CCPA, and HIPAA as they applied to emerging technologies including AI, biometrics, and virtual reality.

At Georgetown, Randy researched digital deception and cybersecurity governance for Dr. Laura DeNardis at the Center for Digital Ethics, and served as a Policy Fellow with the Responsible AI Network studying algorithmic accountability, AI safety frameworks, and responsible AI governance. Earlier, at UC Berkeley’s Citizen Clinic in the Center for Long-Term Cybersecurity, he assessed cybersecurity threats to organizations specializing in open-source investigations, and provided research assistance to Professor James Rule on his book Taking Privacy Seriously.

Randy holds a Master of Arts in Communication, Culture, and Technology from Georgetown University, with a focus on privacy law, digital ethics, and AI governance, and a Bachelor of Arts in History with a minor in Public Policy from UC Berkeley, where he graduated Phi Beta Kappa and with high honors.

Fueled by the conviction that privacy is one of the defining human rights of our time, his current research interest focuses on neuroprivacy, the emerging legal and governance challenges posed by neurotechnology and AI systems trained on neural data, an area he believes represents one of the most consequential and underexplored frontiers in technology policy today.