Privacy On The Ground

World Privacy Forum

Privacy On The Ground is where privacy meets real life. Discussions about privacy in relation to government policy, legal compliance, or tech can be complicated and inaccessible. But the meaning of privacy and how data use affects us in our real lives is anything but: It is contextual and tangible. That's what we aim for with Privacy on the Ground. In this podcast, you'll hear talks and stories that reflect what privacy means for real people and real lives. Privacy On The Ground is a production of World Privacy Forum, a nonpartisan 501c3 nonprofit public interest research organization. Find us online at www.WorldPrivacyForum.org.

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    Machine Unlearning Limitations and Demands with Arizona State University's Yezhou "YZ" Yang

    Machine Unlearning is a field of AI research gaining attention in the policy world. It's often discussed in the context of privacy, particularly in relation to the European Union's General Data Protection Regulation (GDPR) and the EU AI Act as well as the California Consumer Privacy Act (CCPA). At World Privacy Forum's tutorial at the Winter Conference on Applications of Computer Vision (WACV) in Tucson, Arizona in March 2026, we aimed to bridge gaps in understanding between the technical academic community, including machine unlearning researchers, and the AI governance, policy, and legal communities. In this episode you'll hear a chat with Dr. Yezhou "YZ" Yang, a tenured associate professor in computer science and engineering in the School of Computing and Augmented Intelligence at Arizona State University; Yang spoke at WPF's tutorial about machine unlearning for concept erasure. Topics discussed:  Why machine unlearning for concept erasure isn't just for privacy Benchmarks for testing the removal of data - or even the presence of a visual artist's style - from AI models Why Yang wants to see more inclusion of technical AI practitioners in the policy conversation Research discussed:  EraseFlow: Learning Concept Erasure Policies via GFlowNet-Driven Alignment R.A.C.E. : Robust Adversarial Concept Erasure for Secure Text-to-Image Diffusion Model WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Models Featured in this episode:
 Dr. Yezhou "YZ" Yang, tenured Associate Professor in Computer Science and Engineering in the School of Computing and Augmented Intelligence at Arizona State University Kate Kaye, Deputy Director of World Privacy Forum The Privacy on the Ground intro theme features music by Pangal. Episode music is by Maciej Sadowski.

    30 min
  2. Privacy, Identity and Trust in C2PA: An Explainer Series (Part 1)

    03/09/2025

    Privacy, Identity and Trust in C2PA: An Explainer Series (Part 1)

    If you're looking for an accessible overview of how C2PA works technically and how it relates to privacy, identity, and trust, this is it! Imagine a system that automatically generates detailed data showing where the digital images, videos and documents we encounter came from, who made them, how they have changed, who owns the rights to their use, and even whether AI was used in their creation. Some say C2PA (Coalition for Content Provenance and Authenticity) promises to be just that.  C2PA is a technical framework for connecting digital media content such as images and videos to data about the origins of and changes made to that content. But it is not just a "content labeling" system. C2PA is intended to provide signals for gauging trustworthiness of content, kind of like provenance documentation indicating the authenticity of an oil painting or showing how some ancient artifact changed hands over time. But how does C2PA really work? How does it relate to privacy, identity, and trust? And what could its use mean for our information and data ecosystem? It's too early to know whether C2PA will be one of those behind-the-scenes systems that shift the tectonic plates of our digital media ecosystem. But it's the right time to take a step back and assess what we do know about C2PA and what it could mean – not just for the future of digital information but for our connections to it. This episode of Privacy on the Ground features music by Liam Back and Speedtest. The Privacy on the Ground intro theme features music by Pangal.

    24 min

À propos

Privacy On The Ground is where privacy meets real life. Discussions about privacy in relation to government policy, legal compliance, or tech can be complicated and inaccessible. But the meaning of privacy and how data use affects us in our real lives is anything but: It is contextual and tangible. That's what we aim for with Privacy on the Ground. In this podcast, you'll hear talks and stories that reflect what privacy means for real people and real lives. Privacy On The Ground is a production of World Privacy Forum, a nonpartisan 501c3 nonprofit public interest research organization. Find us online at www.WorldPrivacyForum.org.