Contextualizing the Kids Online Safety and Privacy Act: A Deep Dive into the Federal Kids Bill
Co-authored by Nick Alereza, FPF Policy Intern and student Boston University School of Law. With contributions from Jordan Francis. On July 30, 2024, the U.S. Senate passed the Kids Online Safety and Privacy Act (KOSPA) by a vote of 91-3. KOSPA is a legislative package that includes two bills that gained significant traction in the […]
FPF Training Program 2024 – Fundamentals of AI & Machine Learning (Topic Page)
Fundamentals of ai & machine learning FPF is pleased to offer one of our four AI courses: Fundamentals of AI & Machine Learning to you and your team. With the increasing awareness of AI, especially generative AI, machine learning and AI are presenting new challenges for data governance in companies ranging from online service providers […]
Repository for Privacy Enhancing Technologies (PETs)
FPF has long supported the use of technologies as well as research to help better understand what data protection and privacy opportunities and challenges they present. When used appropriately, privacy-enhancing technologies can mitigate individuals’ privacy risks while promoting fairness and enabling socially beneficial data use. Broad adoption of these technologies is only possible if they […]
Reflections on California’s Age-Appropriate Design Code in Advance of Oral Arguments
Co-authored with Isaiah Hinton, Policy Intern for the Youth and Education Team Update: On Wednesday, July 17th, the U.S. 9th Circuit Court of Appeals heard oral arguments for an appeal of the District Court’s preliminary injunction of the California Age-Appropriate Design Code Act (AADC). Judges Milan Smith Jr., Mark Bennett, and Anthony Johnstone appeared interested […]
NEW FPF REPORT: Confidential Computing and Privacy: Policy Implications of Trusted Execution Environments
Written by Judy Wang, FPF Communications Intern Today, the Future of Privacy Forum (FPF) published a paper on confidential computing, a privacy-enhancing technology (PET) that marks a significant shift in the trustworthiness and verifiability of data processing for the use cases it supports, including training and use of AI models. Confidential computing leverages two key […]