Chevron Decision Will Impact Privacy and AI Regulations
The Supreme Court has issued a 6-3 decision in two long-awaited cases – Loper Bright Enterprises v. Raimondo and Relentless, Inc. v. Department of Commerce – overturning the legal doctrine of “Chevron deference.” While the decision will impact a wide range of federal rules, it is particularly salient for ongoing privacy, data protection, and artificial […]
AI Forward: FPF’s Annual DC Privacy Forum Explores Intersection of Privacy and AI
The Future of Privacy Forum (FPF) hosted its inaugural DC Privacy Forum: AI Forward on Wednesday, June 5th. Industry experts, policymakers, civil society, and academics explored the intersection of data, privacy, and AI. In Washington, DC’s southwest Waterfront at the InterContinental, participants joined in person for a full-day program consisting of keynote panels, AI talks, […]
FPF Develops Checklist & Guide to Help Schools Vet AI Tools for Legal Compliance
FPF’s Youth and Education team has developed a checklist and accompanying policy brief to help schools vet generative AI tools for compliance with student privacy laws. Vetting Generative AI Tools for Use in Schools is a crucial resource as the use of generative AI tools continues to increase in educational settings. It’s critical for school […]
Overcoming Hurdles to Effective Data Sharing for Researchers
In 2021, challenges faced by academics in accessing corporate data sets for research and the issues that companies were experiencing to make privacy-respecting research data available broke into the news. With its long history of research data sharing, FPF saw an opportunity to bring together leaders from the corporate, research, and policy communities for a conversation […]
Data Sharing … By Any Other Name
There are many different uses of the term “data sharing” to describe a relationship between parties who share data from one organization to another organization for a new purpose. Some uses of the term data sharing are related to academic and scientific research purposes, and some are related to transfer of data for commercial or government purposes. ..it is imperative that we are more precise which forms of sharing we are referencing so that the interests of the parties are adequately considered, and the various risks and benefits are appropriately contextualized and managed.
FPF Submits Feedback and Comments on UNICEF’s Draft Policy Guidance on AI for Children
Last week, FPF submitted feedback and comments to the United Nations Children’s Fund (UNICEF) on the Draft Policy Guidance on Artificial Intelligence (AI) for Children, which seeks “to promote children’s rights in government and private sector AI policies and practices, and to raise awareness of how AI systems can uphold or undermine children’s rights.” The […]
FPF Letter to NY State Legislature
On Friday, June 14, FPF submitted a letter to the New York State Assembly and Senate supporting a well-crafted moratorium on facial recognition systems for security uses in public schools.