The “Neural Data” Goldilocks Problem: Defining “Neural Data” in U.S. State Privacy Laws
As of halfway through 2025, four U.S. states have enacted laws regarding “neural data” or “neurotechnology data.” These laws, all of which amend existing state privacy laws, signify growing lawmaker interest in regulating what’s being considered a distinct, particularly sensitive kind of data: information about people’s thoughts, feelings, and mental activity. Created in response to […]
The “Neural Data” Goldilocks Problem: Defining “Neural Data” in U.S. State Privacy Laws
Co-authored by Chris Victory, FPF Intern As of halfway through 2025, four U.S. states have enacted laws regarding “neural data” or “neurotechnology data.” These laws, all of which amend existing state privacy laws, signify growing lawmaker interest in regulating what’s being considered a distinct, particularly sensitive kind of data: information about people’s thoughts, feelings, and […]
FPF at PDP Week 2025: Generative AI, Digital Trust, and the Future of Cross-Border Data Transfers in APAC
Authors: Darren Ang Wei Cheng and James Jerin Akash (FPF APAC Interns) From July 7 to 10, 2025, the Future of Privacy Forum (FPF)’s Asia-Pacific (APAC) office was actively engaged in Singapore’s Personal Data Protection Week 2025 (PDP Week) – a week of events hosted by the Personal Data Protection Commission of Singapore (PDPC) at […]
Balancing Innovation and Oversight: Regulatory Sandboxes as a Tool for AI Governance
Thanks to Marlene Smith for her research contributions. As policymakers worldwide seek to support beneficial uses of artificial intelligence (AI), many are exploring the concept of “regulatory sandboxes.” Broadly speaking, regulatory sandboxes are legal oversight frameworks that offer participating organizations the opportunity to experiment with emerging technologies within a controlled environment, usually combining regulatory oversight […]
Practical Takeaways from FPF’s Privacy Enhancing Technologies Workshop
In April, the Future of Privacy Forum and the Mozilla Foundation hosted an all-day workshop with technology, legal, and policy experts to explore Privacy Enhancing Technologies (PETs). During the workshop, multiple companies presented technologies they developed and implemented to preserve individuals’ privacy. In addition, the participants discussed steps for broadening the adoption of these technologies […]
Privacy Enhancing Technologies Workshop Proceedings
On April 25, 2025, the Future of Privacy Forum and the Mozilla Foundation co-hosted a Privacy Enhancing Technologies (PETs) Workshop in Washington, DC, convening industry, academia, and civil society experts to explore practical applications of PETs. The workshop featured two leading-edge use cases: Mastercard’s cross-border fraud detection system using Fully Homomorphic Encryption (FHE), and Oblivious’s […]
PETs Use Case: Differential Privacy for End-of-Life Data
In this use case, Oblivious partnered with an insurance company to tackle a common tension between data privacy and utility: how to retain meaningful insights from personal data while complying with legal requirements to delete it. By applying Differential Privacy, the organization can preserve actuarial insights without violating global privacy laws, generating differentially private statistical […]
Use Case: Preventing Financial Fraud Across Different Jurisdictions with Fully Homomorphic Encryption
Mastercard’s use of Fully Homomorphic Encryption (FHE) demonstrates how Privacy Enhancing Technologies (PETs) can support fraud detection across borders without compromising sensitive data. In this use case, Mastercard collaborated with Singapore’s Infocomm Media Development Authority to pilot a system that allows encrypted International Bank Account Numbers (IBANs) to be checked for fraud risk without revealing […]
Data-Driven Pricing: Key Technologies, Business Practices, and Policy Implications
In the U.S., state lawmakers are seeking to regulate various pricing strategies that fall under the umbrella of “data-driven pricing”: practices that use personal and/or non-personal data to continuously inform decisions about the prices and products offered to consumers. Using a variety of terms—including “surveillance,” “algorithmic,” and “personalized” pricing—legislators are targeting a range of practices […]