Resources

Conversational AI technologies are hyper-personalizing. Across sectors, companies are focused on offering personalized experiences that are tailored to users’ preferences, behaviors, and virtual and physical environments. These range from general purpose LLMs, to the rapidly growing market for LLM-powered AI companions, educational aides, and corporate assistants. There are clear trends among this overall focus: towards […]

On August 28th, FPF provided comments regarding draft regulations for implementing the New Jersey Data Privacy Act (“NJDPA”). FPF seeks to support balanced, informed public policy and equip regulators with the resources and tools needed to craft effective regulation. In response to the Agency’s public comment on the proposed rules, FPF recommends that the Division […]

The widespread adoption of artificial intelligence (AI) continues to impact societies and economies around the world. Policymakers worldwide have begun pushing for normative frameworks to regulate the design, deployment, and use of AI according to their specific ethical and legal standards. In Latin America, some countries have joined these efforts by introducing legislative proposals and […]

On July 17, 2025, the Future of Privacy Forum (FPF) hosted the second in a series of Technologist Roundtables with the goal of convening an open dialogue on complex technical questions that impact law and policy, and assisting global data protection and privacy policymakers in understanding the relevant technical basics of large language models (LLMs). […]

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 […]

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 […]

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 […]

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 […]

This Preview highlights key findings from FPF’s forthcoming report “2025 U.S. State AI Legislation: An Examination of State Approaches to AI,” which provides a data-driven snapshot of enacted and key AI bills affecting the private sector, organizes activity into distinct approaches, and helps stakeholders understand emerging trends and obligations. As AI technologies rapidly integrate into […]

Data-driven pricing: A set of practices that use personal and/or non-personal data to routinely inform decisions about the prices and products offered to consumers, often for the purpose of price personalization. State lawmakers in the U.S. are seeking to regulate various pricing strategies that fall under the umbrella of data-driven pricing, following the release in […]