Privacy Enhancing Technologies (PETs) are crucial for safeguarding individual privacy while enabling socially beneficial research, data sharing, and advancements in sectors that collect or use sensitive data. As AI systems increasingly rely on vast amounts of data, PETs like differential privacy, homomorphic encryption, federated learning, zero-knowledge proofs, and even model contract clauses can help ensure that personal data remains confidential and secure. This is vital not only for protecting individual rights but also for earning and maintaining public trust in technologies that use data about people.
Ethically implementing PETs is also essential. PETs must be designed and deployed to protect marginalized groups and avoid practices that may appear to be privacy-preserving, but actually exploit sensitive data or undermine privacy. In addition, clear policy guidelines on the deployment of PETs are necessary to help make sound business cases for their use in industry. If PETs are ethically integrated into research and business practices, and if global regulators have an opportunity to support their appropriate deployment, there is enormous potential for increasing technological innovation and societal benefits while upholding privacy and public trust.
FPF supports the development of PETs, convenes experts from around the world to deploy best practices, and provides in-depth analysis of emerging technologies and their policy implications. FPF also leads the National Science Foundation and Department of Energy-funded Research Coordination Network for the use of PETs to advance socially beneficial data sharing and protect people’s privacy as data is increasingly used to train AI models. FPF also facilitates a Global PETs Network of regulators who are interested in the lawful and ethical implementation of these tools.
Connecting Experts to Make Privacy-Enhancing Tech and AI Work for Everyone
The Future of Privacy Forum (FPF) launched its Research Coordination Network (RCN) for Privacy-Preserving Data Sharing and Analytics on Tuesday, July 9th. The RCN supports the Biden-Harris Administration’s commitments to privacy, equity, and safety articulated in the administration’s Executive Order on Artificial Intelligence (AI). Industry experts, policymakers, civil society, and academics met to discuss the […]
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 […]
FPF Launches Effort to Advance Privacy-Enhancing Technologies in Support of AI Executive Order, Convenes Experts, and Meets With White House
FPF’s Research Coordination Network will support developing and deploying Privacy-Enhancing Technologies (PETs) for socially beneficial data sharing and analytics. JULY 9, 2024 — Today, the Future of Privacy Forum (FPF) is launching the Privacy-Enhancing Technologies (PETs) Research Coordination Network (RCN) with a virtual convening of diverse experts alongside a high-level, in-person workshop with key stakeholders […]
FPF Awarded NSF and DOE Grants to Advance White House Executive Order on Artificial Intelligence
The Future of Privacy Forum (FPF) has been awarded grants by the National Science Foundation (NSF) and the Department of Energy (DOE) to support FPF’s establishment of a Research Coordination Network (RCN) for Privacy-Preserving Data and Analytics. FPF’s work will support the development and deployment of Privacy Enhancing Technologies (PETs) for socially beneficial data sharing […]