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[…] run AI models, both buyer and provider need to be aware of the data sources and datasets involved, as these factors could impact their liability. For effective use of generative AI products, the panelists agreed on the importance of establishing a governance framework within an organization. This includes having clear guidelines for the responsible […]

[…] for regulated entities to develop and maintain a consumer health data privacy policy that “clearly and conspicuously” makes a specific set of disclosures. The law defines a use-based range of “consumer health data” that applies to information that a regulated entity “uses to identify the past, present or future health status of the consumer,” […]

[…] minimization or complying with anonymization obligations. Panelists agreed that the need to define clear standards for anonymization is an important step for PETs adoption.  Relatedly, panelists discussed use cases where PETs can help with business development while preserving the privacy and utility of the data. For instance, in the food delivery service industry, panelists […]

[…] when a business has “actual knowledge or knowledge fairly implied on the basis of objective circumstances.”  This language is based on the FTC’s trade regulation rules, which use the “knowledge fairly implied” standard to determine if a company knew it violated a trade rule. While the FTC is experienced in using this standard, it […]

[…] bias, especially when it comes to AI decision-making systems; Greater clarity about how regulators apply data protection laws to information subjected to PETs safeguards could increase the use and effectiveness of Privacy Enhancing Tech; Analysis of existing PETs implementations can yield important insights into the opportunities and challenges of particular tech and approaches. Virtual […]

[…] interpret these online protections. Age Assurance Technologies: Legislators have proposed the need for using technology to either infer or verify a user’s age before allowing them to use certain services, including in some states social media or adult content.  You can read more about the knowledge standards of currently enacted laws in our blog […]

[…] 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 technologies: trusted execution environments and attestation services. The technology allows organizations […]

[…] to recognized frameworks such as the NIST Artificial Intelligence Risk Management Framework (NIST AI RMF).  Conduct Impact Assessments annually, which must include the system’s purpose and intended use cases, any known or reasonably foreseeable risks of algorithmic discrimination, risk mitigation steps taken, categories of data processed for system use, the system’s performance metrics, transparency […]

[…] (AI) and other key technologies.  FPF’s RCN will bring together a multi-stakeholder community of academic researchers, industry practitioners, policymakers, and others to identify key barriers to responsible use of PETs and opportunities for PETs to enable ethical data use and sharing. Some PETs offer new anonymization tools, while others enable collaborative analysis on privately-held […]

[…] ongoing efforts such as the FTC’s Commercial Surveillance and Data Security Rulemaking, updates to the Child Online Privacy Protection Act (COPPA), and inter-agency efforts to prevent the use of discriminatory automated systems in the housing market and workplace.  For the last forty years, the Chevron doctrine (Chevron v. NRDC) has provided an analytical framework […]