AI Governance Tools

WPF provides comments on U.S. AI Action Plan; urges support for NIST AISIC and advancing trustworthy metrology of AI governance tools

WPF provided comments to the U.S. National Science Foundation and the Office of Science and Technology Policy regarding its priorities for the U.S. AI Action Plan. WPF's comments focused on 4 key points, including the importance of supporting the NIST AI Safety Institute Consortium, and support for building a verifiable, repeatable evaluative environment for testing and measuring AI governance tools so as to foster trustworthy AI systems and ecosystems, inclusive of privacy.

Deputy director Kate Kaye leading roundtable discussion at GWU conference on ethical frameworks and guidelines for AI

WPF deputy director Kate Kaye will facilitate a roundtable discussion among academic scholars, industry representatives and others addressing concerns and considerations related to synthetic content and use of synthetic content governance tools. Kate will help guide the discussion during the Organizational Applications for Identifying and Tagging Synthetic Content roundtable. In ...

WPF Executive Director Pam Dixon to give talk about Modern Privacy in an AI Era live with Washington State Office of Privacy and Data Protection

WPF Executive Director Pam Dixon will be giving a rare, live one hour Q and A session with the Washington Office of Privacy and Data Protection (OPDP) , which was created by the state legislature in 2016. This will take place in celebration of International Privacy Week, 30 January 2025. ...

AI Governance on the Ground: Chile’s Social Security and Medical Insurance Agency Grapples with Balancing New Responsible AI Criteria and Vendor Cost

The minute decisions, measurements and methods embedded inside the tools used to govern AI systems directly affect whether policy implementations actually align with policy goals. The government of Chile’s experience using its AI bidding template, and questions inside the agency regarding how to weigh traditional tech procurement criteria such as vendor cost along with newer responsible AI criteria like discriminatory impacts, give a glimpse of the AI governance challenges happening on the ground today. The tensions the Chilean government is dealing with may be a sign of what other organizations around the world could encounter as they put their own responsible AI policies into practice and navigate the policy implications of AI-facilitated decision making.

AI Governance on the Ground: Canada's Algorithmic Impact Assessment Process and Algorithm has evolved

WPF’s “AI Governance on the Ground Series” highlights and expands on topics and issues from WPF’s Risky Analysis report and its survey of AI tools. In this first publication of the series, we highlight how Canadian government agencies are implementing AI governance and algorithmic transparency mechanisms across various agencies, including its employment and transportation agencies, its Department of Veterans Affairs, and the Royal Canadian Mounted Police, among others. The agencies have evaluated the automated systems they use according to the country’s Algorithmic Impact Assessment process, or AIA, and the assessment results are public. Designers of this assessment framework — required since the country’s Directive on Automated Decision-Making went into effect in April 2019 – have now re-evaluated the AIA, updating its criteria, requirements, and risk-level scoring algorithm along the way. WPF interviewed government officials as well as key Canadian end-users of the assessments to capture the full spectrum of how the AIA is working at the ground level.

Deputy director Kate Kaye attending ACM FAccT conference in Rio de Janeiro, Brazil

Deputy Director Kate Kaye is in Rio de Janeiro Brazil from 3-6 June to attend the leading conference on Artificial Intelligence and trustworthy AI in socio-technical systems, ACM's Fairness, Accountability, and Transparency (ACM FAccT). While at the conference, Kaye will be interviewing paper authors and leading AI experts for forthcoming WPF podcasts, and to inform additional work.

WPF advises NIST regarding synthetic content and data governance

WPF filed comments with the US National Institute of Standards and Technology regarding its draft governance plan regarding synthetic content. WPF's comments focused on 7 recommendationsWPF's comments focused on 7 recommendations ranging from technical to policy issues. One overarching recommendation was that NIST ensure that human rights were attended to in all of its plans. Additional recommendations include requesting that NIST attend to the risks of digital exhaust in metadata, ensure that biometric data is included in the guidance, among other recommendations.

WPF announces participation in the National Institute of Standards and Technology (NIST) AI Safety Institute Consortium (AISIC)

The World Privacy Forum is pleased to announce that it has joined more than 200 of the nation’s leading artificial intelligence (AI) stakeholders to participate in a Department of Commerce initiative to support the development and deployment of trustworthy and safe AI. Established by the Department of Commerce’s National Institute of Standards and Technology (NIST) in February 2024, the U.S. AI Safety Institute Consortium (AISIC) brings together AI creators and users, academics, government and industry researchers, and civil society organizations to meet this mission.

WPF Comments to OMB regarding AI and Privacy Impact Assessments

The World Privacy Forum has filed detailed comments to the U.S. Office of Management and Budget (OMB) in response to its Request for Information on Privacy Impact Assessments. Specifically, OMB requested information about how the U.S. Federal government should update or adjust its requirements for Privacy Impact Assessments (PIAs) in regards to changes to data ecosystems brought about by Artificial Intelligence (AI). WPF provided substantive recommendations regarding administrative provisions of the Privacy Act, scalable automated AI governance tools for privacy and trustworthy AI, ensuring nimble processes for privacy and AI assessments, and ensuring balanced, skillful socio-legal-technical decisionmaking.

Initial Analysis of the new U.S. governance for Federal Agency use of Artificial Intelligence, including biometrics

Today the Biden-Harris Administration published a Memorandum that sets forth how U.S. Federal Agencies and Executive Departments will govern their use of Artificial Intelligence. The OMB memorandum provides an extensive and in some ways surprising articulation of emergent guardrails around modern AI. There are many points of interest to discuss, but the most striking includes the thread of biometrics systems guidance throughout the memorandum and continuing on in the White House Fact Sheet and associated materials. Additionally, the articulation of minimum practices for safety -impacting and rights- impacting AI will likely become important touch points in regulatory discussions in the U.S. and elsewhere. The guidance represents a significant policy shift for the U.S. Federal government, particularly around biometrics.

WPF comments to OMB regarding its Draft Memorandum on establishing new Federal Agency requirements for uses of AI

In December 2023, WPF submitted detailed comments to the U.S. Office of Management and Budget regarding its Request for Comments on Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence Memorandum.  OMB published the request in the Federal Register on November 3, 2023. This particular Memorandum is of historic importance, as it articulates the establishment of new agency requirements in the areas of AI governance, innovation, and risk management, and would direct agencies to adopt specific minimum risk management practices for uses of AI that impact the rights and safety of the public.

Report: Risky Analysis: Assessing and Improving AI Governance Tools

We are pleased to announce the publication of a new WPF report, “Risky Analysis: Assessing and Improving AI Governance Tools.” This report sets out a definition of AI governance tools, documents why and how these tools are critically important for trustworthy AI, and where these tools are around the world. The report also documents problems in some AI governance tools themselves, and suggests pathways to improve AI governance tools and create an evaluative environment to measure their effectiveness. AI systems should not be deployed without simultaneously evaluating the potential adverse impacts of such systems and mitigating their risks, and most of the world agrees about the need to take precautions against the threats posed. The specific tools and techniques that exist to evaluate and measure AI systems for their inclusiveness, fairness, explainability, privacy, safety and other trustworthiness issues — called in the report collectively AI governance tools – can improve such issues. While some AI governance tools provide reassurance to the public and to regulators, the tools too often lack meaningful oversight and quality assessments. Incomplete or ineffective AI governance tools can create a false sense of confidence, cause unintended problems, and generally undermine the promise of AI systems. The report contains rich background details, use cases, potential solutions to the problems discussed in the report, and a global index of AI Governance Tools.