WPF testifying before US Senate Banking Committee

Pam Dixon, WPF Executive Director, is testifying before the US Senate Banking Committee today on the topic of privacy, the Fair Credit Reporting Act, data brokers, and predictive analytics. “I am pleased to have the opportunity to discuss our research and what we have documented about the privacy of Americans in a predictive analytics era,” said Dixon. “This is a vital topic that touches all of us in our daily lives, and can even influence our dreams for the future.” Dixon will be discussing new research, as well as The Scoring of America report in her testimony. The testimony will be before the full committee. United States Senate Committee on Banking, Housing and Urban Affairs Data Brokers and the Impact on Financial Data Privacy, Credit, Insurance, Employment, and Housing Tuesday June 11, 2019 10 am, Dirksen Senate Office Building 538 For video, and testimony, see the Committee page .

Posted June 11, 2019 in

Global Visualization of Countries with Data Privacy Laws, Treaties, or Conventions

Background and Methodology: The conceptualization and initial research for this...
New 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.
National IDs Around the World — Interactive map

About this Data Visualization: This interactive map displays the presence...