DNA

Sep 16 2022

Identity ecosystems are a central aspect of global digitalization; the principle of Do No Harm must be a policy priority and commitment

Identity is a data-rich resource that acts as a key to connect all levels of emerging digital ecosystems. All forms of ID carry some risk, but digital forms of ID, or “dematerialized ID,” cuts across all sectors and links copious data about individuals, their behaviors, financial status, associates, and potentially even political and religious views. Over time, distinct patterns emerge from the linked data and create new kinds of risks for individuals and groups. As the world becomes increasingly and intensely digitalized, we can expect challenges in the identity space to grow apace unless proactive attention is given to identifying and mitigating the current and future risks.

Mar 01 2022

WPF advises National Institutes of Health re: Genomic Data Sharing Policy

WPF filed comments to the National Institutes of Health (NIH) regarding its Genomic Data Sharing Policy. WPF recognizes that NIH is attempting to create a reasonable standard. Nonetheless, WPF urged NIH to better “future proof” its genomic data sharing proposal, and in particular requested NIH to look further into key areas, including the impacts of “genomic big data” and the limits of deidentification.

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...
Report: From the Filing Cabinet to the Cloud: Updating the Privacy Act of 1974

This comprehensive report and proposed bill text is focused on the Privacy Act of 1974, an important and early Federal privacy law that applies to the government sector and some contractors. The Privacy Act was written for the 1970s information era -- an era that was characterized by the use of mainframe computers and filing cabinets. Today's digital information era looks much different than the '70s: smart phones are smarter than the old mainframes, and documents are now routinely digitized and stored and perhaps even analyzed in the cloud, among many other changes. The report focuses on why the Privacy Act needs an update that will bring it into this century, and how that could look and work. This work was written by Robert Gellman, and informed by a two-year multi-stakeholder process.