The Playbook: Data Sharing for Research Report & Infographic
The Playbook: Data Sharing for Research is an FPF report on the best practices for instituting research data-sharing programs between corporations and research institutions. FPF also developed a summary of recommendations from the full report as well as an infographic on The Value of Responsible Data Sharing for Research. The playbook addresses vital steps for data […]
Privacy Metrics Report
FPF convened policy, academic, and industry privacy experts to discuss privacy metrics and their benefits, and published a report based on their discussions. Through these discussions, we learned that beyond demonstrating compliance, privacy metrics have emerged as a key measure to improve privacy program performance and maturity in terms of customer trust, risk mitigation, and […]
Nothing to Hide: Tools for Talking (and Listening) About Data Privacy for Integrated Data Systems Report
Data-driven and evidence-based social policy innovation can help governments serve communities better, smarter, and faster. Integrated Data Systems (IDS) use data that government agencies routinely collect in the normal course of delivering public services to shape local policy and practice. They can use data to evaluate the effectiveness of new initiatives or bridge gaps between public services and community providers.
Communicating about Data Privacy and Security Report
The ADRF Network is an evolving grassroots effort among researchers and organizations who are seeking to collaborate around improving access to and promoting the ethical use of administrative data in social science research. As supporters of evidence-based policymaking and research, FPF has been an integral part of the Network since its launch and has chaired the network’s Data Privacy and Security Working Group since November 2017.
Unfairness By Algorithm: Distilling the Harms of Automated Decision-Making Report & Infographic
Analysis of personal data can be used to improve services, advance research, and combat discrimination. However, such analysis can also create valid concerns about differential treatment of individuals or harmful impacts on vulnerable communities. These concerns can be amplified when automated decision-making uses sensitive data (such as race, gender, or familial status), impacts protected classes, or affects individuals’ eligibility for housing, employment, or other core services. When seeking to identify harms, it is important to appreciate the context of interactions between individuals, companies, and governments—including the benefits provided by automated decision-making frameworks, and the fallibility of human decision-making.
Understanding Corporate Data Sharing Decisions: Practices, Challenges, and Opportunities for Sharing Corporate Data with Researchers Report
Today, the Future of Privacy Forum released a new study, Understanding Corporate Data Sharing Decisions: Practices, Challenges, and Opportunities for Sharing Corporate Data with Researchers. In this report, we aim to contribute to the literature by seeking the “ground truth” from the corporate sector about the challenges they encounter when they consider making data available for academic research. We hope that the impressions and insights gained from this first look at the issue will help formulate further research questions, inform the dialogue between key stakeholders, and identify constructive next steps and areas for further action and investment.
Understanding Corporate Data Sharing Decisions: Practices, Challenges, and Opportunities for Sharing Corporate Data with Researchers Report
Washington, DC – Today, the Future of Privacy Forum released a new study, Understanding Corporate Data Sharing Decisions: Practices, Challenges, and Opportunities for Sharing Corporate Data with Researchers. In this report, FPF reveals findings from research and interviews with experts in the academic and industry communities. Three main areas are discussed: 1) The extent to which leading companies make data available to support published research that contributes to public knowledge; 2) Why and how companies share data for academic research; and 3) The risks companies perceive to be associated with such sharing, as well as their strategies for mitigating those risks.