This week, the Future of Privacy Forum (FPF) sent a letter to the Senate Homeland, Security & Governmental Affairs Committee in advance of today’s hearing “Examining State and Federal Recommendations for Enhancing School Safety Against Targeted Violence.”
On Friday, June 14, FPF submitted a letter to the New York State Assembly and Senate supporting a well-crafted moratorium on facial recognition systems for security uses in public schools.
Personal data – used lawfully, fairly, and transparently – is central to helping organizations achieve their missions. Today, Boards of Directors, CEOs, policymakers, and others need to understand the wide range of data inputs, the broad scope of risks and benefits, and how privacy and ethics are at the center of an organization’s ability to fulfill […]
Connected technologies and always-on data flows are helping make today’s cities and communities more livable, productive, and equitable. At the same time, these technologies raise concerns about individual privacy, autonomy, freedom of choice, and institutional discrimination. How do we leverage the benefits of a data-rich society while giving members of our community the confidence of […]
Digital Data Flows Masterclass is a year-long educational program designed for regulators, policymakers, and staff seeking to better understand the data-driven technologies at the forefront of data protection law & policy. The program will feature experts on machine learning, biometrics, connected cars, facial recognition, online advertising, encryption, and other emerging technologies. Sign up to receive email […]
Today, FPF announces the release of The Privacy Expert’s Guide to AI and Machine Learning. This guide explains the technological basics of AI and ML systems at a level of understanding useful for non-programmers, and addresses certain privacy challenges associated with the implementation of new and existing ML-based products and services.
These resources will help businesses and policymakers better understand and evaluate the growing use of face-based biometric technology systems when used for consumer applications. Facial recognition technology can help users organize and label photos, improve online services for visually impaired users, and help stores and stadiums better serve customers. At the same time, the technology often involves the collection and use of sensitive biometric data, requiring careful assessment of the data protection issues raised. Understanding the technology and building trust are necessary to maximize the benefits and minimize the risks.
The Best Practices provide a policy framework for the collection, protection, sharing, and use of Genetic Data generated by consumer genetic testing services. These services are commonly offered to consumers for testing and interpretation related to ancestry, health, nutrition, wellness, genetic relatedness, lifestyle, and other purposes.
John Verdi, the Future of Privacy Forum’s Vice President of Policy, testified today before the Federal Commission on Student Safety meeting, “Curating a Healthier & Safer Approach: Issues of Mental Health and Counseling for Our Young.”
This article examines the potential for bias and discrimination in automated algorithmic decision-making. As a group of commentators recently asserted, “[t]he accountability mechanisms and legal standards that govern such decision processes have not kept pace with technology.” Yet this article rejects an approach that depicts every algorithmic process as a “black box” that is inevitably plagued by bias and potential injustice.