FPF Launches Virtual Privacy Book Club
We are pleased to announce the launch of our Privacy Book Club! The FPF Privacy Book Club will provide members the opportunity to read a wide range of books — privacy, data, ethics, academic works, and other important data relevant issues — and have an open discussion of the selected literature.
AI and Machine Learning: Educational Resources
Content Areas Interactive Explanations and Courses News, Reports, and Other Media International Resources Books Interactive Explanations and Courses Google Machine Learning 101 – A comprehensive overview of AI and machine learning with numerous resources for additional research. Intro to Machine Learning – A detailed, video-based, interactive course into ML concepts. Prerequisites include strong algebra skills […]
PrivacyNews.TV
FPF uses Facebook Live to discuss timely topics. Watch some of our previous videos here and be sure to tune in live for our next discussion!
Mobile Platforms Address Data Privacy with 2018 Updates (iOS 12, Mojave, & Android P)
In light of recent debates over Facebook’s role in protecting users’ privacy against third-party app developers, many are recognizing the importance of mobile platforms in safeguarding user data. Apple emphasized privacy in its Worldwide Developers Conference (June 4-8, 2018), highlighting several privacy-related updates to the upcoming macOS and iOS 12. Google also made privacy a focus of their newest mobile operating system, Android P, with several key software updates that will restrict app developers’ access to data.
Future of Privacy Forum’s 2018 Annual Meeting Agenda
Monday, May 14 4:00-8:00 PM (Library) EVENT REGISTRATION Pick up your name tag and folder at the FPF table in the library (across the hall from the hotel check in desk). 8:00-10:00 PM (Middleburg Foyer & Terrace) BOOK TALK & DESSERT RECEPTION A discussion & book signing with Woodrow Hartzog, Professor of Law and Computer […]
Privacy Papers 2017: Spotlight on the Winning Authors
Today, FPF announced the winners of the 8th Annual Privacy Papers for Policymakers (PPPM) Award. This Award recognizes leading privacy scholarship that is relevant to policymakers in the United States Congress, at U.S. federal agencies, and for data protection authorities abroad.
Unfairness By Algorithm: Distilling the Harms of Automated Decision-Making
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.
The Top 10: Student Privacy News (October-November 2017)
The Future of Privacy Forum tracks student privacy news very closely, and shares relevant news stories with our newsletter subscribers. Approximately every month, we post “The Top 10,” a blog with our top student privacy stories.
Protected: K-12 Privacy Leaders Working Group Notes and Resources
There is no excerpt because this is a protected post.
Spotlight on PPPM Judges (2017)
In December, the Future of Privacy Forum will announce the winners of the 2017 Privacy Papers for Policymakers Award. Each year, FPF awards the Privacy Papers for Policymakers Award to the authors of leading privacy research and analytical work that is relevant to policymakers in the United States Congress, at U.S. federal agencies, and for data […]