Taming The Golem: Challenges of Ethical Algorithmic Decision-Making
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.
The Top 10 (& Federal Actions): Student Privacy News (November 2017-February 2018)
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.
FPF Publishes Model Open Data Benefit-Risk Analysis
This Report first describes inherent privacy risks in an open data landscape, with an emphasis on potential harms related to re-identification, data quality, and fairness. To address these risks, the Report includes a Model Open Data Benefit-Risk Analysis (“Model Analysis”). The Model Analysis evaluates the types of data contained in a proposed open dataset, the potential benefits – and concomitant risks – of releasing the dataset publicly, and strategies for effective de-identification and risk mitigation.
From cross-border transfers to privacy engineering, check out all panels and events FPF will be a part of at CPDP2018
Computers Privacy and Data Protection conference (CPDP) kicks off this week in Brussels, and the theme this year is “The Internet of Bodies”. The conference will gather 400 speakers for 80 panels to set the stage for the privacy and data protection conversation in Europe for 2018. And this is such an important year for data protection – not only the General Data Protection Regulation becomes applicable in May, but also the text of the new ePrivacy Regulation will likely be finalized.
Privacy Scholarship Research Reporter: Issue 3, December 2017 – 2017 Privacy Papers for Policymakers Award Winners
Notes from FPF On December 12, 2017, FPF announced the winners of our 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. In this special issue of the Scholarship Reporter, you […]
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.
Privacy Papers 2017
The winners of the 2017 PPPM Award are: Artificial Intelligence Policy: A Primer and Roadmap by Ryan Calo, Associate Professor of Law, University of Washington Abstract: Talk of artificial intelligence is everywhere. People marvel at the capacity of machines to translate any language and master any game. Others condemn the use of secret algorithms to […]
Advisory Board Reviewers for PPPM 2017
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 protection authorities abroad. The Award showcases work that analyzes current and emerging privacy issues and proposes achievable short-term solutions […]
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 […]
FPF Welcomes New Team Members
The Future of Privacy Forum is delighted to welcome several new members to our team!