CDT Tech Talks

More and more people turn to quantified health, achievement, and ability measures, such as fitness apps and economic measures of well-being every single day. As part of this trend, medicalized approaches to human health often describe people in terms of statistics and data, sometimes failing to capture more important details. In particular, the quantified approach falls short in describing the needs and rights of disabled people, as seen in lawsuits and case studies involving algorithmic decision-making about disability benefits. Here to talk about algorithmic decision-making and quantification in disability benefits in the United States and India are Vandana Chaudhry, Associate Professor in the Department of Social Work and Disability Studies at the City University of New York who focuses on disability and digital justice in the Global South, and Lydia X.Z. Brown, activist for disability justice, Director of Public Policy at the National Disability Institute, and CDT’s very own former policy counsel.

New internet-based technologies have boomed with unprecedented access to data and data management tools. While this has facilitated innovation, it has also left many personal users and companies alike with limited knowledge about the uses and potential harms of their data. Balancing innovation and data privacy often requires tailored approaches, which is what the National Institute of Standards and Technology, more commonly known as NIST, attempted to address with their now highly-relied upon voluntary Privacy Framework, which offers guidance for organizations to voluntarily implement to protect data privacy and security.

It’s a modern day reality that large social media platforms deliver political information to many citizens, making these companies’ policies for removing and blocking speech critical to politics and culture. Emergencies such as the January 6th attack on the U.S. Capitol and the genocide of the Rohingya people in Myanmar can be traced in part to misinformation and hate speech shared online via large social media platforms. The problem of how social media companies should create policies to govern these spaces makes them uniquely quasi-governmental, a role, still developing today.

Recently, legislative bodies across the United States have exploded as lawmakers in over 10 states introduced several closely related bills to tackle AI- systems and their impacts on various facets of society. From hiring practices to education, insurance, housing, lending, government services, and even criminal sentencing, the scope of these bills is vast and far-reaching and will likely have a rippling effect across the country. Here to talk about these systems and the decisions they are responsible for making. Grace Gedye, Policy Analyst for Consumer Reports, and Matt Scherer, Senior Policy Counsel for CDT.

In recent years, differential privacy has emerged as a promising solution for enhancing privacy protections in data processing systems. However, beneath its seemingly robust framework lie certain assumptions that, if left unquestioned, could inadvertently undermine its efficacy in safeguarding individual privacy. Here to discuss their recent papers on differential privacy is Rachel Cummings, Associate Professor of Industrial Engineering and Operations Research at Columbia University and CDT Non-Resident Fellow and Daniel Susser, Associate Professor for the Department of Information Science at Cornell University and CDT Non-Resident Fellow.