On January 27th, the Trump Administration made headlines with a controversial move to dismiss three Democratic members of the Privacy and Civil Liberties Oversight Board (PCLOB), an independent agency responsible for ensuring transparency and accountability in U.S. surveillance practices. With the attempted removal of these members, including the Chair, the board now lacks a quorum and is unable to function effectively, leaving just one member behind. As the future of the board remains uncertain, it could take months for replacements to be appointed, leaving the agency non-operational for the foreseeable future.

On February 24th, two of the removed members filed a lawsuit in federal court, claiming their firing was illegal.

In this episode, Greg Nojeim, Senior Counsel and Director of CDT’s Security and Surveillance Project, joins us to discuss the ramifications of the Trump Administration’s actions, the legal battle ahead, and what this all means for the future of privacy and trans-Atlantic data flows.

In today’s episode, we dive into an often overlooked but incredibly important issue: content moderation in non-dominant languages, specifically Maghrebi Arabic dialects. Recently, CDT released a groundbreaking report titled "Moderating Maghrebi Arabic Content on Social Media," which explores the challenges, gaps, and opportunities in ensuring fair and effective moderation of Arabic content on social platforms.

To unpack these insights, we’ll be joined by two leading experts in the field: Mona Elswah, a researcher in digital rights and content moderation, and Fellow of the Content Moderation for Languages in the Global South Project at CDT; and Emna Mizouni, a Tunisian digital rights advocate, community leader, and founder-CEO of Digital Citizenship.

We’ll discuss the unique hurdles faced by Maghrebi Arabic speakers online, why it's critical for platforms to address these gaps, and what needs to change to make content moderation more inclusive and equitable for all users.

In today’s episode, we tackle a fascinating question: What happens when an AI system deployed by a company decides to "resign"—stopping its recommendations or restricting access to its outputs? Can such actions help mitigate reputational or legal risks for organizations? To help us explore this, we’re joined by Dr. Umang Bhatt, Assistant Professor and Faculty Fellow at the Center for Data Science at New York University, CDT Non-Resident Fellow, and co-author of the paper When Should Algorithms Resign?: A Proposal for AI Governance, which delves into this thought-provoking concept.

In this episode, we explore the vital topic of bias and equity in AI systems. Joining the conversation are two esteemed guests: Raffi Krikorian, Chief Technology Officer at the Emerson Collective, and Alexandra Givens, President and CEO of the Center for Democracy and Technology. Tune in as we unpack the challenges and opportunities in making AI more equitable for all.In this episode, we explore the vital topic of bias and equity in AI systems. Joining the conversation are two esteemed guests: Raffi Krikorian, Chief Technology Officer at the Emerson Collective, and Alexandra Givens, President and CEO of the Center for Democracy and Technology. Tune in as we unpack the challenges and opportunities in making AI more equitable for all.

AI chatbots have quickly taken the world by storm with more people than ever integrating them into their daily lives. Many are familiar with the big name chatbots that can write recipes as Shakespearean poems or summarize obscure topics. But one type of chatbot, AI romantic companions, are less known despite the fact that they fill an especially personal role for their users. For these users, the chatbot developers’ data privacy practices are critical, yet many lack mature privacy and security protocols, leaving users’ most vulnerable data, such as health details, unprotected.

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Here to talk about these AI companion companies’ data privacy practices are Jen Caltrider, Mozilla’s *Privacy Not Included Program Director, and Michal Luria, CDT’s own Research Fellow.

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.