Computer Says Maybe

The hosts reflect on the troubling impact of social media on mental health and exploitation of young users. They draw unsettling parallels between big tech and big tobacco, highlighting the need for accountability. Discussions emphasize the barriers to transparency in corporations and the vital role of whistleblowers. The challenges of regulating harmful speech on digital platforms are explored, along with the implications of Section 230. The conversation wraps up with the necessity for short-term tech policy improvements and a call for transparency in research.

Elizabeth Eagen, Deputy Director of the Citizens and Technology Lab at Cornell University, discusses the role of social scientists in legal contexts. She addresses the challenges they face in conveying research uncertainty and the need for collaboration with lawyers. The conversation explores the ethical implications of AI technologies, the requirement for transparency in tech regulation, and the importance of effective government communication. Eagen emphasizes how technology impacts society and highlights the urgency for legislative responses as tech evolves.

In this engaging discussion, Alexa Koenig, Co-Faculty Director at UC Berkeley's Human Rights Center, dives into the complexities of using digital evidence in courts. She explores the challenges posed by social media and the evolving nature of authenticating images and audio. Koenig also highlights the potential roles of social scientists as expert witnesses and how generative AI complicates evidence integrity. The conversation underscores the urgent need for collaboration between tech companies and the legal system in our digital era.

Meetali Jain, founder of the Tech Justice Law Project, dives deep into the intricate world of holding big tech accountable. She discusses how Section 230 shields platforms from liability and the legal chess moves required to challenge this. Jain emphasizes the critical role of whistleblowers in promoting transparency and explores the implications of the Digital Services Act. She draws parallels between tech design accountability and tobacco litigation, making a case for serious regulatory reforms to ensure safer online spaces.

Frances Haugen, a former data scientist at Meta, gained notoriety for her whistleblowing on the company's harmful practices affecting children. In her chat with Alix, she exposes the negligence behind social media design choices. The discussion delves into the consequences of her revelations, sparking crucial conversations on accountability and child safety online. Haugen raises pressing questions about age verification and the balance of encryption with user privacy, reflecting on the need for corporate responsibility in the tech industry.

Pratham Juneja, a PhD Candidate in Social Data Science at the Oxford Internet Institute, dives into the parallels between Big Tobacco and Big Tech. He discusses how tobacco's historical manipulation of public perception mirrors current tech practices. The conversation explores the challenges of securing legal accountability in technology, the vital role of independent research, and how both industries mislead the public for profit. Juneja emphasizes the importance of learning from past failures to prevent similar outcomes in today’s tech landscape.

In the Exhibit X series Alix and Prathm sink their fingernails into the tangled universe of litigation and Big Tech; how have the courts held Big Tech firms accountable for their various harms over the years? Is whistleblowing an effective mechanism for informing new regulations? What about a social media platform’s first amendment rights? So much to cover, so many episodes coming your way!

In part four of our FAccT deep dive, Alix joins Marta Ziosi and Dasha Pruss to discuss their paper “Evidence of What, for Whom? The Socially Contested Role of Algorithmic Bias in a Predictive Policing Tool”.In their paper they discuss how an erosion of public trust can lead to ‘any idea will do’ decisions, and often these lean on technology, such as predictive policing systems. One such tool is the Shot Spotter, a piece of audio surveillance tech designed to detect gunfire — a contentious system which has been sold both as a tool for police to surveil civilians, and as a tool for civilians to keep tabs on police. Can it really be both?Marta Ziosi is a Postdoctoral Researcher at the Oxford Martin AI Governance Initiative, where her research focuses on standards for frontier AI. She has worked for institutions such as DG CNECT at the European Commission, the Berkman Klein Centre for Internet & Society at Harvard University, The Montreal International Center of Expertise in Artificial Intelligence (CEIMIA) and The Future Society. Previously, Marta was a Ph.D. student and researcher on Algorithmic Bias and AI Policy at the Oxford Internet Institute. She is also the founder of AI for People, a non-profit organisation whose mission is to put technology at the service of people.  Marta holds a BSc in Mathematics and Philosophy from University College Maastricht. She also holds an MSc in Philosophy and Public Policy and an executive degree in Chinese Language and Culture for Business from the London School of Economics.Dasha Pruss is a 2023-2024 fellow at the Berkman Klein Center for Internet & Society and an Embedded EthiCS postdoctoral fellow at Harvard University. In fall 2024 she will be an assistant professor of philosophy and computer science at George Mason University. She received her PhD in History & Philosophy of Science from the University of Pittsburgh in May 2023, and holds a BSc in Computer Science from the University of Utah. She has also co-organized with Against Carceral Tech, an activist group working to ban facial recognition and predictive policing in the city of Pittsburgh.This episode is hosted by Alix Dunn. Our guests are   Marta Ziosi and Dasha PrussiFurther Reading Evidence of What, for Whom? The Socially Contested Role of Algorithmic Bias in a Predictive Policing Tool Refusing and Reusing Data by Catherine D’Ignazio

In this episode, we speak with Lara Groves and Jacob Metcalf  at the seventh annual FAccT conference in Rio de Janeiro.In part four of our FAccT deep dive, Alix joins Lara Groves and Jacob Metcalf  to discuss their paper “ Auditing Work: Exploring the New York City algorithmic bias audit regime”.Lara Groves is a Senior Researcher at the Ada Lovelace Institute. Her most recent project explored the role of third-party auditing regimes in AI governance. Lara has previously led research on the role of public participation in commercial AI labs, and on algorithmic impact assessments. Her research interests include practical and participatory approaches to algorithmic accountability and innovative policy solutions to challenges of governance.Before joining Ada, Lara worked as a tech and internet policy consultant, and has experience in research, public affairs and campaigns for think-tanks, political parties and advocacy groups. Lara has an MSc in Democracy from UCL.Jacob Metcalf, PhD, is a researcher at Data & Society, where he leads the AI on the Ground Initiative, and works on an NSF-funded multisite project, Pervasive Data Ethics for Computational Research (PERVADE). For this project, he studies how data ethics practices are emerging in environments that have not previously grappled with research ethics, such as industry, IRBs, and civil society organizations. His recent work has focused on the new organizational roles that have developed around AI ethics in tech companies.Jake’s consulting firm, Ethical Resolve, provides a range of ethics services, helping clients to make well-informed, consistent, actionable, and timely business decisions that reflect their values. He also serves as the Ethics Subgroup Chair for the IEEE P7000 Standard.This episode is hosted by Alix Dunn. Our guests are Lara Groves and Jacob Metcalf.Further ReadingLara Groves (Ada Lovelace Institute, UK), Jacob Metcalf (Data & Society Research Institute, USA), Alayna Kennedy (Independent researcher, USA), Briana Vecchione (Data & Society Research Institute, USA) and Andrew Strait (Ada Lovelace Institute, UK)- Auditing Work: Exploring the New York City algorithmic bias audit regime

In this episode, we speak with Nari Johnson and Sanika Moharana at this year’s FAccT conference in Rio de Janeiro.In part two of our FAccT deep dive, Alix joins Nari Johnson and Sanika Moharana to discuss their paper “The Fall of an Algorithm: Characterizing the Dynamics Toward Abandonment”.Nari Johnson is a third-year PhD student in Carnegie Mellon University's Machine Learning Department, where she is advised by Hoda Heidari. She graduated from Harvard in 2021 with a BA and MS in Computer Science, where she previously worked with Finale Doshi-Velez.Sanika Moharana is a second-year PhD student in Human Computer Interaction at Carnegie Mellon University. As an advocate for human-centered design and research, Sanika practices iterative ideation and prototyping for multimodal interactions and interfaces across intelligent systems, connected smart devices, IOT’s, AI experiences, and emerging technologies .Further Reading The Fall of an Algorithm: Characterizing the Dynamics Toward Abandonment