What ethical risks might occur when AI systems are used for human social needs like romance, companionship, or entertainment? Join the University of Cambridge’s Henry Shevlin for an exploration of the potential benefits and harms of social AI.

How is the regulation of digital technologies influenced by geopolitical competition? Join the University of Chicago’s Aziz Huq for a talk on the future of the governance of technology.

How can algorithms contribute to or reduce inequality? Join Rediet Abebe to explore how mathematics and computation can support more equitable outcomes in the public sphere.

How can AI systems better support public health planning and policy? Join SRI Faculty Affiliate Laura Rosella for insights on how AI and data are transforming public health.

Can LLMs or agents built on top of them spontaneously “go rogue"? Join SRI Chair Roger Grosse for a special in-person edition of the SRI Seminar Series.

How are online networks, VR, and generative AI transforming the human experience? Join SRI Faculty Affiliate Bree McEwan to explore how technology is impacting the ways we communicate today.

How can we build technical systems that are secure and trustworthy? Join renowned computer scientist Cynthia Dwork of Harvard University for a talk on her latest research.

Why do large language models “hallucinate” facts and what can be done to mitigate this phenomenon? Join OpenAI’s Adam Tauman Kalai to learn more about new approaches towards AI alignment and safety.

How can we better understand the role of public trust in digital media? Join the University of Sydney’s Terry Flew to explore new approaches towards questions of mediated trust.

Luciano Floridi is the founding director of the Digital Ethics Center at Yale University, where he is also a professor in the Cognitive Science Program. World-renowned as one of the most authoritative voices of contemporary philosophy, Floridi is a founding figure within the philosophy of information and one of the major interpreters of the digital revolution. He is deeply engaged with policy initiatives on the socio-ethical value and implications of digital technologies and collaborates closely on these topics with many governments and companies worldwide.

Ann Copestake is a professor of computational linguistics at the Department of Computer Science and Technology at the University of Cambridge. Her research involves developing computer models of human languages, including explores the development of semantic models compatible with broad-coverage computational processing, and establishing the performance of deep learning systems according to linguistic criteria.

Iason Gabriel is a staff research scientist at Google DeepMind whose work focuses on the ethics of artificial intelligence, including questions about AI value alignment, distributive justice, language ethics and human rights. Gabriel has contributed to several projects that promote responsible innovation in AI, including the creation of the ethics review process at NeurIPS.

Marlène Koffi is an assistant professor in economics at the University of Toronto, and a faculty affiliate at the National Bureau of Economics Research and the Schwartz Reisman Institute for Technology and Society. Koffi’s research interests are in the economics of innovation and science, and she is also interested in applying deep learning and artificial intelligence techniques for economics studies and public policies.

Rohan Alexander is an assistant professor at the University of Toronto, jointly appointed in the Faculty of Information and the Department of Statistical Sciences, assistant director of CANSSI Ontario, a faculty affiliate at the Schwartz Reisman Institute, and a co-lead of the Data Sciences Institute’s Thematic Program in Reproducibility. Alexander’s research investigates how to develop workflows that improve the trustworthiness of data science.

Vincent Conitzer is a professor of computer science at Carnegie Mellon University where he directs the Foundations of Cooperative AI Lab, head of technical AI engagement at the Institute for Ethics in AI, and a professor of computer science and philosophy at the University of Oxford. Conitzer works on artificial intelligence, including the intersections between AI and game theory, and AI and ethics, and explores how to determine the objectives AI systems should pursue.

Jon Kleinberg is a professor of computer science at Cornell University whose research focuses on issues at the interface of networks and information, with an emphasis on the social and information networks that underpin the web and other online media. In this talk, Kleinberg proposes a new method for optimizing user experience on online platforms based on an insight that users have inconsistent preferences, exploring new insights for interactions between design, behavioral science, and social media.

Norman Sadeh is a professor in the School of Computer Science at Carnegie Mellon University, director of CMU’s Mobile Commerce Laboratory and its e-Supply Chain Management Laboratory, and co-director of the MSIT Program in Privacy Engineering. Sadeh’s research focus is mobile and pervasive computing, cybersecurity, online privacy, user-oriented machine learning, and semantic web technologies, and he is well known for his seminal work in AI planning and scheduling, supply chain management, automated trading, and negotiation. In this talk, he will present his recent research exploring how to overcome privacy challenges associated with contemporary data collection practices, and will describe some practical solutions aimed at empowering people to regain control over their data.

Dylan Hadfield-Menell is an assistant professor at MIT’s Department of Electrical Engineering and Computer Science, and runs the Algorithmic Alignment Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. His research works to identify solutions to alignment problems that arise from groups of AI systems, principal-agent pairs such as human-robot teams, and societal oversight of machine learning systems.

Lynette H. Ong is a professor in the Department of Political Science and the Munk School of Global Affairs & Public Policy at the University of Toronto and the director of the Munk School China Initiative. Her research interests lie at the intersection of authoritarianism, contentious politics, and development. In this talk, she will examine how digital technologies have enabled new forms of control for autocratic governments to co-opt and repress dissent.

Elizabeth Joh is the Martin Luther King Jr. Professor of Law at UC Davis School of Law, and a leading expert on policing, privacy, and technology. In this talk, Joh will examine how advanced surveillance technologies used by modern police forces create new forms of knowledge that expand the capacities of policing, arguing that we must understand these new tools as “experiments on communities.”

Pinar Yildirim is an associate professor of marketing at the Wharton School and associate professor of economics at the University of Pennsylvania who studies media, technology, and information economics, with a focus on the applied economics of online platforms, and effects of technology and AI. In this talk, Yildirim will explore how automation has impacted the US labour market, demonstrating that robotization is contributing to a loss of average local labour market career values, and that these changes have repercussions for investment in public infrastructure and political affiliations.

Luke Stark is an assistant professor in the Faculty of Information & Media Studies at Western University who researches the ethical, historical, and social impacts of computational technologies, including how these tools mediate social and emotional expression, make inferences about people, and are reshaping our relationships to collective action, our selves, and each other.

Tawanna Dillahunt is an associate professor at the University of Michigan’s School of Information whose research spans human-computer interaction and ubiquitous computing fields, including environmental, economic, and social sustainability. Dillahunt investigates, designs, builds, enhances, and deploys innovative digital tools to solve real-world problems that support the needs of people from historically excluded groups.

Our weekly SRI Seminar Series welcomes Beth Simone Noveck, a professor at Northeastern University, where she directs the Burnes Center for Social Change and its partner projects, the GovLab, and InnovateUS. Noveck’s work focuses on using AI to reimagine participatory democracy and strengthen governance, and she has spent her career helping institutions incorporate more participatory and open ways of working.

Arvind Narayanan is a professor of computer science at Princeton University and the director of the Center for Information Technology Policy. Narayanan led the Princeton Web Transparency and Accountability Project to uncover how companies collect and use personal information, and his work was among the first to show how machine learning reflects cultural stereotypes.

Regina Rini is an associate professor of philosophy at York University, and a Canada Research Chair in Social and Moral Cognition. Rini teaches and writes on a number of topics at the intersection of normative theory and social science, with a focus on the relevance of cognitive science to moral theory.

Marzieh Fadaee is a senior research scientist at Cohere For AI, a non-profit research lab that seeks to solve complex machine learning problems and create more points of entry into machine learning research. Fadaee’s work is broadly interested in all aspects of natural language understanding, particularly in multilingual learning, data-conscious learning, robust and scalable models, compositionality, and interpretability.

Salomé Viljoen is an assistant professor of law at the University of Michigan Law School who studies the information economy, the social impacts of automation, and how legal structures impact inequality. Viljoen’s current work is on the political economy of social data, including its legal status and implications, and algorithmic governance, particularly the use of economic optimization methods in relation to algorithmic fairness.

Shion Guha is an assistant professor at the University of Toronto’s Faculty of Information and Department of Computer Science, and a 2023 SRI faculty fellow. Guha’s research interests are broadly in the nascent field of human-centered data science, which he helped develop, including the role of algorithmic decision-making in public services.

Aaron Hertzmann is a principal scientist at Adobe Research and an affiliate professor at the University of Washington who is an expert in computer graphics, machine learning, and art. In this session, Hertzmann will discuss questions of authorship raised by generative AI tools that are able to create images, enabling new modes of artistic expression. Can AI algorithms be considered artists? Hertzmann will explore this issue in relation to previous technological developments, as well as the role of art as a social phenomenon.