• Ariel Procaccia is Gordon McKay Professor of Computer Science at Harvard University. He works on a broad and dynamic set of problems related to AI, algorithms, economics, and society. His distinctions include the Social Choice and Welfare Prize (2020), a Guggenheim Fellowship (2018), the IJCAI Computers and Thought Award (2015), and a Sloan Research Fellowship (2015). To make his research accessible to the public, he has founded the not-for-profit website Spliddit.org and he regularly contributes opinion pieces.

• Bo An is a President’s Council Chair Associate Professor at Nanyang Technological University, Singapore. His current research interests include artificial intelligence, multiagent systems, computational game theory, reinforcement learning, and optimization. Dr. An received many awards including INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice. He led the team HogRider which won the 2017 Microsoft Collaborative AI Challenge. He was named to IEEE Intelligent Systems' "AI's 10 to Watch" list for 2018.

• Dorsa Sadigh is an assistant professor in Computer Science and Electrical Engineering at Stanford University. Her research interests lie in the intersection of robotics, learning, and control theory. Specifically, she is interested in developing algorithms for safe and adaptive human-robot and multi-agent interaction. Dorsa received her doctoral degree in Electrical Engineering and Computer Sciences (EECS) from UC Berkeley in 2017, and received her bachelor’s degree in EECS from UC Berkeley in 2012. She is recognized by awards such as the NSF CAREER award, the AFOSR Young Investigator award, the IEEE TCCPS early career award, MIT TR35, as well as industry awards such as the JP Morgan, Google, and Amazon faculty research awards.

• Michael Muthukrishna is Associate Professor of Economic Psychology and STICERD Developmental Economics Group Affiliate at the London School of Economics, CIFAR Azrieli Global Scholar at the Canadian Institute for Advanced Research, and Technical Director of The Database of Religious History (religiondatabase.org). His research focuses on human biological and cultural evolution, how this understanding of human behavior and social change can improve innovation, reduce corruption, and increase cross-cultural cooperation. His work is featured in international and national news outlets including CNN, BBC, Wall Street Journal, The Economist, Scientific American, Nature News, and Science News, and in the UK in the Times, Telegraph, Mirror, Sun, and Guardian. Michael's research is informed by his educational background in engineering and psychology, with graduate training in evolutionary biology, economics, and statistics, and his personal background living in Sri Lanka, Botswana, Papua New Guinea, Australia, Canada, United States, and United Kingdom. He is currently working on a book to be published with MIT Press.

• Website: michael.muthukrishna.com

• Twitter: @mmuthukrishna

• Nika Haghtalab is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. She works broadly on the theoretical aspects of machine learning and algorithmic economics. Prof. Haghtalab's work builds theoretical foundations for ensuring both the performance of learning algorithms in presence of everyday economic forces and the integrity of social and economic forces that are born out of the use of machine learning systems.

• Previously, Prof. Haghtalab was an Assistant Professor in the CS department of Cornell University, in 2019-2020. She received her Ph.D. from the Computer Science Department of Carnegie Mellon University. She is a co-founder of Learning Theory Alliance (LeT-All). Among her honors are the CMU School of Computer Science Dissertation Award, SIGecom Dissertation Honorable Mention, and other industry research awards.

• Pablo Samuel Castro was born and raised in Quito, Ecuador, and moved to Montreal after high school to study at McGill, eventually obtaining his masters and PhD at McGill, focusing on Reinforcement Learning. He is currently a staff research Software Developer in Google Research (Brain team) in Montreal, focusing on fundamental Reinforcement Learning research, Machine Learning and Creativity, and being a regular advocate for increasing the LatinX representation in the research community. He is also an active musician.

• Allan Dafoe is a Senior Staff Research Scientist and lead of the Long-term Strategy and Governance team at DeepMind; Allan is also President of the Centre for the Governance of AI and Trustee of the Cooperative AI Foundation. He was previously on faculty at the University of Oxford and Yale University, with a background in political science. Allan’s work aims to map and prepare for the potential opportunities and risks from advanced AI, so as to help steer the development of AI for the benefit of all humanity.

More info at: www.allandafoe.com

• Chris Amato is an assistant professor in the Khoury College of Computer Sciences at Northeastern University. His research is at the intersection of artificial intelligence, machine learning and robotics. Amato currently heads the Lab for Learning and Planning in Robotics, where his team works on planning and reinforcement learning in partially observable and multi-agent/multi-robot systems.

• Before joining Northeastern, he worked as a research scientist at Aptima Inc., a research scientist and postdoctoral fellow at MIT, and an assistant professor at the University of New Hampshire. Amato received his bachelor’s from Tufts University and his master’s and doctorate from the University of Massachusetts, Amherst.

• Amato is widely published in leading artificial intelligence, machine learning, and robotics conferences. He is the recipient of a best paper prize at AAMAS-14 and was nominated for the best paper at RSS-15, AAAI-19, and AAMAS-21. Amato has also successfully co-organized several tutorials on multi-agent planning and learning and has co-authored a book on the subject.

• As one of Forbes "15 AI Ethics Leaders Showing The World The Way Of The Future", Elizabeth M. Adams is a highly-sought-after resource in business and professional circles for executives, small business owners, non-profits, institutions of higher learning and community leaders from all sectors of society, looking to expand their knowledge of AI Ethics and Leadership of Responsible AI™.

• For over two decades, she has studied the science of business and technology influences on society while leading large scale technology initiatives for Fortune 500 companies and various government organizations. As a scholar-practitioner, Elizabeth has developed her expertise by interviewing, observing, advising, and working alongside successful technical and non-technical leaders, creating alliances with community that translate theory into results.

• In December of 2019, Elizabeth was awarded the inaugural 2020 Race & Technology Practitioner Fellowship by Stanford University's Center for Comparative Studies in Race & Ethnicity. In August of 2021 she was awarded Affiliate Fellow status with Stanford's Institute for Human-Centered AI, a 2-year appointment. Elizabeth is pursuing a doctoral degree at Pepperdine University with a research focus on Leadership of Responsible AI™. Elizabeth serves as the Global Chief AI Culture & Ethics Officer for Women in AI where she volunteers her time building a world class team and program to support the needs of 8,000 women around the world. Elizabeth works with a sense of urgency and intentionality in helping others aim high to create technology that brings us all together to make a positive impact on the world.

• Fei Fang is Leonardo Assistant Professor at the Institute for Software Research in the School of Computer Science at Carnegie Mellon University. Before joining CMU, she was a Postdoctoral Fellow at the Center for Research on Computation and Society (CRCS) at Harvard University, hosted by David Parkes and Barbara Grosz. She received her Ph.D. from the Department of Computer Science at the University of Southern California advised by Milind Tambe (now at Harvard).

• Her research lies in the field of artificial intelligence and multi-agent systems, focusing on integrating machine learning with game theory. Her work has been motivated by and applied to security, sustainability, and mobility domains, contributing to the theme of AI for Social Good. She is the recipient of the IJCAI-21 Computers and Thought Award. She was named to IEEE Intelligent Systems’ “AI’s 10 to Watch” list for 2020. Her work has won the Best Paper Runner-Up at the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI’21), Distinguished Paper at the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI’18), Innovative Application Award at Innovative Applications of Artificial Intelligence (IAAI’16), the Outstanding Paper Award in Computational Sustainability Track at the International Joint Conferences on Artificial Intelligence (IJCAI’15). She received an NSF CAREER Award in 2021. Her dissertation is selected as the runner-up for IFAAMAS-16 Victor Lesser Distinguished Dissertation Award, and is selected to be the winner of the William F. Ballhaus, Jr. Prize for Excellence in Graduate Engineering Research as well as the Best Dissertation Award in Computer Science at the University of Southern California.

• Her work has been deployed by the US Coast Guard for protecting the Staten Island Ferry in New York City since April 2013. Her work has led to the deployment of PAWS (Protection Assistant for Wildlife Security) in multiple conservation areas around the world, which provides predictive and prescriptive analysis for anti-poaching effort.