Angela Aristidou will spend her year at CASBS focused on a project tentatively titled Bringing the Social in the Practice of Artificial Intelligence for Cross-sector Collaborations. This project brings together two lines of inquiry: collaboration across sectors (public, private, third), and the mobilisation of digital tools to support these cross-sector collaborations. The project aims to understand how digital tools—and in particular AI-powered tools and platforms-are used in real-world settings by actors within, across and outside organizational boundaries and across sectors. Aristidou is an assistant professor at the University College London School of Management. Her current research and research team are funded through her UK Research Innovation grant (UKRI FLF, 2020-2028). She leads a team of postdoctoral research fellows and PhD students that combines methodologies from management, economics, sociology and public policy and employs both qualitative and quantitative techniques to collect real-life datasets in the UK, China, USA, and Canada. Each of these empirical studies consists of multiple cases of digital tools being deployed in the formation of new, government-mandated cross-sector collaborations for health care integration. In 2022, Aristidou was invited to join the UK NICE Panel for the development of national standards for AI implementation in healthcare and has published on the topic of AI in Healthcare in The Lancet. Since 2019, Aristidou has been chairing the international Research Advisory Board for the Relational Coordination Collaborative as well as multiple international, interdisciplinary symposia on cross-sector collaboration and AI.

David Autor is Ford Professor in the MIT Department of Economics, vice president of the American Economic Association, co-director of the NBER Labor Studies Program and the JPAL Work of the Future experimental initiative. His scholarship explores the labor market impacts of technological change and globalization on job polarization, skill demands, earnings levels and inequality, and electoral outcomes.

Autor has received numerous awards for both his scholarship—the National Science Foundation CAREER Award, an Alfred P. Sloan Foundation Fellowship, the Sherwin Rosen Prize for outstanding contributions to the field of Labor Economics, the Andrew Carnegie Fellowship in 2019, the Society for Progress Medal in 2021—and for his teaching, including the MIT MacVicar Faculty Fellowship. In 2020, Autor received the Heinz 25th Special Recognition Award from the Heinz Family Foundation for his work “transforming our understanding of how globalization and technological change are impacting jobs and earning prospects for American workers.”

In a 2019 article, the Economist labeled him as “The academic voice of the American worker.” Later that same year, and with (at least) equal justification, he was christened “Twerpy MIT Economist” by John Oliver of Last Week Tonight in a segment on automation and employment.

Sarah’s research uses novel methods to measure skills, tasks, and technologies, with an emphasis on uncovering fine distinctions using big datasets. 

Her most recent work uses state-of-the-art natural language processing techniques to better characterize how jobs have changed over time.

Sarah has been published by the Journal of Policy Analysis and Management and the Sloan Management Review, and has spoken at several events, including the California State Assembly’s Rising Tide Summit on Economic Security. In 2019, she was awarded an honorable mention by the Upjohn Institute for her dissertation, “Three Essays on Vulnerable Workers.” 

Sarah received her Ph.D. in economics from the University of California, Santa Barbara, and was a postdoctoral associate at the MIT Initiative on the Digital Economy.

She is especially interested in questions related to market structure, firm strategies, and consumer behavior in digital markets. Her research combines economic modeling and data analytics to understand the online economy.

Sagit earned her PhD and MA in economics, and BSc in mathematics from Tel Aviv University. She joined the Coller School of Management in October 2017 as an assistant professor of Technology Management and Information Systems. 

Sagit also conducts postdoctoral research at MIT’s Sloan School of Management and the MIT Initiative on the Digital Economy, where she remains a digital fellow.

Matt Beane does field research on work involving robots and AI to uncover systematic positive exceptions that we can use across the broader world of work. His award-winning research has been published in top management journals such as Administrative Science Quarterly and Harvard Business Review, and he has spoken on the Ted stage. He also took a two-year hiatus from his doctoral studies at MIT’s Sloan School of Management to help found and fund Humatics, a full-stack IoT startup. Beane is an assistant professor in the Technology Management Program at the University of California, Santa Barbara, and a digital fellow with Stanford’s Digital Economy Lab and MIT’s Institute for the Digital Economy.

Seth is an assistant professor of Management Science at the Argyros School of Business and Economics at Chapman University. He holds a Ph.D. in Economics. Before coming to Chapman University, Seth was a postdoctoral associate at the MIT Initiative on the Digital Economy. Seth received his Ph.D. in economics from Boston University in 2016. His dissertation advisor was Laurence Kotlikoff. He received a B.A. in economics and a B.S. in physics and mathematics from Tulane University in 2012.

Seth’s current projects with other Stanford Digital Economy Lab researchers focus on measuring skill biased technical change, taxation, and regulation of digital platforms, as well as the measurement of network effects and the macroeconomic implications of progress in artificial intelligence. 

Seth has presented his research at the US Capitol and as an expert for a US international public diplomacy mission. His work has been published in AEJ: Applied Economics, PNAS, Sloan Management Review and other peer-reviewed and non-peer reviewed outlets. 

He is an Assistant Professor in the Department of Information, Risk and Operations Management at the McCombs School of Business at The University of Texas at Austin. He is also a digital fellow at the MIT Initiative on the Digital Economy and the Stanford Digital Economy Lab. 

Avinash holds a PhD in management science from the Sloan School of Management at Massachusetts Institute of Technology.

His research builds broadly on advances in the fields of labor economics, sociology, computational social science, network science, data science, political science, and complex systems.

Morgan is assistant professor in the Department of Informatics and Networked Systems and the Department of Information Culture and Data Stewardship in the School of Computing and Information at the University of Pittsburgh. 

He is also an MIT Connection Science Fellow and digital fellow at the Stanford Institute for Human-Centered Artificial Intelligence. Morgan also serves as researcher at the Massachusetts General Hospital Center for Genomic Medicine and a research affiliate at the Institute for Cyber Law, Policy, and Security at the University of Pittsburgh.

Renée is an expert on the intersection between behavioral science and technology, and the implications for cognitive bias in human decision-making. She is a leading thinker on the science of digital brand strategy and her research and expertise have been published in various academic and trade publications. 

Renée’s research examines how social structure and technology (e.g., Digital Customer Experience, Status, Social Media) affect performance and self-perception (as featured in her TEDx talk, “The Outsourced Mind”). Her projects have examined how cognitive style predicts preference for AI versus human input; the interaction of brand status and placebo effects in performance; how consumers determine real from fake products; the circumstances under which customers perceive value in platforms; and the effects of storytelling in social media on trust and persuasion. 

Renée is a 2020 honoree on the Thinkers50 Radar List of thinkers who are “putting a dent in the universe,” and has been named one of the World’s Top 40 Professors under 40 by Poets and Quants.

Jeremy Howard is a data scientist, researcher, developer, educator, and entrepreneur. Jeremy is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible, and is an honorary professor at the University of Queensland. Previously, Jeremy was a Distinguished Research Scientist at the University of San Francisco, where he was the founding chair of the Wicklow Artificial Intelligence in Medical Research Initiative.

Jeremy was the founding CEO of Enlitic, which was the first company to apply deep learning to medicine, and was selected as one of the world’s top 50 smartest companies by MIT Tech Review two years running. He was the President and Chief Scientist of the data science platform Kaggle, where he was the top ranked participant in international machine learning competitions 2 years running. He was the founding CEO of two successful Australian startups (FastMail, and Optimal Decisions Group–purchased by Lexis-Nexis). Before that, he spent 8 years in management consulting, at McKinsey & Co, and AT Kearney. Jeremy has invested in, mentored, and advised many startups, and contributed to many open-source projects.

He has many media appearances, including writing for the Guardian, USA Today, and the Washington Post, appearing on ABC (Good Morning America), MSNBC (Joy Reid), CNN, Fox News, BBC, and was a regular guest on Australia’s highest-rated breakfast news program. His talk on TED.com, “The wonderful and terrifying implications of computers that can learn”, has over 2.5 million views. He is a co-founder of the global Masks4All movement.