2021 MIT IDE Annual Conference

• Sinan Aral – Director, MIT IDE
• Andrew McAfee – Co-Director & Tech for Good Research Group Lead, MIT IDE
• David Verrill – Executive Director, MIT IDE

• Andrew McAfee -Co-director & Tech for Good Research Group Lead, MIT IDE
• Neil Thompson -Research Scientist, MIT IDE
  • “The Sustainability Challenge Facing Machine Learning in a Post-Moore’s Law world” For decades, Moore’s Law not only made computers more powerful, but also more economical and environmentally sustainable. As Moore’s Law ends, the rising computing demands in machine learning and elsewhere will become increasingly burdensome slowing progress in some areas, and redirecting it in others.

Enjoy a 10-minute break and join the conversation on Twitter @mit_ide

• Dean Eckles – Social Networks & Digital Experimentation Research Group Lead, MIT IDE
• Seth Benzell – Digital Fellow, MIT IDE
  • “Rationing Social Contact During the COVID-19 Pandemic” Summoned by Director Sinan Aral’s call to action, many projects were launched to harness the MIT IDE’s social analytics skills in the pandemic response. In a series of three papers, two published and one under review, IDE Fellows Benzell, Collis and Nicolaides investigated one aspect of this problem — how to best ration newly dangerous social interactions. Harnessing mobility data from millions of smartphones, we measure the economic benefit to COVID risk ratio for different public location types, show how businesses can use this information to better serve customers, and evaluate the efficiency of US social distancing.
• Jeremy Yang – PhD Candidate, MIT Sloan School of Management
  • “First Law of Motion: Influencer Video Advertising on TikTok” This paper develops an algorithm to predict the effect of influencer video advertising on product sales. We propose the concept of motion-score, or m-score, a summary statistic that captures the extent to which a product is advertised in the most engaging parts of a video. We locate pixel-level product placement with an object detection algorithm and estimate pixel-level engagement as a saliency map by fine-tuning a deep 3D convolutional neural network on video-level engagement data. M-score is then defined as pixel-level engagement-weighted advertising intensity of a video. We construct and evaluate the algorithm with around 40,000 influencer video ads on TikTok, the largest short video platform of the world. We leverage variation in video posting time to identify the causal effect of video ads on product sales. Videos of higher m-score indeed lift more sales. This effect is sizable, robust, and more pronounced among impulsive, hedonic, or inexpensive products. We trace the mechanism to influencers’ incentives to promote themselves rather than the product. We discuss how various stakeholders in entertainment commerce can use m-score in a scalable way to optimize content, align incentives, and improve efficiency.

Enjoy a 10-minute break and join the conversation on Twitter @mit_ide

• David Rand – Misinformation & Fake News Research Group Lead, MIT IDE
• Jennifer Allen – PhD Candidate, MIT Sloan School of Management
  • “Scaling Up Fact-Checking Using the Wisdom of Crowds” Misinformation on social media has become a major focus of research and concern in recent years. Perhaps the most prominent approach to combating misinformation is the use of professional fact-checkers. This approach, however, is not scalable: Professional fact-checkers cannot possibly keep up with the volume of misinformation produced every day. Furthermore, not everyone trusts fact-checkers, with some arguing that they have a liberal bias. Here, we explore a potential solution to both of these problems: leveraging the “wisdom of crowds” to identify misinformation at scale using politically-balanced groups of laypeople. Using a set of 207 news articles flagged for fact-checking by an internal Facebook algorithm, we compare the accuracy ratings given by (i) three professional fact-checkers after researching each article and (ii) 1,128 Americans from Amazon Mechanical Turk after simply reading the headline and lede sentence. We find that the average rating of a small politically-balanced crowd of laypeople is as correlated with the average fact-checker rating as the fact-checkers’ ratings are correlated with each other. Furthermore, the layperson ratings can predict whether the majority of fact-checkers rated a headline as “true” with high accuracy, particularly for headlines where all three fact-checkers agree. We also find that layperson cognitive reflection, political knowledge, and Democratic Party preference are positively related to agreement with fact-checker ratings; and that informing laypeople of each headline’s publisher leads to a small increase in agreement with fact-checkers. Our results indicate that crowdsourcing is a promising approach for helping to identify misinformation at scale.
• Ziv Epstein – PhD Candidate, MIT Media Lab
  • “Shifting Attention to Accuracy Can Reduce Misinformation Online” In recent years, there has been a great deal of concern about the proliferation of false and misleading news on social media. Academics and practitioners alike have asked why people share such misinformation, and sought solutions to reduce the sharing of misinformation. We attempt to address both of these questions. First, we find that the veracity of headlines has little effect on sharing intentions, despite having a large effect on judgments of accuracy. This dissociation suggests that sharing does not necessarily indicate belief. Nonetheless, most participants say it is important to share only accurate news. To shed light on this apparent contradiction, we carried out four survey experiments and a field experiment on Twitter; the results show that subtly shifting attention to accuracy increases the quality of news that people subsequently share. These findings indicate that people often share misinformation because their attention is focused on factors other than accuracy—and therefore they fail to implement a strongly-held preference for accurate sharing. Our results challenge the popular claim that people value partisanship over accuracy , and provide evidence for scalable attention-based interventions that social media platforms could easily implement to counter misinformation online. I will also discuss some finding practical tips for deploying accuracy prompts on digital platforms and introduce a new platform for studying attention on social media.

Enjoy a 10-minute break and join the conversation on Twitter @mit_ide

• Maria Ressa – CEO, Rappler

Enjoy a lunch break and join the conversation on Twitter @mit_ide

• Geoffrey Parker – Visiting Scholar, MIT IDE
  • “B2B Platforms and Six Archetypes for Bridging the Industry 4.0 Scaling Chasm” Geoff shares work on a B2B platform classification scheme as well as six archetypes of digital technology adoption in the manufacturing sector.  
• John Horton – AI, Labor Economics & Online Marketplaces Research Group Lead, MIT IDE
  • “What’s Newly Possible in Online Markets” John will discuss some recent examples of platform interventions in labor markets enabled by digitization and sketch out a research agenda & some implications for practitioners.
    

Enjoy a 10-minute break and join the conversation on Twitter @mit_ide

• Renée Richardson Gosline – Human/AI Interface Research Group Lead, MIT IDE
  • “The Algorithm Made Me Do It: Human-AI Cooperation in Decision-Making and Implications for Accountability” Human-AI interaction is increasing amidst digital transformation, as humans incorporate input from “artificial intelligence” into choices. This raises questions about how human culpability is perceived when AI helps us make decisions. In order to understand how judgments of human accountability are affected by human-AI collaboration we ask: How do audiences view human responsibility when AI contributes to a problematic decision? These perceptions of accountability in Human-AI Collaborations are important, as they may create “moral crumple zones” that will impact for policy, legal action, perceptions of harm caused by biases in algorithms. We run experiments across a variety of decision scenarios to examine whether a human decision-maker will be held to greater/lesser/equal account when following the input of an algorithm (vs. another source). Our results suggest that Incorporating AI into a decision lowers perceived responsibility, equivalent to another human’s input. We argue that these results suggest that AI can be perceived as collaborative, not just passive, and call for the design of Human-AI collaborative systems that combat the decoupling of humans from their roles in decision outcomes.
• Heather Yang – PhD Candidate, MIT Sloan School of Management
  • “The Facilitatory Effects of Stereotype Congruent Features of Digital Voiced Agents” The use of female voices in novel technologies has been justified through a generalized preference for female voices. I draw upon the stereotype congruence literature to establish that, while individuals may explicitly justify their preference due to superficial characteristics of a female voice, their preferences are driven by stereotype congruence. Gender cues, as conveyed through a device’s voice, can either be congruent or incongruent with the stereotypes associated with the role that it is designed to serve, such as the female-typed role of assistant. I propose that congruent pairings serve to facilitate understanding of novel technologies by borrowing from categorical information of the stereotype, such that novice users better understand a device’s capabilities.

Enjoy a 10-minute break and join the conversation on Twitter @mit_ide

• Alex ‘Sandy’ Pentland – Data-Driven Societies Research Group Lead, MIT IDE
  • “Data Driven Societies” Data has become a major source of production, like capital, labor, and land. Consequently, people are worried about the concentration data in very few hands, and of AI using their data to exploit the them. But just as in the case of labor in the early 1900s, or banks in the 1870s, there is the possibility of communities of people coming together to use their data for their own benefit, resulting in more balanced ownership and beneficial use of data than we have today. This transformation is already underway in the legal sphere, but perhaps surprisingly there is enormous opportunity for business and investment as well.

• Sinan Aral – Director, MIT IDE
• Andrew McAfee – Co-Director & Tech for Good Research Group Lead, MIT IDE

To register for the IDE Annual Conference please contact Devin Cook, Associate Director: devinc@mit.edu

Sinan Aral a global authority on business analytics; award-winning researcher; entrepreneur and venture capitalist. He is the David Austin Professor of Management, Marketing, IT and Data Science at MIT, Director of the MIT Initiative on the Digital Economy (IDE) and a Founding Partner at Manifest Capital. He was the Chief Scientist at SocialAmp, one of the first social commerce analytics companies (until its sale to Merkle in 2012) and at Humin, a social platform that the Wall Street Journal called the first “Social Operating System” (until its sale to Tinder in 2016). He is currently on the Advisory Boards of the Alan Turing Institute, the British National Institute for Data Science in London, the Center for Responsible Media Technology and Innovation in Bergen, Norway and C6 Bank, one of the first all-digital banks of Brazil. Sinan has helped leading Fortune 500 firms, including Facebook, Yahoo!, Twitter, LinkedIn, Snapchat, WeChat, Spotify, AirBnB, Microsoft, Walmart, IBM, Intel, Cisco, Oracle, SAP and The New York Times to realize business value from big data analytics, social media and IT investments. His research has won numerous awards including the Microsoft Faculty Fellowship, the PopTech Science Fellowship, an NSF CAREER Award, a Fulbright Scholarship and the Jamieson Award for Teaching Excellence (MIT Sloan’s highest teaching honor). In 2014, he was named one of the “World’s Top 40 Business School Professors Under 40.” In 2018, he became the youngest ever recipient of the Herbert Simon Award of Rajk László College in Budapest, Hungary. In the same year, his article on the spread of false news online was published on the cover of Science magazine and became the second most influential scientific publication of the year in any discipline. Sinan’s first book, The Hype Machine, which was named a 2020 Best Book on Artificial Intelligence by WIRED, a 2020 Porchlight Best “Big Ideas and New Perspectives” Book Award Winner and among the Best New Technology Books and Best New Economy Books to Read in 2021 by BookAuthority, became an instant classic and a must-read for business leaders at every level of management. A managerial economist and econometrician by training, Sinan’s expertise spans social networks, causal inference, the design and analysis of large-scale digital experiments, machine learning, predictive modeling, natural language processing, AI, big data, marketing, IT, social commerce, ecommerce, behavior change and economic productivity. He earned his PhD at MIT and completed his Master’s degrees at the London School of Economics and at Harvard. You can find Sinan on Twitter @sinanaral and on Instagram @professorsinan.

Andrew McAfee is the Co-Director of the IDE and a Principal Research Scientist at the MIT Sloan School of Management.

His research investigates how information technology changes the way companies perform, organize themselves, and compete. At a higher level, his work also focuses on how computerization affects competition, society, the economy, and the workforce. In addition to having numerous papers published, McAfee also writes a widely read blog, which is at times one of the 10,000 most popular in the world. He is the author or co-author of more than 100 articles, case studies and other materials for students and teachers of technology. Prior to joining MIT Sloan, McAfee was a professor at Harvard Business School. He has also served as a fellow at the Berkman Center for Internet and Society at Harvard Law School. McAfee received his doctorate from Harvard Business School, and completed two Master of Science and two Bachelor of Science degrees at MIT. He speaks frequently to both academic and industry audiences, and has taught in executive education programs around the world

A journalist in Asia for 35 years, Maria Ressa co-founded Rappler, the top digital only news site that is leading the fight for press freedom in the Philippines. As Rappler’s executive editor and CEO, Maria has endured constant political harassment and arrests by the Duterte government, forced to post bail nine times to stay free. Rappler’s battle for truth and democracy is the subject of the 2020 Sundance Film Festival documentary, A Thousand Cuts.

For her courage and work on disinformation and ‘fake news,’ Maria was named Time Magazine’s 2018 Person of the Year, was among its 100 Most Influential People of 2019, and has also been named one of Time’s Most Influential Women of the Century. She was also part of BBC’s 100 most inspiring and influential women of 2019 and Prospect magazine’s world’s top 50 thinkers. In 2020, she received the Journalist of the Year award, the John Aubuchon Press Freedom Award, the Most Resilient Journalist Award, the Tucholsky Prize, the Truth to Power Award, and the Four Freedoms Award.

Among many awards for her principled stance, she received the prestigious Golden Pen of Freedom Award from the World Association of Newspapers and News Publishers, the Knight International Journalism Award from the International Center for Journalists, the Gwen Ifill Press Freedom Award from the Committee to Protect Journalists, the Shorenstein Journalism Award from Stanford University, the Columbia Journalism Award, the Free Media Pioneer Award from the International Press Institute, and the Sergei Magnitsky Award for Investigative Journalism.

Before founding Rappler, Maria focused on investigating terrorism in Southeast Asia. She opened and ran CNN’s Manila Bureau for nearly a decade before opening the network’s Jakarta Bureau, which she ran from 1995 to 2005. She wrote Seeds of Terror: An Eyewitness Account of al-Qaeda’s Newest Center of Operations in Southeast Asia and From Bin Laden to Facebook: 10 Days of Abduction, 10 Years of Terrorism.

Devin Cook is Associate Director at the MIT Initiative on the Digital Economy (IDE). Previously, she co-founded and led the IDE’s Inclusive Innovation Challenge, a $1.5 million future of work prize for startups. A Fulbright Scholar, she researched entrepreneurship and economic development among textile artisans in India. She has conducted research with MIT innovation and entrepreneurship faculty, worked at multiple start-ups, mentored over 100 start-up founders, and teaches entrepreneurship at accelerators nationwide. Devin is an Advisory Board member of Humans for AI, a Jurist for the INDEX: Award – the world’s largest design prize, and a Board Member of Coastal Enterprises, Inc.. She earned a BA from Middlebury College and an MBA from the MIT Sloan School of Management, where she was awarded the Ronald I. Heller Award for her contribution to entrepreneurship education on campus.

David Verrill is executive director of the Initiative on the Digital Economy. David has worked and consulted at MIT for more than 30 years. Prior to his work at MIT, he was a research scientist at the Center for Blood Research in Boston.

David has also worked at Xerox Adaptive Products, where he was manager of International Sales and Business Development. He has helped start two companies, including Winchester International Group and the Hub Investment Group, which has invested in more than 50 early stage companies in the New England region – including Zipcar and DraftKings. He sits on the boards of several startups, is Chairman Emeritus of the Angel Capital Association, and is the recipient of the Hans Severiens Award (along with three other distinguished Sloan alumni – Jean Hammond, Brad Feld, and James Geshwiler).

David holds degrees from Bowdoin College and the MIT Sloan School of Management, where he received a master of science in management.

Dean Eckles is an Assistant Professor of Marketing at MIT Sloan.

His substantive research examines people’s interactions with and through communication technologies, especially how these technologies mediate, amplify, and direct social influence. This work sometimes requires or benefits from new analytical methods, so Eckles also works on applied statistics, design of field experiments, and causal inference.

Prior to joining MIT, he was a scientist at Facebook, where he worked on many product areas and analytical methods, including News Feed, messaging, advertising, tools for randomized experiments, and survey methods. Eckles previously worked in research at Nokia and Yahoo.

Eckles received his BA in philosophy, a BS and MS in cognitive science,  an MS in statistics, and a PhD in communication, all from Stanford University.

John Horton is the Richard S. Leghorn (1939) Career Development Professor and an Associate Professor of Information Technologies at the MIT Sloan School of Management.

Horton’s research focuses on the intersection of labor economics, market design, and information systems. He is particularly interested in improving the efficiency and equity of matching markets.

After completing his PhD and prior to joining NYU Stern School of Business in 2013, he served for two years as the staff economist for oDesk, an online labor market.

Horton received a BS in mathematics from the United States Military Academy at West Point and a PhD in public policy from Harvard University.

David Rand is the Erwin H. Schell Professor and Professor of Management Science and Brain and Cognitive Sciences at MIT, an affiliate of the MIT Institute of Data, Systems, and Society, and the director of the Human Cooperation Laboratory and the Applied Cooperation Team.

Bridging the fields of cognitive science, behavioral economics, and social psychology, David’s research combines behavioral experiments run online and in the field with mathematical and computational models to understand people’s attitudes, beliefs, and choices. His work uses a cognitive science perspective grounded in the tension between more intuitive versus deliberative modes of decision-making. He focuses on illuminating why people believe and share misinformation and “fake news,” understanding political psychology and polarization, and promoting human cooperation. David received his B.A. in Computational Biology from Cornell University in 2004 and his Ph.D. in Systems Biology from Harvard University in 2009, was a post-doctoral researcher in Harvard University’s Department of Psychology from 2009 to 2013, and was an Assistant and then Associate Professor (with tenure) of Psychology, Economics, and Management at Yale University prior to joining the faculty at MIT. His work has been published in peer-reviewed journals such Nature, Science, Proceedings of the National Academy of Science, the American Economic Review, Psychological Science, Management Science, New England Journal of Medicine, and the American Journal of Political Science, and has received widespread attention from print, radio, TV and social media outlets. He has also written popular press articles for outlets including the New York Times, Wired, New Scientist, and the Psychological Observer. He was named to Wired magazine’s Smart List 2012 of “50 people who will change the world,” chosen as a 2012 Pop!Tech Science Fellow, and awarded the 2015 Arthur Greer Memorial Prize for Outstanding Scholarly Research, fact-checking researcher of the year in 2017 by the Poyner Institute’s International Fact-Checking Network, and the 2020 FABBS Early Career Impact Award from the Society for Judgment and Decision Making. Papers he has coauthored have been awarded Best Paper of the Year in Experimental Economics, Social Cognition, and Political Methodology.

Renée Richardson Gosline is a Senior Lecturer in the Management Science group at the MIT Sloan School of Management and the head of the new Human-AI Interaction group at MIT’s Initiative on The Digital Economy. She is an expert on the intersection between behavioral science and technology, and the implications of AI for cognitive bias in human decision-making. In 2020 Dr. Gosline was named a Digital Fellow at Stanford’s Digital Economy Lab. and an honoree on the Thinkers50 Radar List of thinkers who are “putting a dent in the universe.” She has also been named one of the World’s Top 40 Professors under 40 by Poets and Quants. She is a leading thinker on the science of digital brand strategy and CX, and has been published in academic journal and books, and has contributed her expertise to international media outlets PBS, The BBC, The Economist, NPR, Yahoo Finance, Forbes, and Psychology Today.

Dr. Gosline’s research examines how digital structure and technology affect human judgment and performance (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 digital 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. She is currently conducting experiments on how the presence of AI affects the judgment of human decisions, and the interplay of human and AI bias, Gosline is also currently writing a book called “The Human Algorithm” (MIT Press), which examines how AI affects our lives, and the benefits and perils of our digitally-mediated judgments.

Dr. Gosline enjoys teaching MBA and Executive Education classes on CX (Customer Experience), Brand strategy, and Experimental Culture. She has also collaborated and consulted with a variety of organizations on CX and Leadership, including Salesforce, IBM, Procter and Gamble, OECD, Johnson & Johnson, Analog Devices Incorporated, TD Ameritrade, and Capgemini. Prior to academia, she was a marketing practitioner at LVMH Moet Hennessy and Leo Burnett.

Dr. Gosline serves on the advisory board of the National Kidney Foundation and the Scientific Affiliate Board of the Behavioral Economics group Ideas42. She received her Undergraduate, Master’s, and Doctoral degrees at Harvard University.

Jennifer Allen is a PhD Candidate at the MIT Sloan School of Management in the Quantitative Marketing Group. Previous Degree: B.A. Computer Science & Psychology, Yale College

Ziv Epstein is a PhD student in the MIT Media Lab, co-advised by David Rand and Sandy Pentland. Epstein’s work integrates aspects of design and computational social science to understand and build cooperative systems. Epstein focuses on new challenges and oppurtunities that emerge from a digital society, particularly in the domains of social media and artificial intelligence.

Seth G. Benzell is a Digital Fellow at the MIT Initiative on the Digital Economy in the group on Productivity, Employment, and Inequality.  He holds a Ph.D. in Economics from Boston University.

Seth’s work is in the economics of automation, digitization, and networks. He is also interested in fiscal policy, and macroeconomics generally. A current focus is investigating how skill-biased technological changes are directed and propagate throughout the economy. Another focus is predicting how new technologies, especially artificial intelligence, will impact investment, wages and welfare. Previous work has explored the possibility of negative welfare effects from automation in an overlapping generations context. In ongoing research, he studies the effect of application programming interfaces and ‘firm inversion’ at the firm and macroeconomic level. Seth is also interested in economic history and fiscal policy. He has worked on multiple studies of tax reform in computable general equilibrium models and has briefed legislative assistants at the U.S. Capitol. In an economic history paper, he showed that European royal family network connections played a causal role in preventing violent conflict.

Before coming to MIT, Seth received his Ph.D. in Economics at 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.  His undergraduate thesis adviser was Keith Finlay.

View Benzell’s latest publication “Rationing social contact during the COVID-19 pandemic: Transmission risk and social benefits of US locations” here. (co-authors: Avinash Collis and Christos Nicolaides)

Geoffrey Parker is a professor of engineering at Dartmouth College where he also serves as Director of the Master of Engineering Management Program.

In addition, he is a research fellow and visiting scholar at MIT’s Initiative for the Digital Economy. He received a B.S.E. from Princeton and M.S. and Ph.D. from MIT. Parker has made significant contributions to the field of network economics and strategy as co-developer of the theory of “two-sided” markets. He is co-author of the award-winning book “Platform Revolution.” His current research includes studies of platform business strategy, Internet of Things data governance, and technical/economic systems to integrate distributed energy resources. Parker’s research has been funded by grants from the National Science Foundation, the Department of Energy, the states of Louisiana and New York and numerous corporations.  He serves or has served as associate editor at multiple journals and as a National Science Foundation panelist. Parker is a frequent keynote speaker and advises senior leaders on their organizations’ platform strategies. Before attending MIT, he held positions in engineering and finance at GE. Additional information can be found at ggparker.net and @g2parker.

Neil Thompson is a Research Scientist at MIT’s Computer Science and Artificial Intelligence Lab and a Visiting Professor at the Lab for Innovation Science at Harvard.

 Neil is also an Associate Member of the Broad Institute, and was previously an Assistant Professor of Innovation and Strategy at the MIT Sloan School of Management, where he co-directed the Experimental Innovation Lab (X-Lab).  He has advised businesses and government on the future of Moore’s Law and have been on National Academies panels on transformational technologies and scientific reliability.

Neil did his PhD in Business and Public Policy at Berkeley, where he also did Masters degrees in Computer Science and Statistics. He has a masters in Economics from the London School of Economics, and undergraduate degrees in Physics and International Development. Prior to academia, Neil worked at organizations such as Lawrence Livermore National Laboratories, Bain and Company, The United Nations, the World Bank, and the Canadian Parliament.

Heather Yang is an organizational psychologist and PhD candidate at MIT Sloan School of Management. She has been recognized as an MIT Presidential Fellow. Yang’s dissertation research is on how social information embedded in novel technologies (such as artificial intelligence) influences their use and how technology shapes us and our social worlds in return.

Starting Fall 2021, Yang will be an incoming Assistant Professor of Management & Technology at Bocconi University in Milan, Italy.

Jeremy Yang is a PhD Candidate at MIT Sloan School of Management. His research focuses on combining economic and behavioral insights with causal inference and machine learning to optimize managerial decisions such as advertising, pricing, and targeting.