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Colloquium Series

We highlight exemplary work on improving access to opportunity for disadvantaged and marginalized groups through a monthly online colloquium series. You can find below a list of the past talks in our colloquium series and their recordings on our youtube channel and you can subscribe to our calendar.
 

Previous Colloquium Talks



Pauline Kim, Washington University in St. Louis


Date: Friday, November 15, 12:00-1:30 PM EST

Link: Youtube Live

 

Pauline Kim is the Daniel Noyes Kirby Professor Washington University Law School in St. Louis. She is a nationally recognized expert on the law governing the workplace and has written widely on issues affecting workers, including privacy, discrimination and job security, as well as the impact of technology in the workplace. Her research focuses on the risks of unfairness and bias as automated decision-processes are incorporated into firms’ personnel decision-making and the legal challenges posed by these technological developments. She is studying the role of technological intermediaries in shaping labor markets, and the possibilities for artificially intelligent systems to avoid human biases in making personnel decisions. She is a graduate of Harvard and Radcliffe Colleges and Harvard Law School, and clerked for the Honorable Cecil F. Poole on the Ninth Circuit Court of Appeals. Following her clerkship, she worked as a staff attorney at the Employment Law Center/Legal Aid Society of San Francisco.



 

Manipulating Opportunity: Online Market Intermediaries and Risks of Discrimination

Concerns about online manipulation have centered on fears about undermining the autonomy of consumers and citizens. Less analyzed are the risks that the same techniques of personalizing information online can also threaten equality. When predictive algorithms are used to allocate information about opportunities like employment, housing and credit, they can reproduce past patterns of discrimination and exclusion in these markets. In this talk, I will focus on the labor market and the increasingly dominant role of tech intermediaries in managing interactions between job-seekers and firms. Because these intermediaries rely on past behavioral data to distribute information about job openings and match job-seekers with hiring firms, their predictions about who will be a good match for which jobs will likely reflect existing occupational segregation and inequality. I will discuss the legal and policy implications of tech intermediaries’ new role in labor markets, including the challenges in holding them responsible for discriminatory effects and the possibility of other regulatory responses that might address these concerns.



Kentaro Toyama, University of Michigan


Date: Friday, October 25, 12:00-1:30 PM EST

Link: Youtube Live

 

Kentaro Toyama is W. K. Kellogg Professor of Community Information at the University of Michigan School of Information and a fellow of the Dalai Lama Center for Ethics and Transformative Values at MIT. He is the author of Geek Heresy: Rescuing Social Change from the Cult of Technology. From 2005-2009, Toyama was co-founder and assistant managing director of Microsoft Research India. There, he started the Technology for Emerging Markets research group, which conducts interdisciplinary research to understand how the world’s poorest communities interact with electronic technology and to invent new ways for technology to support their socio-economic development. Prior to his time in India, Toyama did research in artificial intelligence, computer vision, and human-computer interaction at Microsoft and taught mathematics at Ashesi University in Ghana.



 

Lessons from ICTD -- Information & Communication Technologies and Development

Since the turn of the millennium, the interdisciplinary field of information & communication technologies and development (ICTD) has explored how digital technologies could contribute to international socio-economic development. The associated research community includes both techno-utopians who imagine that just about any problem can be solved with the right application of technology, as well as extreme skeptics wary of any attempts at intervention. Debates continue, but in this talk, I will attempt to summarize some of the expressed consensus in ICTD -- things that not everyone necessarily believes, but will at least pay lip service to. I will also discuss what I call technology's "Law of Amplification," which reconciles some of the differing opinions in ICTD and also offers guidance for how mechanism design can have real-world impact.



Justine Hastings, Brown University


Date: Friday, May 10, 1:00-2:15 PM EST

 

Justine Hastings is a Professor of Economics and International and Public Affairs at Brown University and a Faculty Research Associate with the National Bureau of Economic Research. Her areas of expertise include research in Industrial Organization and Public Economics which address important economic and public policy questions. She has conducted academic research on topics such as market structure and competition, environment and energy regulation, advertising and consumer protection, consumer financial markets, health care, social safety-net programs, and markets for higher education. Her research employs diverse empirical techniques including field experiments, survey analysis, machine learning, predictive analytics, analysis of large administrative datasets, and structural demand and supply estimation. Her research was cited in the 2017 Nobel Prize scientific background materials, and has been used to shape public policy improvements around the world. Professor Hastings is the founding director of Research Improving People's Lives (RIPL), a nonprofit research institute using data and science to impact policy and improve lives.



 

Fact-Based Policy: How Do States and Local Governments Accomplish It?

There is growing demand for a genuinely accountable government which, even with limited resources, delivers programs and policies with meaningful, measurable impact. Rapid advances in technology support the use of data and science in the private sector to develop insights about what people need, innovate products and policies to meet those needs, and then measure their success. Government has the potential to be similarly impactful, prompting recent federal and state calls for government to use a data-driven approach to produce efficient and effective policy solutions. But how can state and local governments use data and science to deliver improved results to their constituents? This talk will highlight the key challenges to creating and supporting fact-based policy at the state and local level, and will outline solutions and lessons learned from an innovative and scalable partnership model developed with the state of Rhode Island.


Rajiv Sethi, Barnard College, Columbia University


Date: Friday, April 5, 1:00-2:30 PM EST

Link: Youtube Live

 

Rajiv Sethi is a Professor of Economics at Barnard College, Columbia University and an External Professor at the Santa Fe Institute. He has previously held visiting positions at Microsoft Research in New York City, and at the Institute for Advanced Study in Princeton. He is on the editorial boards of the American Economic Review and Economics and Philosophy. His current research deals with information and beliefs, including examining how stereotypes affect interactions among strangers, especially in relation to crime and the criminal justice system. He is also part of a large interdisciplinary team working on the forecasting of geopolitical events using methods that combine machine models with human judgment. Rajiv is a founding member of CORE (Curriculum Open-Access Resources for Economics), a group of scholars engaged in the production of high-quality freely-available resources for the teaching of economics.



 

The Geography of Lethal Force

Police officers in the United States currently kill about eleven hundred civilians annually. In contrast, police in Germany kill fewer than ten a year, and those in England and Wales kill about two. This talk will examine recent data on police homicides in the US, with particular attention to the geographic distribution of incidents and racial disparities in victimization. I consider and evaluate two competing hypotheses that seek to account for the data, and discuss the possibility that Simpson's paradox may be relevant for understanding the patterns that we see. Some historical context is provided with reference to the 1968 Kerner Commission Report and the Carnegie-Myrdal study of the 1930s. The talk will draw on material from Shadows of Doubt: Stereotypes, Crime and the Pursuit of Justice, written jointly with Brendan O'Flaherty (Harvard University Press, forthcoming in April 2019) as well as ongoing work with Jose Luis Monteil Olea and Brendan O'Flaherty.



Matthew Jackson, Stanford University


Date: Friday, March 1, 1:00-2:30 PM EST

Link: Youtube Live

 

Matthew O. Jackson is the William D. Eberle Professor of Economics at Stanford University and an external faculty member of the Santa Fe Institute and a senior fellow of CIFAR. He was at Northwestern University and Caltech before joining Stanford, and received his BA from Princeton University in 1984 and PhD from Stanford in 1988. Jackson's research interests include game theory, microeconomic theory, and the study of social and economic networks, on which he has published many articles and the books `The Human Network' and `Social and Economic Networks'. He also teaches an online course on networks and co-teaches two others on game theory. Jackson is a Member of the National Academy of Sciences, a Fellow of the American Academy of Arts and Sciences, a Fellow of the Econometric Society, a Game Theory Society Fellow, and an Economic Theory Fellow, and his other honors include the von Neumann Award, a Guggenheim Fellowship, the Social Choice and Welfare Prize, the B.E.Press Arrow Prize for Senior Economists, and teaching awards. He has served as co-editor of Games and Economic Behavior, the Review of Economic Design, and Econometrica.



 

Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials

Can we identify highly central individuals in a network without collecting network data, simply by asking community members? Can seeding information via such nominated individuals lead to significantly wider diffusion than {choosing} randomly chosen people, or even respected ones? In two separate large field experiments in India, we answer both questions in the affirmative. In particular, in 521 villages in Haryana, we provided information on monthly immunization camps to either randomly selected individuals (in some villages) or to individuals nominated by villagers as people who would be good at transmitting information (in other villages). We find that the number of children vaccinated every month is 22% higher in villages in which nominees received the information. We show that people's knowledge of who are highly central individuals and good seeds can be explained by a model in which community members simply track how often they hear gossip about others. Indeed, we find in a third dataset that nominated seeds are central in a network sense, {and are} not just those with many friends or in {powerful} positions.



Tawanna Dillahunt, University of Michigan


Date: Friday, January 25th, 1:00-2:30 PM EST

 

Tawanna Dillahunt is an Assistant Professor at the University of Michigan's School of Information and holds a courtesy appointment with the Electrical Engineering and Computer Science Department. Tawanna earned her Ph.D. in Human-Computer Interaction (HCI) from Carnegie Mellon University. She now leads the Social Innovations research group, an interdisciplinary group of individuals whose vision is to design, build, and enhance technologies to solve real-world problems affecting marginalized groups and individuals primarily in the U.S. Our current projects aim to address unemployment, environmental sustainability, and technical literacy by fostering social and sociotechnical capital within these communities.



 

Designing and Envisioning Digital Tools for Low-resource Job Seekers

Today's Information and Communication Technologies (ICTs) are designed to address one of society's most pressing problems---unemployment. These technologies support job seekers' ability to search for jobs, create resumes, highlight skills, share employment opportunities, and even transport to work and job counseling. However, the benefits of employment tools and technologies are unequally distributed and provide limited advantages for certain populations in our society. Like other valuable resources, ICTs have done little to support individuals with limited knowledge, skills, or experience to leverage them and who often face geographic and social isolation. Without an understanding of how people from low-resource settings use ICTs for job seeking, the same employment inequalities that occur offline will be repeated in online contexts. In this presentation, I will discuss the results of several studies that investigate how ICTs could improve employability, particularly among job seekers with limited digital skills, education, and income, and those who are geographically and socially isolated. I will also discuss new principles for fostering innovations among these populations and identify barriers for designers and technologists to address in the future.


 

Alvin Roth, Stanford University


Date: Thursday, December 13th, 12:00-1:30 PM EST
Link: Youtube Live

 

Al Roth is a professor of Economics at Stanford. He shared the 2012 Nobel prize in Economics for “the theory of stable allocations and the practice of market design”.



 

Market design is more complicated than mechanism design. And so is achieving good social outcomes.

Marketplaces are often small parts of large markets, and so potential marketplace participants may have large strategy sets, that include actions taken outside of the marketplace. And markets require social support, so the behavior of people who do not intend to participate in the market may nevertheless be important for market design. This talk will illustrate these points with some examples, drawing on experience from the design of school choice systems and kidney exchange clearinghouses.



Canice Prendergast, University of Chicago


Date: Monday, November 12th, 1:00-2:30 PM EST
Link: Youtube Live

 

Canice Prendergast is the author of "The Limits of Bureaucratic Efficiency" published in the Journal of Political Economy in 2003 and "The Tenuous Trade-Off Between Risk and Incentives" that appeared in the Journal of Political Economy in 2002. Prendergast is widely published, with work appearing in the Economic Journal, the Journal of Labor Economics, the American Economic Review, the Journal of the Japanese and International Economics, and the European Economic Review. Articles on his recent research have appeared in Fortune Magazine, the Financial Times, the Economist, and Der Spiegel.



 

The Allocation of Food to Food Banks

Feeding America distributes food to food banks across the United States. In 2005, it transitioned from a centralized allocation process to one where local affiliates would bid for food items through an online auction mechanism. To do so, it constructed a specialized currency called “shares”. The change, its necessary idiosyncrasies, and outcomes are described here. We both show that the new system exhibits desirable theoretical properties, and document considerable welfare implications. The choices of the food banks vary enormously from the allocations they received under the old system, and much of this gain is from sorting of food banks along the quality-quantity dimension. Furthermore, supply of food rose by roughly 100 million pounds around the time of its introduction. A structural exercise estimates that the value of reallocated demand effectively meant that each pound of food allocated through this system increased efficiency by almost another additional pound.