Talks on Technology Science (ToTS) and Topics in Privacy (TIP)

Fall 2016

This is the schedule of weekly talks on Technology Science from expert researchers, public interest groups, and others on the social impact of technology and its unforseen consequences.

Join us on most Monday afternoons 2:30-4 PM at CGIS Knafel, Room K354 (1737 Cambridge St, Cambridge, MA).

Date Speakers Topic
9/19 Virgilio Almeida, Harvard University Re-Identification and the Right to Be Forgotten: a data driven study
9/26 Alan Mislove, Northeastern University Increasing the transparency of online algorithms
10/3 Christo Wilson, Northeastern University Caught Red Handed: Tracing Information Flows Between Ad Exchanges Using Retargeted Ads
10/10 Columbus Day None
10/17 Mike Katell, University of Washington Reputational Justice: Transparency vs. Equity in the Information Society
10/24 John Byers, Boston University Witnessing the Rise of the Sharing Economy: Empirical Observations of Airbnb
10/31 Joe Hand, Dat TBD
11/7 TBD
11/14 TBD
11/21 TBD
11/28 Susan Crawford, Harvard Law School, and Holly St. Clair, Commonwealth of Massachusetts How Data and Technology Can Help Improve Government
12/5 Andrea Matwyshyn, Northeastern University TBD
12/12 TBD



Re-Identification and the Right to Be Forgotten: a data driven study

Data analysis can be an important tool for policy-makers to evaluate and propose policies for cyberspace governance. In this talk I take a quantitative approach to analyze the content that is being delisted by traditional media outlets (i.e., newspapers and broadcasters) as a consequence of the “Right to be Forgotten” policy. Specifically, I discuss a detailed data analysis of a number of delisted links and the corresponding articles. Based on the delisted links, it is possible to determine the names of requesters and perform a demographic analysis on these requesters. I also discuss possible data-driven attacks that “transparency activists” or other third parties could take to discover delisted links.

Speaker: Virgilio Almeida is a full professor of the Computer Science Department at the Federal University of Minas Gerais (UFMG), Brazil. His areas of research interest include large scale distributed system, Internet governance, social computing, autonomic computing and performance modeling and analysis. He received a Ph.D. degree in Computer Science from Vanderbilt University, an MS in Computer Science, from the Pontifical Catholic University in Rio de Janeiro and a BS Electrical Engineering from UFMG, Brazil. He was a visiting professor at Boston University, Technical University of Catalonia (UPC) in Barcelona, Polytechnic Institute of NYU and held visiting appointments at Santa Fe Institute, Hewlett-Packard Research Laboratory and Xerox Research Center.

He is a former National Secretary for Information Technology Policies of the Ministry of Science, Technology and Innovation of Brazil (2011 to 2015). He is the chair of the Brazilian Internet Governance Committee ( He was the chair of NETmundial, Global Multistakeholder Conference on the Future of Internet Governance, that was held in Sao Paulo in 2014.

He published over 150 technical papers and co-authored five books on performance modeling od computer systems, including "Performance By Design" (2004) "Capacity Planning for Web Services" (2002), and "Scaling for E-business" (2000) published by Prentice Hall. He has supervised more 50 PhD theses and MSc dissertations. Prof. Almeida is a full member of the Brazilian Academy of Sciences.

He is currently a Visiting Professor at School of Engineering and Applied Sciences at Harvard University and a Fellow at Berkman Center for Internet & Society.


Increasing the transparency of online algorithms

We have recently entered the era of "big data", where the online activities of billions of people are now routinely collected and analyzed. This explosion of data has led to the development of numerous algorithms for tasks as diverse as online content recommendations, dynamic pricing of goods, and prediction of criminal activity. However, external observers---including researchers, lawmakers, and regulators---typically have only limited visibility into such systems, as both the algorithm itself and the input data are typically considered proprietary. As a result, the increasingly popularity of these systems has brought up significant concerns about their fairness, transparency, and potential discrimination.

In this talk, I discuss my group's recent work that aims to increase the transparency of these systems via online algorithmic auditing. We have developed techniques that allow an external observer to determine properties of the algorithms, such as the extent to which outputs vary between users and the most important input features used to generate outputs. I describe our results from applying our techniques to three different real-world systems: content personalization in Google search, price discrimination in popular e-commerce retailers, and the surge pricing algorithm in Uber. Overall, our results offer a first step towards increasing the transparency of big data algorithms.

Speaker: Alan Mislove is an Associate Professor at the College of Computer and Information Science at Northeastern University. He received his Ph.D. from Rice University in 2009. Prof. Mislove’s research concerns distributed systems and networks, with a focus on using social networks to enhance the security, privacy, and efficiency of newly emerging systems. He is a recipient of an NSF CAREER Award (2011), and his work has been covered by the Wall Street Journal, the New York Times, and the CBS Evening News.


Caught Red Handed: Tracing Information Flows Between Ad Exchanges Using Retargeted Ads

Numerous surveys have shown that Web users are seriously concerned about the loss of privacy associated with online tracking. Alarmingly, these surveys also reveal that people are unaware of the amount of data sharing that occurs between ad exchanges, and thus underestimate the privacy risks associated with online tracking.

In reality, the modern ad ecosystem is fueled by a flow of user data between trackers and ad exchanges. Although online tracking itself is a well-studied phenomenon, the relationships between trackers and ad exchanges remain opaque, and the implications of this data sharing on user privacy sharing are poorly understood.

In this study, we develop a methodology that is able to detect client- and server-side flows of information between arbitrary ad exchanges. Our key insight is to leverage retargeted ads as a mechanism for identifying information flows. Intuitively, our methodology works because it relies on the semantics of how exchanges serve ads, rather than focusing on specific cookie matching mechanisms. Using crawled data on 35,448 ad impressions, we show that our methodology can successfully categorize four different kinds of information sharing between ad exchanges, including cases were existing heuristic methods fails.

Speaker: Christo Wilson is an Assistant Professor in the College of Computer and Information Science at Northeastern University. Professor Wilson's research focuses on Algorithmic Auditing, which is the process of examining black box systems to understand how they work, the data they use, and ultimately how these algorithms impact individuals. To date, he has examined systems like personalization on Google Search, price discrimination in e-commerce, and surge pricing on Uber. Professor Wilson got his PhD from the University of California, Santa Barbara, and his research is supported by the NSF, the European Commission, the Knight Foundation, and the Data Transparency Lab.

10/10 None

Reputational Justice: Transparency vs. Equity in the Information Society

The data industry has evolved the practice of online user profiling from its humble origins as a means to target advertising into the “reputation economy, where, in order to succeed, individuals must work to build and maintain positive digital profiles while data brokers aim to render them completely transparent. While there may be social benefits to increasing transparency and reducing information asymmetries among transactants in business and social interactions, aspects of the reputation economy also present serious risks to cherished values, legal protections, and hard-fought struggles for social equity. Questions arise about data bias and the power of machine inference to surface sensitive or protected information that would be unavailable or off-limits to decision makers in a less connected world. In this talk I discuss the emergence of reputation as an important socio-technical feature of the information society. I also offer a blueprint for confronting some of the moral hazards of algorithmically derived reputation using a multi-agent negotiation approach in order to perpetuate and assert the intent of existing social policies and legal norms in the data ecosystem.

Speaker: Mike Katell is a PhD student at the University of Washington Information School where he is a research assistant in the Tech Policy Lab and a member of the Value Sensitive Design Lab. His work concerns the ethics of information systems and employs the tools of critical design to address questions of race, gender, and class equity in the information society.


Witnessing the Rise of the Sharing Economy: Empirical Observations of Airbnb

Peer-to-peer markets, collectively known as the sharing economy, have emerged as alternative suppliers of goods and services traditionally provided by long-established industries. Hosts offering short-term accommodations on Airbnb, for example, act as hoteliers on a micro-entrepreneurial scale: they market their properties, set prices, manage their online reputation, and decide how much to invest in cleaning, customer service and upkeep. Moreover, they receive continuous public feedback in the form of ratings and reviews left by their guests.

With the unprecedented visibility enabled by datasets collected from sharing economy platforms, data scientists are busy investigating research questions ranging from racial discrimination to reputation management strategies to the economic impacts on incumbent firms. I will discuss our research on Airbnb's differentiated impacts on the hotel industry in the state of Texas, where we identify a causal impact on hotel revenue in the 8-10% range in Austin, the city seeing the greatest impact. I will also touch on some of the nuances of interpreting user-generated ratings in our study of reputation at over 600,000 Airbnb properties worldwide.

Speaker: John Byers is a Professor of Computer Science at Boston University, which he joined in 1999. He is also founding Chief Scientist of Cogo Labs, a technology incubator in Kendall Square, where he has held an executive role since 2005. Professor Byers's academic research centers on data-analytic and algorithmic challenges in two disciplines: the empirical study of Internet platforms and the science of computer networking. His recent research studies the effectiveness of e-commerce platforms such as Groupon, the utility of rating and review sites such as Yelp and TripAdvisor, and the broader impact of sharing economy firms such as Airbnb. His research has been covered in the New York Times, The Economist, in TIME magazine, on NPR, and on Bloomberg TV. Dr. Byers received his B.A. from Cornell University and his Ph.D. in Computer Science at the University of California at Berkeley (1997).

10/31 TBD

How Data and Technology Can Help Improve Government

This will be a brainstorming session on the ways data and technology can improve local government. The session begins with a presentation by Susan Crawford. Her recent book The Responsive City highlights the promising intersection of government and data through vivid case studies featuring municipal pioneers and big data success stories from Boston, Chicago, New York, and more. She explores topics including:

  • Building trust in the public sector and fostering a sustained, collective voice among communities
  • Using data-smart governance to preempt and predict problems while improving quality of life
  • Creating efficiencies and saving taxpayer money with digital tools
  • Spearheading these new approaches to government with innovative leadership

Holly St. Clair will respond and provide a few words about her thoughts and vision for the State of Massachusetts.

Then, the remainder of the session will be spent brainstorming ideas for how data and technology can help improve government. What are some low-hanging opportunities?

Speakers: Susan Crawford is a professor at Harvard Law School and a co-director of the Berkman Center. She is the author of Captive Audience: The Telecom Industry and Monopoly Power in the New Gilded Age, co-author of The Responsive City: Engaging Communities Through Data-Smart Governance, and a contributor to’s Backchannel. She served as Special Assistant to the President for Science, Technology, and Innovation Policy (2009) and co-led the FCC transition team between the Bush and Obama administrations. She also served as a member of Mayor Michael Bloomberg’s Advisory Council on Technology and Innovation and is now a member of Mayor Bill de Blasio’s Broadband Task Force. Ms. Crawford was formerly a (Visiting) Stanton Professor of the First Amendment at Harvard’s Kennedy School, a Visiting Professor at Harvard Law School, and a Professor at the University of Michigan Law School (2008-2010). As an academic, she teaches Internet law and communications law. She was a member of the board of directors of ICANN from 2005-2008 and is the founder of OneWebDay, a global Earth Day for the internet that takes place each Sept. 22. One of Politico’s 50 Thinkers, Doers and Visionaries Transforming Politics in 2015; one of Fast Company’s Most Influential Women in Technology (2009); IP3 Awardee (2010); one of Prospect Magazine’s Top Ten Brains of the Digital Future (2011); and one of TIME Magazine’s Tech 40: The Most Influential Minds in Tech (2013). Ms. Crawford received her B.A. and J.D. from Yale University.

Holly St. Clair is the Director of Enterprise Level Data Management overseeing the Commonwealth of Massachusett's activities in data management, data analysis, research, and public access to data. Ms. St. Clair has pioneered the use of advanced decision support tools in Metropolitan Boston, managing a variety of projects that use scenarios modeling, community indicators, and innovative meeting formats to engage stakeholders in dialogue about policy choices. She has a excellent track record in public sector innovation and is recognized by Planetizen as one of the Leading Thinkers and Innovators in the field of Urban Planning and Technology.

12/5 TBD

Prior Sessions

Spring 2016 | Fall 2015 | Spring 2014 | Fall 2013 | Spring 2013 | Fall 2012 | Spring 2012 | Fall 2011

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