Event Description
Big data analytics promise to solve weighty social problems. Yet, which stakeholders drive big data questions? How can computer scientists, community groups and social scientists work together to build on what we know about power, surveillance, privacy and collaboration? How can we make sure that a commitment to equity is central to big data analytics? This two-day workshop aims to discuss how to build ethical big data practices with leading scholars and practitioners. The workshop will start Thursday, September 29, 2016 at 8 AM and end on Friday, September 20, 2016 at 2:30 PM. Breakfast and lunch will be provided on both days. Thursday, September 29, 2016 8-8:50 AM: Registration and Continental Breakfast
9-9:30 AM: Big Data, Disciplinary Expertise, and Building Community for Empirical Ethics
In May 2014, the White House issued a report on the promise of big data, while also warning of the risks to core values such as equality, privacy and access to knowledge. We all want big data to help communities address major social problems. As we embark on creating and using big data sets, questions such as who defines relevant research problems, which disciplines and expertise drive big data work and what that means for the work that gets done emerge. Kelly Joyce, Drexel University
Susan Sterett, Virginia Tech 9:30-11 AM: Professional Challenges to Collaboration: Asking Good Questions, Developing Useful Answers
Disciplinary expertise and research methods often drive big data questions and research. This panel highlights examples of big data research driven by disciplinary expertise. Practitioners offer alternative ways to draw upon different types of expertise to build big data teams. This panel highlights the benefits and challenges of collaboration across disciplines and with a variety of stakeholders. Chair:Justin Abold-LaBreche, IRS
Srinivas Aluru, Representative from South Data Hub
Eta Davis, Fairfax County Government
Michelle Rogers, Drexel University, “Impact of Health Care Data on Work Practices”
Discussant: Hugh Gusterson, George Washington University
11:15 AM-12:15 PM: Keynote: Ana Diez Roux, Dean of Dornsife School of Public Health, Drexel University 12:30-1:30 PM: Lunch -All Attendees Welcome
1:30-3 PM: Data Veracity and Model Validity as Ethical Challenges
The ethics of big data often focuses on privacy. The hope we will act on data analytics in governing makes the expanding the big data ethics conversation to include issues of veracity and validity crucial. How do different disciplines understand and verify validity? How do these notions of validity relate to local stakeholders’ concerns?
Chair: Mark Orr, Virginia Tech
Naren Ramakrishnan, Virginia Tech, "Modeling Population-level Activity Using Open Source Data"
Edgar Chou, Drexel University, “Designing Consequences of Health Care Data into the Questions”
Discussant: Kevin Finneran, National Academy of Sciences (NAS)
3:15-4:45 PM: Conceptualizing Privacy: Producers, Users, and Institutions
Ideas of privacy are built into technical infrastructures. What are the prevailing understandings of privacy? Which values drive current notions of privacy? How are these materialized in big data projects? What are the political effect of such choices?
Chair: Adam Eckerd, Virginia Tech
Meg Leta Jones, Georgetown University
Michael Planty, Bureau of Justice Statistics, U.S. Department of Justice: The Role of Privacy in the Design and Dissenination of National Statistical Data
Sallie Keller, Virginia Tech: Does Big Data Change the Privacy Landscape
Discussant: Kelly Moore, Loyola University, Chicago
5-6:30 PM: Reception - All Attendees Welcome
Friday, September 30, 2016
8-8:50 AM: Registration and Continental Breakfast
9-10:30 AM: Inequalities, Surveillance and Data Analytics
In May 2016, The White House issued a report on data analytics and civil rights. The report argues that analytics promise fairer practices in access to credit, higher education, employment discrimination and criminal justice. The report also argues that predictive analytics in policing could contribute to increasing safety and trust. What practices would support the use of data analytics that could contribute to equality? What practices would contribute to the risk of increased surveillance that does not contribute to equality?
Chair: Sara Jordan, Virginia Tech
Solon Barocas, Yale University
Torin Monahan, University of North Carolina, Chapel Hill
TBD, City of Arlington
Discussant: Barbara Allen, Virginia Tech
10:45 AM-12:15 PM: Using Big Data: Reworking Professional Practices and Relationships
Discussion of data analytics recognizes the multiple skills that are required for good analytics, and that the multiple skills will not belong to only one person, or to a group of people with similar training and perspectives. The MetroLab Network is a new effort to contribute to collaboration, and to build capabilities distributed across members of teams. Yet collaboration when people work on different timelines with different professional knowledge and commitments is difficult. What contributes to fruitful, ethical collaborations?
Chair: Michelle Cullen, IBM
Karen Levy, NYU/Cornell
Katie Shilton, University of Maryland
Suzanne Thomas,Intel Labs
Discussant: Sudipta Sarangi, Economics, VT
12:30-1:30 PM: Working Lunch - All Attendees Welcome
What problems are you working on? What are you missing? Who do you need to work with? What are some of the professional or institutional barriers that make it harder to produce socially-meaningful, big data research? Lunch will be provided.
1:45-2:30 PM: Closing Remarks
Kelly Joyce, Drexel University
Susan Sterett, Virginia Tech
This workshop is open to the public, but is currently at capacity. To see if spots have opened up on the waitlist, go to: https://www.eventbrite.com/e/big-data-ethics-workshop-tickets-25936000275
This workshop is supported by the National Science Foundation under grant number 1623445. |
