Presented By: Multi-Ethnic Information Exchange (School of Information)
2016 MIX MLK Lecture
Preventing Big Data Discrimination: Addressing Flawed Notice and Choice Privacy Policy
Please join us for a free lunch and guest lecture on discrimination and ethics in Big Data - on Friday, February 5th from Noon to 1pm in the North Quad room 1255.
The SI student Multi-Ethnic Information Exchange (MIX), the Office of Multi-Ethnic Student Affairs (MESA), and the UMSI Diversity Committee present the 2016 MIX MLK Symposium, featuring Dr. Jonathan Obar, an assistant professor in the Communication and Digital Media Studies program at the University of Ontario Institute of Technology. Dr. Obar will address “Preventing Big Data Discrimination: Addressing Flawed Notice and Choice Privacy Policy.” The program will shed light on how discrimination is unconsciously built into Big Data.
Abstract:
A 2014 White House Report on Big Data suggested that "big data analytics have the potential to eclipse longstanding civil rights protections in how personal information is used in housing, credit, employment, health, education, and the marketplace." In light of growing empirical evidence that forms of discrimination (including racial bias) may already be built-into a mosaic of Big Data approaches, this presentation aims to address a first step for preventing Big Data discrimination. The central argument suggests that consistent and growing evidence that longstanding notice (i.e. privacy policies) and choice (i.e. user access and control of data) privacy policy is deeply flawed, requiring that we both call attention to the failures of the model and propose alternatives. Results from an ongoing quantitative survey analysis co-authored with Dr. Anne Oeldorf-Hirsch (University of Connecticut) demonstrating the extent to which users ignore terms of service and privacy policies online will be presented to demonstrated notice policy flaws. The fallacy of data privacy self-management, an argument recently published by Dr. Obar in "Big Data and Society," will be presented next to argue for flawed choice policy. Representative data management is offered as a pragmatic solution to the challenges faced. A number of startups in the infomediary market will be profiled to justify this proposal.
Bio:
Jonathan Obar is an assistant professor in the Communication and Digital Media Studies program at the University of Ontario Institute of Technology. He also serves as a research associate with the Quello Center for Telecommunication Management and Law at Michigan State University. His research appears in a variety of academic journals and addresses the impact digital technologies have on civil liberties, civic engagement, and the inclusiveness of public culture.
Please RSVP: https://docs.google.com/a/umich.edu/forms/d/1wVmoEUi_SVzCfad3dGG1BtJdp7wtDAB3QrE2Rzjqw1s/viewform?c=0&w=1&usp=mail_form_link
Even though we ask you to RSVP you are still welcome to attend.
The SI student Multi-Ethnic Information Exchange (MIX), the Office of Multi-Ethnic Student Affairs (MESA), and the UMSI Diversity Committee present the 2016 MIX MLK Symposium, featuring Dr. Jonathan Obar, an assistant professor in the Communication and Digital Media Studies program at the University of Ontario Institute of Technology. Dr. Obar will address “Preventing Big Data Discrimination: Addressing Flawed Notice and Choice Privacy Policy.” The program will shed light on how discrimination is unconsciously built into Big Data.
Abstract:
A 2014 White House Report on Big Data suggested that "big data analytics have the potential to eclipse longstanding civil rights protections in how personal information is used in housing, credit, employment, health, education, and the marketplace." In light of growing empirical evidence that forms of discrimination (including racial bias) may already be built-into a mosaic of Big Data approaches, this presentation aims to address a first step for preventing Big Data discrimination. The central argument suggests that consistent and growing evidence that longstanding notice (i.e. privacy policies) and choice (i.e. user access and control of data) privacy policy is deeply flawed, requiring that we both call attention to the failures of the model and propose alternatives. Results from an ongoing quantitative survey analysis co-authored with Dr. Anne Oeldorf-Hirsch (University of Connecticut) demonstrating the extent to which users ignore terms of service and privacy policies online will be presented to demonstrated notice policy flaws. The fallacy of data privacy self-management, an argument recently published by Dr. Obar in "Big Data and Society," will be presented next to argue for flawed choice policy. Representative data management is offered as a pragmatic solution to the challenges faced. A number of startups in the infomediary market will be profiled to justify this proposal.
Bio:
Jonathan Obar is an assistant professor in the Communication and Digital Media Studies program at the University of Ontario Institute of Technology. He also serves as a research associate with the Quello Center for Telecommunication Management and Law at Michigan State University. His research appears in a variety of academic journals and addresses the impact digital technologies have on civil liberties, civic engagement, and the inclusiveness of public culture.
Please RSVP: https://docs.google.com/a/umich.edu/forms/d/1wVmoEUi_SVzCfad3dGG1BtJdp7wtDAB3QrE2Rzjqw1s/viewform?c=0&w=1&usp=mail_form_link
Even though we ask you to RSVP you are still welcome to attend.
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