Award Abstract # 2047827
CAREER: Usable, Data-Driven Transparency and Access for Consumer Privacy

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: UNIVERSITY OF CHICAGO
Initial Amendment Date: February 9, 2021
Latest Amendment Date: August 30, 2024
Award Number: 2047827
Award Instrument: Continuing Grant
Program Manager: Dan Cosley
dcosley@nsf.gov
 (703)292-8832
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: April 1, 2021
End Date: March 31, 2026 (Estimated)
Total Intended Award Amount: $549,510.00
Total Awarded Amount to Date: $549,510.00
Funds Obligated to Date: FY 2021 = $103,721.00
FY 2022 = $105,884.00

FY 2023 = $110,613.00

FY 2024 = $229,292.00
History of Investigator:
  • Blase Ur (Principal Investigator)
    blase@uchicago.edu
Recipient Sponsored Research Office: University of Chicago
5801 S ELLIS AVE
CHICAGO
IL  US  60637-5418
(773)702-8669
Sponsor Congressional District: 01
Primary Place of Performance: University of Chicago
IL  US  60636-2612
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): ZUE9HKT2CLC9
Parent UEI: ZUE9HKT2CLC9
NSF Program(s): Secure &Trustworthy Cyberspace
Primary Program Source: 01002526DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 025Z, 1045
Program Element Code(s): 806000
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Data collected about consumers underpins online personalization, yet raises critical privacy concerns. Mitigating these concerns requires giving consumers awareness and access to, data collected about them. To date, though, consumers have been given limited insight through these mechanisms. Attempts to provide awareness have centered on static disclosures of limited utility. Access rights for collected data have mostly been ignored or manifested as meaningless database exports. Unfortunately, consumers struggle to learn what has been collected, by whom, and especially what this collection implies for their privacy. This project aims to improve data transparency and access rights by developing novel models, user interactions, and open-source privacy tools. These techniques and tools will empower consumers to protect their privacy in a data-driven world. Furthermore, the project will enhance education and outreach. The investigator will develop a pilot program for engaging early-career students in research, create a new privacy course for underprivileged high school students, and both develop and exhibit artworks designed to provoke reflection on individual privacy, by collaborating with the School of the Art Institute of Chicago and the Chicago Museum of Science and Industry.

The project will center around the intellectual development of complementary tools that give consumers data-driven insight into (i) the huge archives companies give consumers who exercise data-access rights and (ii) the online third-party tracking ecosystem. Several intellectual challenges stand in the way. First, usable transparency about voluminous data requires automatic methods that surface the information that matters most to consumers. The project will address this challenge through formative user studies and the iterative development and evaluation of a data-access tool. In addition, the project will develop new techniques for identifying, integrating, and visualizing data archives. Second, because the raw data collected about a consumer provides only partial transparency, the project will develop new methods for communicating, in an individualized manner, inferences possible from data. Third, as transparency is powerless without recourse, the project will understand the types of recourse users desire and develop tools that identify and mitigate privacy-tool-related website breakage at scale.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Reitinger, Nathan and Wen, Bruce and Mazurek, Michelle L. and Ur, Blase "Analysis of Google Ads Settings Over Time: Updated, Individualized, Accurate, and Filtered" , 2023 https://doi.org/10.1145/3603216.3624968 Citation Details
Barbosa, Natã M. and Wang, Gang and Ur, Blase and Wang, Yang "Who Am I?: A Design Probe Exploring Real-Time Transparency about Online and Offline User Profiling Underlying Targeted Ads" Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , v.5 , 2021 https://doi.org/10.1145/3478122 Citation Details
Borem, Arthur and Pan, Elleen and Obielodan, Olufunmilola and Roubinowitz, Aurelie and Dovichi, Luca and Mazurek, Michelle L. and Ur, Blase "Data Subjects Reactions to Exercising Their Right of Access" , 2024 Citation Details
Harrison, Galen and Bryson, Kevin and Bamba, Ahmad Emmanuel and Dovichi, Luca and Binion, Aleksander Herrmann and Borem, Arthur and Ur, Blase "JupyterLab in Retrograde: Contextual Notifications That Highlight Fairness and Bias Issues for Data Scientists" , 2024 Citation Details
Nisenoff, Alexandra and Borem, Arthur and Pickering, Madison and Nakanishi, Grant and Thumpasery, Maya and Ur, Blase "Defining "Broken": User Experiences and Remediation Tactics When Ad-Blocking or Tracking-Protection Tools Break a Websites User Experience" Proceedings of the 32nd USENIX Security Symposium , 2023 Citation Details
Reitinger, Nathan and Wen, Bruce and Mazurek, Michelle L and Ur, Blase "What Does It Mean to Be Creepy? Responses to Visualizations of Personal Browsing Activity, Online Tracking, and Targeted Ads" Proceedings on Privacy Enhancing Technologies , v.2024 , 2024 https://doi.org/10.56553/popets-2024-0101 Citation Details
Veys, Sophie and Serrano, Daniel and Stamos, Madison and Herman, Margot and Reitinger, Nathan and Mazurek, Michelle L and Ur, Blase "Pursuing Usable and Useful Data Downloads Under GDPR/CCPA Access Rights via Co-Design" Proceedings of the USENIX Symposium on Usable Privacy and Security (SOUPS) 2021 , 2021 Citation Details

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