Abstract
This paper uses and recycles data from a third-party digital marketing firm, to explore how targeted ads contribute to larger systems of racial discrimination. Focusing on a case study of targeted ads for educational searches in New York City, it discusses data visualizations and mappings of trends in the advertisements' targeted populations alongside U.S census data corresponding to these target zipcodes. We summarize and reflect on the results to consider how internet platforms systemically and differentially target advertising messages to users based on race; the tangible harms and risks that result from an internet traffic system designed to discriminate; and finally, novel approaches and frameworks for further auditing systems amid opaque, black-boxed processes forestalling transparency and accountability.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022 |
| Editors | Tung X. Bui |
| Publisher | IEEE Computer Society |
| Pages | 2806-2815 |
| Number of pages | 10 |
| ISBN (Electronic) | 9780998133157 |
| State | Published - 2022 |
| Event | 55th Annual Hawaii International Conference on System Sciences, HICSS 2022 - Virtual, Online, United States Duration: Jan 3 2022 → Jan 7 2022 |
Publication series
| Name | Proceedings of the Annual Hawaii International Conference on System Sciences |
|---|---|
| Volume | 2022-January |
| ISSN (Print) | 1530-1605 |
Conference
| Conference | 55th Annual Hawaii International Conference on System Sciences, HICSS 2022 |
|---|---|
| Country/Territory | United States |
| City | Virtual, Online |
| Period | 1/3/22 → 1/7/22 |
Keywords
- algorithmic audits
- data ethics
- discrimination
- education
- race
ASJC Scopus subject areas
- General Engineering