| dc.contributor.author | Berke, Alex | |
| dc.contributor.author | Calacci, Dana | |
| dc.contributor.author | Mahari, Robert | |
| dc.date.accessioned | 2024-10-09T01:50:30Z | |
| dc.date.available | 2024-10-09T01:50:30Z | |
| dc.date.issued | 2022-12-01 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/157133 | |
| dc.description.abstract | In this comment, we urge the FTC to consider rulemaking that empowers consumers to pool and share their data responsibly to help researchers uncover harms such as anti-competitive practices, privacy violations, and algorithmic bias. A large aggregate dataset combined with audit tools would enable the identification of systemic issues otherwise hidden by current corporate practices. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Federal Trade Comission | en_US |
| dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
| dc.subject | Commercial Surveillance | en_US |
| dc.subject | Consumer Data Rights | en_US |
| dc.subject | Data Aggregation for Research | en_US |
| dc.subject | Algorithmic Bias | en_US |
| dc.title | Comment to Federal Trade Commission on Commercial Surveillance | en_US |
| dc.type | Other | en_US |
| dc.identifier.citation | Alex Berke, Dana Calacci, and Robert Mahari. 2022. Comment in response to proposed FTC Trade Regulation Rule on Commercial Surveillance and Data Security: Commercial Surveillance ANPR R111004. | en_US |
