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dc.contributor.authorBerke, Alex
dc.contributor.authorCalacci, Dana
dc.contributor.authorMahari, Robert
dc.date.accessioned2024-10-09T01:50:30Z
dc.date.available2024-10-09T01:50:30Z
dc.date.issued2022-12-01
dc.identifier.urihttps://hdl.handle.net/1721.1/157133
dc.description.abstractIn 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.isoen_USen_US
dc.publisherFederal Trade Comissionen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectCommercial Surveillanceen_US
dc.subjectConsumer Data Rightsen_US
dc.subjectData Aggregation for Researchen_US
dc.subjectAlgorithmic Biasen_US
dc.titleComment to Federal Trade Commission on Commercial Surveillanceen_US
dc.typeOtheren_US
dc.identifier.citationAlex 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


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