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dc.contributor.authorSuresh, Harini
dc.contributor.authorGuttag, John
dc.date.accessioned2022-11-03T15:42:55Z
dc.date.available2022-11-03T15:42:55Z
dc.date.issued2021-10-05
dc.identifier.isbn978-1-4503-8553-4
dc.identifier.urihttps://hdl.handle.net/1721.1/146108
dc.publisherACM|Equity and Access in Algorithms, Mechanisms, and Optimizationen_US
dc.relation.isversionofhttps://doi.org/10.1145/3465416.3483305en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/en_US
dc.sourceACM|Equity and Access in Algorithms, Mechanisms, and Optimizationen_US
dc.titleA Framework of Potential Sources of Harm Throughout the Machine Learning Life Cycleen_US
dc.typeArticleen_US
dc.identifier.citationSuresh, Harini and Guttag, John. 2021. "A Framework of Potential Sources of Harm Throughout the Machine Learning Life Cycle."
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-11-02T22:06:07Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2022-11-02T22:06:07Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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