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dc.contributor.authorBrown, Dan
dc.contributor.authorByl, Lauren
dc.contributor.authorGrossman, Maura R.
dc.date.accessioned2021-11-17 21:56:58 (GMT)
dc.date.available2021-11-17 21:56:58 (GMT)
dc.date.issued2021-09
dc.identifier.urihttp://hdl.handle.net/10012/17708
dc.description.abstractWe consider the use of large corpora for training compuationally creative systems, particularly those that write new text based on the style of an existing author or genre. Under Canadian copyright law, a key concern for whether this is “fair dealing” is whether this usage will result in new creations that compete with those in the corpus. While recent law review articles in the United States suggest that training models on such corpora would be “fair use” in the United States, we argue that Canadian law may, in fact, forbid this use when the new products compete with works in the original corpusen
dc.description.sponsorshipThe work of authors DB and MRG is supported by the Natural Sciences and Engineering Research Council of Canada.en
dc.language.isoenen
dc.publisherProceedings of the 12th International Conference on Computational Creativityen
dc.subjectcopyrighten
dc.subjectfair dealingen
dc.subjectcomputational creativityen
dc.subjectcorporaen
dc.subjecttext generationen
dc.titleAre machine learning corpora “fair dealing” under Canadian law?en
dc.typeConference Paperen
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation1Waterloo Libraryen
uws.contributor.affiliation2David R. Cheriton School of Computer Scienceen
uws.contributor.affiliation2Waterloo Libraryen
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen
uws.scholarLevelLibrarianen


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