Are machine learning corpora “fair dealing” under Canadian law?
dc.contributor.author | Brown, Dan | |
dc.contributor.author | Byl, Lauren | |
dc.contributor.author | Grossman, Maura R. | |
dc.date.accessioned | 2021-11-17T21:56:58Z | |
dc.date.available | 2021-11-17T21:56:58Z | |
dc.date.issued | 2021-09 | |
dc.description.abstract | We 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 corpus | en |
dc.description.sponsorship | The work of authors DB and MRG is supported by the Natural Sciences and Engineering Research Council of Canada. | en |
dc.identifier.uri | http://hdl.handle.net/10012/17708 | |
dc.language.iso | en | en |
dc.publisher | Proceedings of the 12th International Conference on Computational Creativity | en |
dc.subject | copyright | en |
dc.subject | fair dealing | en |
dc.subject | computational creativity | en |
dc.subject | corpora | en |
dc.subject | text generation | en |
dc.title | Are machine learning corpora “fair dealing” under Canadian law? | en |
dc.type | Conference Paper | en |
uws.contributor.affiliation1 | Faculty of Mathematics | en |
uws.contributor.affiliation1 | Waterloo Library | en |
uws.contributor.affiliation2 | David R. Cheriton School of Computer Science | en |
uws.contributor.affiliation2 | Waterloo Library | en |
uws.peerReviewStatus | Reviewed | en |
uws.scholarLevel | Faculty | en |
uws.scholarLevel | Librarian | en |
uws.typeOfResource | Text | en |