Show simple item record

dc.contributor.authorGundersen, Odd Erik
dc.date.accessioned2020-03-16T12:25:35Z
dc.date.available2020-03-16T12:25:35Z
dc.date.created2020-02-03T12:51:44Z
dc.date.issued2019
dc.identifier.citationThe AI Magazine. 2019, 40 (4), 9-23.nb_NO
dc.identifier.issn0738-4602
dc.identifier.urihttp://hdl.handle.net/11250/2646980
dc.description.abstractA recent study implies that research presented at top artificial intelligence conferences is not documented well enough for the research to be reproduced. My objective was to investigate whether the quality of the documentation is the same for industry and academic research or if differences actually exist. My hypothesis is that industry and academic research presented at top artificial intelligence conferences is equally well documented. A total of 325 International Joint Conferences on Artificial Intelligence and Association for the Advancement of Artificial Intelligence research papers reporting empirical studies have been surveyed. Of these, 268 were conducted by academia, 47 were collaborations, and 10 were conducted by the industry. A set of 16 variables, which specifies how well the research is documented, was reviewed for each paper and each variable was analyzed individually. Three reproducibility metrics were used for assessing the documentation quality of each paper. The findings indicate that academic research does score higher than industry and collaborations on all three reproducibility metrics. Academic research also scores highest on 15 out of the 16 surveyed variables. The result is statistically significant for 3 out of the 16 variables, but none of the reproducibility metrics. The conclusion is that the results are not statistically significant, but still indicate that my hypothesis probably should be refuted. This is surprising, as the conferences use double-blind peer review and all research is judged according to the same standards.nb_NO
dc.language.isoengnb_NO
dc.publisherAssociation for the Advancement of Artificial Intelligencenb_NO
dc.titleStanding on the feet of giants - Reproducibility in AInb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber9-23nb_NO
dc.source.volume40nb_NO
dc.source.journalThe AI Magazinenb_NO
dc.source.issue4nb_NO
dc.identifier.doi10.1609/aimag.v40i4.5185
dc.identifier.cristin1790176
dc.description.localcode© 2019. This is the authors' accepted and refereed manuscript to the article. The final authenticated version is available online at: http://dx.doi.org/10.1609/aimag.v40i4.5185nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record