The impact of Artificial Intelligence on unemployment: a systematic literature review

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dc.contributor.advisor Saccon, Chiara it_IT
dc.contributor.author Dall'Anese, Davide <1994> it_IT
dc.date.accessioned 2020-10-13 it_IT
dc.date.accessioned 2021-02-02T09:54:46Z
dc.date.available 2021-02-02T09:54:46Z
dc.date.issued 2020-11-06 it_IT
dc.identifier.uri http://hdl.handle.net/10579/17930
dc.description.abstract The world is currently witnessing the effects of that period of fast technological advancements which has become known as the “Fourth industrial revolution”. Featuring it, there is the introduction of a broad set of new technologies, like big data and analytics, 3-D printing, the internet of things, and autonomous robots. If, on the one hand, the introduction of Artificial Intelligence allows firms to perform a wide range of tasks more efficiently, on the other hand, there are bad consequences its implementation may lead to. The focus of this thesis is the relationship between employment and Artificial Intelligence. Experts in the AI field and part of the literature warn about the massive technological unemployment that might occur in the near future. The common thinking is that thanks to AI, practically all jobs might be done by machines. In order to find out if the implementation of AI machines leads to unemployment, a systematic literature review is undertaken. The findings show the actual scenario is more complicated, with many factors to be taken into consideration. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Davide Dall'Anese, 2020 it_IT
dc.title The impact of Artificial Intelligence on unemployment: a systematic literature review it_IT
dc.title.alternative The impact of Artificial Intelligence on unemployment: a systematic literature review it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Economia e gestione delle aziende it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Management it_IT
dc.description.academicyear 2019-2020_Sessione autunnale it_IT
dc.rights.accessrights openAccess it_IT
dc.thesis.matricno 867170 it_IT
dc.subject.miur SECS-P/02 POLITICA ECONOMICA it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend it_IT
dc.provenance.upload Davide Dall'Anese (867170@stud.unive.it), 2020-10-13 it_IT
dc.provenance.plagiarycheck Chiara Saccon (csaccon@unive.it), 2020-10-19 it_IT


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