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 |