2019
DOI: 10.2478/izajolp-2019-0004
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Economics of Artificial Intelligence: Implications for the Future of Work

Abstract: The current wave of technological change based on advancements in artificial intelligence (AI) has created widespread fear of job loss and further rises in inequality. This paper discusses the rationale for these fears, highlighting the specific nature of AI and comparing previous waves of automation and robotization with the current advancements made possible by a widespread adoption of AI. It argues that large opportunities in terms of increases in productivity can ensue, including for developing countrie… Show more

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Cited by 174 publications
(113 citation statements)
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References 54 publications
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“…On the other side, automation technologies have received much criticism in terms of job losses and technological unemployment due to replacement of human employees (Leonhard, 2016;McClure, 2018;Spencer, 2018), privacy issues (Berle, 2020;Klitou, 2014;Przegalinska, 2019), or aggravating economic and social inequality (Ernst, Merola, & Samaan, 2019).…”
Section: Automation Technologies In Tourismmentioning
confidence: 99%
“…On the other side, automation technologies have received much criticism in terms of job losses and technological unemployment due to replacement of human employees (Leonhard, 2016;McClure, 2018;Spencer, 2018), privacy issues (Berle, 2020;Klitou, 2014;Przegalinska, 2019), or aggravating economic and social inequality (Ernst, Merola, & Samaan, 2019).…”
Section: Automation Technologies In Tourismmentioning
confidence: 99%
“…The use of artificial intelligence therefore seems to determine a decrease in the working hours necessary for production, which has as a consequence an impoverishment of the working middle class. In the coming years, this situation will lead to a labor market that will need personnel to perform AI-related tasks or that will involve creative and relational skills that are difficult to reproduce by means of AI (Ernst et al, 2019).…”
Section: Social Capital and Creativitymentioning
confidence: 99%
“…2 Searches conducted in May 2020. discussing machine learning and data science in relation to specific sub-fields of economics (for example, Kou et al 2019, andHsu et al 2016) were excluded. Similarly articles covering the impact of machine learning and data science as part of a 'future of work'-themed discussion (for example, Ernst, Merola, and Samaan 2019, Agrawal, Gans, and Goldfarb 2018a, 2018b were also not considered. The exclusions were aimed at ensuring that a high-level perspective on potential changes to economics as a field could be collected as part of the findings.…”
Section: Approach To Identifying Relevant Literaturementioning
confidence: 99%