@article {Gentili2020,
	title = {Are machines stealing our jobs?},
	journal = {Cambridge Journal of Regions, Economy and Society},
	volume = {13},
	number = {1},
	year = {2020},
	pages = {153{\textendash}173},
	abstract = {This study aims to contribute empirical evidence to the debate about the future of work in an increasingly robotised world. We implement a data-driven approach to study the technological transition in six leading Organisation for Economic Co-operation and Development (OECD) countries. First, we perform a cross-country and cross-sector cluster analysis based on the OECD-STAN database. Second, using the International Federation of Robotics database, we bridge these results with those regarding the sectoral density of robots. We show that the process of robotisation is industry- and country-sensitive. In the future, participants in the political and academic debate may be split into optimists and pessimists regarding the future of human labour; however, the two stances may not be contradictory.},
	keywords = {cluster analysis, e24, e66, j24, jel classifications, labour dislocation, robotisation},
	issn = {1752-1378},
	doi = {10.1093/cjres/rsz025},
	author = {Gentili, Andrea and Compagnucci, Fabiano and Gallegati, Mauro and Valentini, Enzo}
}
@conference {Sushina2020,
	title = {Artificial Intelligence in the Criminal Justice System: Leading Trends and Possibilities},
	booktitle = {Proceedings of the 6th International Conference on Social, economic, and academic leadership (ICSEAL-6-2019)},
	volume = {441},
	year = {2020},
	pages = {432{\textendash}437},
	publisher = {Atlantis Press},
	organization = {Atlantis Press},
	address = {Paris, France},
	keywords = {artificial intelligence, criminal justice system, digital technologies, Leadership},
	isbn = {978-94-6252-974-8},
	doi = {10.2991/assehr.k.200526.062},
	url = {https://www.atlantis-press.com/article/125940991},
	author = {Sushina, Tatyana and Sobenin, Andrew}
}
@article {Acemoglu2020,
	title = {Competing with Robots: Firm-Level Evidence from France},
	journal = {AEA Papers and Proceedings},
	volume = {110},
	year = {2020},
	pages = {383{\textendash}388},
	abstract = {We study the firm-level implications of robot adoption in France. Of 55,390 firms in our sample, 598 adopted robots between 2010 and 2015, but these firms accounted for 20 percent of manufacturing employment. Adopters experienced significant declines in labor shares, the share of production workers in employment, and increases in value added and productivity. They expand their overall employment as well. However, this expansion comes at the expense of competitors, leading to an overall negative association between adoption and employment. Robot adoption has a large impact on the labor share because adopters are larger and grow faster than their competitors.},
	keywords = {automation, competition, j23, j24, jel codes, l11, labor share, manufacturing, productivity, reallocation, robots, tasks},
	issn = {2574-0768},
	doi = {10.1257/pandp.20201003},
	author = {Acemoglu, Daron and Lelarge, Claire and Restrepo, Pascual}
}
@conference {Martnez-Plumed2020,
	title = {Does AI qualify for the job? A bidirectional model mapping labour and AI intensities},
	booktitle = {AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society},
	year = {2020},
	pages = {94{\textendash}100},
	abstract = {In this paper we present a setting for examining the relation between the distribution of research intensity in AI research and the relevance for a range of work tasks (and occupations) in current and simulated scenarios. We perform a mapping between labour and AI using a set of cognitive abilities as an intermediate layer. This setting favours a two-way interpretation to analyse (1) what impact current or simulated AI research activity has or would have on labour-related tasks and occupations, and (2) what areas of AI research activity would be responsible for a desired or undesired effect on specific labour tasks and occupations. Concretely, in our analysis we map 59 generic labour-related tasks from several worker surveys and databases to 14 cognitive abilities from the cognitive science literature, and these to a comprehensive list of 328 AI benchmarks used to evaluate progress in AI techniques. We provide this model and its implementation as a tool for simulations. We also show the effectiveness of our setting with some illustrative examples.},
	keywords = {AI benchmarks, AI impact, AI intensity, Labour market, Simulation, tasks},
	isbn = {9781450371100},
	doi = {10.1145/3375627.3375831},
	author = {Mart{\textquoteright}nez-Plumed, Fernando and Tolan, Song{\textquoteright}l and Pesole, Annarosa and Hern{\textquoteright}ndez-Orallo, Jos{\'e} and Fern{\textquoteright}ndez-Mac{\textquoteright}as, Enrique and G{\textquoteright}mez, Emilia}
}
@article {Abeliansky2020,
	title = {The Future of Work: Challenges for Job Creation Due to Global Demographic Change and Automation},
	journal = {IZA Discussion Paper Series},
	number = {12962},
	year = {2020},
	keywords = {demography, labor, unemployment},
	url = {www.iza.org},
	author = {Abeliansky, Ana and Algur, Eda and Bloom, David E and Prettner, Klaus}
}
@article {EganadelSol2020,
	title = {The Future of Work in Developing Economies},
	journal = {MIT Sloan Management Review},
	volume = {61},
	number = {2},
	year = {2020},
	pages = {1{\textendash}3},
	abstract = {<p>Much has been written about the rise of automation in developed countries. Economists have been busily creating models seeking to quantify the likely impact of automation on employment. However, far less has been written about the potential effects on work in developing nations. This is surprising, given that automation may be especially troublesome for developing economies. Here, del Sol and Joyce examine the effects of large-scale automation on workers in developing countries.</p>},
	keywords = {Armenia, Asia, Austria, automation, Bolivia, Business And Economics{\textendash}Management, China, Developing countries{\textendash}LDCs, Employment, future, Georgia (country), Ghana, Impact analysis, Kenya, Kuala Lumpur Malaysia, Laos, Republic of North Macedonia, South Korea, Sri Lanka, United States{\textendash}US, Vietnam, Workers},
	issn = {15329194},
	author = {Egana del Sol, Pablo and Joyce, Connor and Del Sol, Pablo Ega{\~n}a and Joyce, Connor}
}
@article {Jung2020,
	title = {Industrial robots, employment growth, and labor cost: A simultaneous equation analysis},
	journal = {Technological Forecasting and Social Change},
	volume = {159},
	number = {June},
	year = {2020},
	pages = {120202},
	publisher = {Elsevier},
	abstract = {In recent years, the global rapid expansion of industrial robots has induced ever-increasing concerns for the cause and effect of such growth, particularly with regard to its relationship with labor. This paper analyzes the factors underlying the adoption of industrial robots, employment growth and structure, and labor costs, taking into account the two-way causalities between these variables. For the empirical analysis, we use the three-stage least squares (3SLS) method for the system of simultaneous equations and apply it to the panel data constructed for 42 countries. Explanatory variables for each equation include the dependent variables of other equations and exogenous variables, such as the labor market environment, physical and human capital, and country-specific social environment. The empirical results of the present study indicate that the increase in both unit labor costs and hourly compensation level induces an extensive application of industrial robots. Subsequently, the expansion of industrial robots leads to a reduction of unit labor costs; however, the hourly compensation level increases, implying that the productivity-enhancing effect exceeds the wage-increasing effect of industrial robots. The extensive use of industrial robots tends to suppress employment growth, confirming the labor-substituting effect of industrial robots; the observed trend disproportionately affects low-skilled labor.},
	keywords = {Compensation level, Employment growth, Industrial robots, Labor cost, Simultaneous equation analysis},
	issn = {00401625},
	doi = {10.1016/j.techfore.2020.120202},
	url = {https://doi.org/10.1016/j.techfore.2020.120202},
	author = {Jung, Jin Hwa and Lim, Dong Geon}
}
@booklet {Grimshaw2020,
	title = {International organisations and the future of work: How new technologies and inequality shaped the narratives in 2019},
	howpublished = {Journal of Industrial Relations},
	volume = {62},
	number = {3},
	year = {2020},
	pages = {477{\textendash}507},
	abstract = {In a critical review of seven prominent flagship reports from five international organisations {\textendash} the International Labour Organization (ILO), Organisation for Economic Co-operation and Development (OECD), United Nations Industrial Development Organization (UNIDO), United Nations Development Programme (UNDP) and World Bank {\textendash} this article explores how the policy narratives set out during 2019 and early 2020 have characterised the major future of work challenges associated with new technologies and inequality. It identifies some similarities in viewpoints, including about the unevenness of job changes caused by new technologies and about the declining labour income share, a key measure of inequality. However, there are major points of differentiation. The ILO, OECD and UNDP express serious concerns about the interaction between new technologies and growing inequalities, on the one hand, and a rise in precarious work, concentration of corporate power and erosion of labour bargaining power on the other. Also, UNIDO emphasises the inequalities in technological capacities between developed and developing countries, which make it difficult for markets to distribute the gains from growth evenly. While the World Bank makes some concessions, it remains less open to real-world heterodox evidence about how labour markets function in society. The World Bank aside, there is a growing consensus that labour institutions around the world need to be reinvigorated in order to respond to the challenges facing the future of work.},
	keywords = {future of work, Inequality, International Labour Organization, international organisations, labour income share, new technologies},
	issn = {14729296},
	doi = {10.1177/0022185620913129},
	author = {Grimshaw, Damian}
}
@article {2018,
	title = {Artificial intelligence, jobs,  inequality and productivity:  Does aggregate demand matter},
	number = {ISSN 1871-9872},
	year = {2018},
	publisher = {Maastricht University},
	keywords = {artificial intelligence, economics of automation, growth theory, innovation, labour demand, productivity, technology},
	url = {http://ftp.iza.org/dp12005.pdf},
	author = {Thomas Gries and Wim Naude}
}
@article {2018,
	title = {The discourse approach to boundary identification and corpus construction for theory review articles},
	journal = {Journal of the Association for Information Systems},
	year = {2018},
	keywords = {article identification, boundary identification, citation search, keyword search, literature review, machine learning, research review, review article},
	url = {https://www.researchgate.net/publication/325215971_Understanding_the_Elephant_The_Discourse_Approach_to_Boundary_Identification_and_Corpus_Construction_for_Theory_Review_Articles},
	author = {Kai R. Larsen and Dirik S. Hovorka and Alan R. Dennis and Jevin D. West}
}
@article {2018,
	title = {The future of work in the light of technological change},
	volume = {UDC: 005.32:005.95/.96},
	year = {2018},
	type = {Original Scientific Paper},
	abstract = {Abstract: Technological unemployment, a phenomenon that has been relevant for decades, is now
reaching a new dimension. There is a growing number of discussions about whether technology is the
main culprit for the rising trend of unemployment rates around the world, therefore, the paper discusses the impact of technological changes on the labour market. We conducted a survey in Slovenian
companies with more than 100 employees in order to find out their view on replacing workers with
technology, as well as the reasons and consequences of new technology. We discussed the results of our
research and the views, findings and suggestions of various authors. We have found that technological
unemployment is not a simple problem, as this phenomenon is intertwined with various issues, and
that technology presents various dangers which may at first seem less visible.},
	keywords = {Impact of technology on the labour market, Labour market, Technological unemployment},
	url = {http://media3.novi.economicsandlaw.org/2017/07/Vol23/IJEAL-23-09.pdf},
	author = {Vesna Novak and Denis Dizdarevic}
}
@proceedings {2018,
	title = {A literature Analysis of Research on Artificial Intelligence in Management Information System (MIS)},
	year = {2018},
	abstract = {This article presents an overview of Artificial Intelligence (AI) research applied in the Management Information System field by analyzing the databases of the AIS journal basket list representing the major international journal on MIS. AN initial set of 438 published papers was identified based on our search criteria. From those, 74 were selected because of their appropriate fit with the research questions. They were organized into domains, type of research, data collection strategy and AI techniques. We found; (1) MIS Quarterly published 42\% of the papers; (2) 50\% of studies were on Information Systems applications, followed by 15\% on Knowledge Management; and (3) 7 AI techniques were presented. This paper provides an overview of applied AI in Management, highlights the most studies related topics and techniques and contributes to a research agenda on the subject.},
	keywords = {artificial intelligence, Information Systems, Literature Analysis},
	author = {Alexandre Moreira Nascimento and Maria Alexandra V. C. da Cunha and Fernando de Souza Meirelles and Eusebio Scornavacca and Vinicius Veloso de Melo}
}
