@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}
}
@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}
}
@booklet {Willcocks2020,
	title = {Robo-Apocalypse cancelled? Reframing the automation and future of work debate},
	howpublished = {Journal of Information Technology},
	number = {2016},
	year = {2020},
	abstract = {Robotics and the automation of knowledge work, often referred to as AI (artificial intelligence), are presented in the media as likely to have massive impacts, for better or worse, on jobs skills, organizations and society. The article deconstructs the dominant hype-and-fear narrative. Claims on net job loss emerge as exaggerated, but there will be considerable skills disruption and change in the major global economies over the next 12 years. The term AI has been hijacked, in order to suggest much more going on technologically than can be the case. The article reviews critically the research evidence so far, including the author{\textquoteright}s own, pointing to eight major qualifiers to the dominant discourse of major net job loss from a seamless, overwhelming AI wave sweeping fast through the major economies. The article questions many assumptions: that automation creates few jobs short or long term; that whole jobs can be automated; that the technology is perfectible; that organizations can seamlessly and quickly deploy AI; that humans are machines that can be replicated; and that it is politically, socially and economically feasible to apply these technologies. A major omission in all studies is factoring in dramatic increases in the amount of work to be done. Adding in ageing populations, productivity gaps and skills shortages predicted across many G20 countries, the danger might be too little, rather than too much labour. The article concludes that, if there is going to be a Robo-Apocalypse, this will be from a collective failure to adjust to skills change over the next 12 years. But the debate needs to be widened to the impact of eight other technologies that AI insufficiently represents in the popular imagination and that, in combination, could cause a techno-apocalypse.},
	keywords = {AI, automation, cognitive automation, future of work, Information Technology, Jobs, robotic process automation, skills},
	isbn = {0268396220925},
	issn = {14664437},
	doi = {10.1177/0268396220925830},
	author = {Willcocks, Leslie}
}
@article {Clifton2020,
	title = {When machines think for us: The consequences for work and place},
	journal = {Cambridge Journal of Regions, Economy and Society},
	volume = {13},
	number = {1},
	year = {2020},
	pages = {3{\textendash}23},
	abstract = {The relationship between technology and work, and concerns about the displacement effects of technology and the organisation of work, have a long history. The last decade has seen the proliferation of academic papers, consultancy reports and news articles about the possible effects of Artificial Intelligence (AI) on work-creating visions of both utopian and dystopian workplace futures. AI has the potential to transform the demand for labour, the nature of work and operational infrastructure by solving complex problems with high efficiency and speed. However, despite hundreds of reports and studies, AI remains an enigma, a newly emerging technology, and its rate of adoption and implications for the structure of work are still only beginning to be understood. The current anxiety about labour displacement anticipates the growth and direct use of AI. Yet, in many ways, at present AI is likely being overestimated in terms of impact. Still, an increasing body of research argues the consequences for work will be highly uneven and depend on a range of factors, including place, economic activity, business culture, education levels and gender, among others. We appraise the history and the blurry boundaries around the definitions of AI. We explore the debates around the extent of job augmentation, substitution, destruction and displacement by examining the empirical basis of claims, rather than mere projections. Explorations of corporate reactions to the prospects of AI penetration, and the role of consultancies in prodding firms to embrace the technology, represent another perspective onto our inquiry. We conclude by exploring the impacts of AI changes in the quantity and quality of labour on a range of social, geographic and governmental outcomes.},
	keywords = {artificial intelligence, automation, bias in machine learning, geography of technology, job displacement and growth},
	issn = {17521386},
	doi = {10.1093/cjres/rsaa004},
	author = {Clifton, Judith and Clifton, Judith and Glasmeier, Amy and Gray, Mia}
}
@article {2019,
	title = {Applying for your next job may be an automated nightmare},
	journal = {Gizmodo},
	year = {2019},
	month = {04/2019},
	type = {Automation},
	keywords = {automation, job},
	url = {https://gizmodo.com/applying-for-your-next-job-may-be-an-automated-nightmar-1834275825},
	author = {Brian Merchant}
}
