@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}
}
