Why Are There Still So Many Jobs? The History and Future of Workplace

By David H. Autor. 2015

2,117 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/3a8910a977b06c4c89a6cbdce7952e29d1feded2

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In Industrial and Manufacturing Engineering

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Citations in the corpus

Who on Earth Can Work from Home? (2020, background): “This is supported by other studies such as Autor and Dorn (2013) and Autor, Dorn, and Hanson (2015),who find that local labormarketsmore exposed to computerization experienced job polarization.”
The wrong kind of AI? Artificial intelligence and the future of labour demand (2019, neutral): “17See Dreyfus (1992) and Autor (2015).”
Should we fear the robot revolution? (The correct answer is yes) (2018, positive): “Autor (2015) propounds this hypothesis, speculating that the income and price elasticities of demand for nonautomatable (NA) goods and substitutability of labor across sectors will play a large role in determining the outcome.”
What is the future of work? A science mapping analysis (2020, background): “automation and joblessness has developed into more realistic views, that is, many of the middle-skilled jobs of the future will combine routine technical tasks with non-routine tasks, in which employees hold comparative advantages, such as interpersonal interaction, flexibility, adaptability and pro”
The Evolution of Work in the United States (2020, methodology): “Autor, Levy, and Murnane (2003) and Acemoglu and Autor (2011) develop the hypothesis that technological advances have reduced the demand for routine tasks, which, in turn, has led to a reduction in the wages of low- and middle-skill workers.”
Big Data: New Tricks for Econometrics (2014, methodology): “Source: The table is based on that in Ley and Steel (2009); the data analyzed is from Sala-i-Martín (1997). Notes: We illustrate different methods of variable selection.”
Robots at Work (2015, positive): “There is a particularly lively debate on the implications of recent and anticipated developments in robotics and closely related technologies (see, e.g., Brynjolfsson & McAfee, 2014, and Autor, 2015).”
Toward understanding the impact of artificial intelligence on labor (2019, methodology): “As another approach, data on educational requirements can add resolution to employment trends (50 – 52).”
Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy (2019, background): “For those with a more pessimistic bend, more automation meant increased unemployment; the beginning of this idea probably goes back to the luddites (David, 2015), who actively tried to remove machines from the production process as a means to preserve jobs.”
Entrepreneurial spirits in women and men. The role of financial literacy and digital skills (2019, background): “More specifically, Autor (2015) argues that the interplay between machine and human comparative advantage allows computers to substitute for workers in performing routine and codifiable tasks while amplifying the comparative advantage of workers in supplying problemsolving skills, adaptability, and…”
Education for AI, not AI for Education: The Role of Education and Ethics in National AI Policy Strategies (2021, background): “Next, nearly all of the national policy strategies (at least 21 of 24) also include some discussion of labor displacement risks due to automation, and how skill and task content will change (Autor, 2015), urging a need for new policy around education and training (West 2018).”