Robots Are Us: Some Economics of Human Replacement
By Seth G. Benzell, L. Kotlikoff, Guillermo Lagarda, Jeffrey D. Sachs. 2015
161 citations recorded by the source corpus.
Will smart machines do to humans what the internal combustion engine did to horses – make them obsolete? If so, can putting people out of work or, at least, good work leave them unable to buy what smart machines produce? Our model’s answer is yes. Over time and under the right conditions, supply reduces demand, leaving everyone worse off in the long-run. Carefully crafted redistribution policies can prevent such immiserating growth. But blunt policies, such as limiting intellectual property rights or restricting labor supply, can make matters worse.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/c0425ac6211a83802914690c8d8d708d93df150b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
Citations in the corpus
- Innovation, automation, and inequality: Policy challenges in the race against the machine (2020, background): “…reasons less related studies on automation and macroeconomic performance are provided by Zeira (2006), Steigum (2011), Peretto and Seater (2013), Benzell et al. (2015), Restrepo (2015), Sachs et al. (2015), Abeliansky and Prettner (2017), Gasteiger and Prettner (2017), Prettner (2017), Cords…”
- Racing with or Against the Machine? Evidence from Europe (2016, unknown): “In particular, Benzell et al. (2015) and Sachs et al. (2015) show that a rise in robotic productivity which substitutes for labor can result in declining product demand if the output produced by robots is sufficiently substitutable for the output produced by humans.”
- Expanding the Impact of the Psychology of Working: Engaging Psychology in the Struggle for Decent Work and Human Rights (2019, background): “in the workplace will dramatically reduce the availability of work, particularly decent work, for millions of people around the world (Benzell et al., 2015; Brynjolfsson & McAfee, 2014; Frey & Osbourne, 2013; National Academy of Sciences, 2017; OECD, 2015; World Economic Forum, 2016).”