The Future(s) of Unpaid Work: How Susceptible Do Experts From Different Backgrounds Think the Domestic Sphere Is to Automation

31 Pages Posted: 30 Jan 2022 Last revised: 5 Jan 2023

See all articles by Vili Lehdonvirta

Vili Lehdonvirta

University of Oxford - Oxford Internet Institute

Lulu P. Shi

University of Oxford - Department of Sociology

Ekaterina Hertog

University of Oxford - Department of Sociology

Nobuko Nagase

Ochanomizu University

Yuji Ohta

Ochanomizu University

Date Written: January 5, 2023

Abstract

The future of work has become a prominent topic for research and policy debate. However, the debate has focused entirely on paid work, even though people in industrialized countries on average spend comparable amounts of time on unpaid work. The objectives of this study are therefore (1) to expand the future of work debate to unpaid domestic work and (2) to critique the main methodology used in previous studies. To these ends, we conducted a forecasting exercise in which 65 AI experts from the UK and Japan estimated how automatable are 17 housework and care work tasks. Unlike previous studies, we applied a sociological approach that considers how experts’ diverse backgrounds might shape their estimates. On average our experts predicted that 39 percent of the time spent on a domestic task will be automatable within ten years. Japanese male experts were notably pessimistic about the potentials of domestic automation, a result we interpret through gender disparities in the Japanese household. Our contributions are providing the first quantitative estimates concerning the future of unpaid work and demonstrating how such predictions are socially contingent, with implications to forecasting methodology.

Keywords: artificial intelligence, automation, qualitative forecasting, domestic work, gender

Suggested Citation

Lehdonvirta, Vili and Shi, Lulu and Hertog, Ekaterina and Nagase, Nobuko and Ohta, Yuji, The Future(s) of Unpaid Work: How Susceptible Do Experts From Different Backgrounds Think the Domestic Sphere Is to Automation (January 5, 2023). Available at SSRN: https://ssrn.com/abstract=4017695 or http://dx.doi.org/10.2139/ssrn.4017695

Vili Lehdonvirta (Contact Author)

University of Oxford - Oxford Internet Institute ( email )

1 St. Giles
University of Oxford
Oxford, Oxfordshire OX1 3JS
United Kingdom

HOME PAGE: http://www.oii.ox.ac.uk

Lulu Shi

University of Oxford - Department of Sociology ( email )

Manor Road
Manor Road
Oxford, OX1 3UQ
United Kingdom

Ekaterina Hertog

University of Oxford - Department of Sociology ( email )

Manor Road
Manor Road
Oxford, OX1 3UQ
United Kingdom

Nobuko Nagase

Ochanomizu University ( email )

2-1-1 Ohtsuka
Tokyo, Bunkyo-ku 112-8610
Japan

Yuji Ohta

Ochanomizu University ( email )

2-1-1 Ohtsuka
Tokyo, Bunkyo-ku 112-8610
Japan

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