A main aim of the study was understand how experts predict the automation of unpaid domestic work. To do so, we conducted a Delphi survey with technology experts in the UK and Japan. The data set includes answers collected from a forecasting exercise in which 65 AI experts from the UK (29 respondents) and Japan (36 respondents) were asked to estimate how automatable 17 housework and care work tasks are in the next 5 to 10 years. The experts were also asked to estimate the cost of the automations. In addition, background information, such as the experts' gender, age and field of expertise, were collected. Based on the respondents answers, the Delphi survey shows that on average 27% of time that people currently spend on doing unpaid domestic work could be automated in the next 5 years, and 39% in the next 10 years.This project brings unpaid domestic work into the discussion of AI and the future of labour and predicts the degree of automation of unpaid work in two distinct countries – the UK and Japan. To do this we evaluate the technological likelihood of automatibility of domestic work tasks using a grid of 17 such tasks identified in the UK Time Use Survey 2014-15 and the Japanese Survey on Time Use and Leisure Activities 2016. We use a panel consisting of technology experts to assess how quickly AI-powered domestic technologies will become not only technologically possible but also affordable for households.

For the Delphi survey we recruited 65 respondents who are technology experts. 29 respondents are based in the UK, 36 are based in Japan. We consider "technology experts" as people with expert knowledge in AI or AI related technologies, including machine learning, robotics, or the social and/or business aspects of AI related technologies. Our approach was to recruit a balanced number of female and male respondents, as well as a balanced number in three different professional fields: academia, research and development, and business. We recruited the respondents through our own network, through snowball sampling, and through desktop research. We contacted the experts via email and LinkedIn, sending them the invitation to participate in the Delphi survey. Respondents based in the UK were contacted by the UK team using English as the communication language, and respondents based in Japan were contacted by the Japanese team using Japanese as the correspondence language. While Japanese respondents received a small monetary compensation, as it is expected in Japan, the UK respondents did not receive any monetary compensation.