The Future of Unpaid Work: AI's potential to transform unpaid domestic work in the UK and Japan

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The "Future of Work" has attracted much attention in recent years. Significant efforts are directed at understanding the implications of new technologies for the future of employment and training. In contrast, the future of unpaid domestic work has received little attention. This is although working-age adults in the UK spend about 56% of all paid and unpaid work time on household and care work; the figure for Japan is 38%. AI-powered technology replacing human labour in domestic tasks can potentially free up large amounts of time for men and women of all ages. It also has the potential to make the time spent on the domestic work that is hard to automate, or that people want to do themselves (e.g. interactive childcare or eldercare), more efficient and help consolidate it into fewer episodes. This project will bring unpaid domestic work into the discussion of AI and the future of labour and assess its implications in two socially and culturally quite distinct countries. To do this we will consider multiple factors that will influence the diffusion of AI-powered time-saving domestic technology in three distinct Work Packages (WP). In WP1 we will first evaluate the technological likelihood of automatibility of domestic work tasks using a grid of around 50 such tasks identified in the UK Time Use Survey 2014-15, to which we will apply a modified version of the widely used Frey-Osborne approach to measuring automatibility. We will then use an expert panel to assess how quickly AI-powered domestic technologies will become not only technologically possible, but also affordable for households. In WP2 we will address social factors affecting the adoption of intelligent machines at home. We will first analyse the case of shopping, commonly carried out offline or online with the help of AI-powered apps. UK and Japan are global leaders in e-commerce, making online shopping in these countries a good test case to analyse how performing a household task with AI-powered technology may differ from performing it without it. How does AI-powered technology affect daily time use and the rates of participation in the activity by different members of the household? We will then carry out an experimental vignette survey to evaluate the acceptability of outsourcing a range of domestic tasks to AI-powered technology. Our vignettes will describe a fictitious family situation in which a given domestic task is performed. Across the vignettes, we will randomly vary a number of core factors such as type of task, family income, who performs the task etc. The vignettes will be supplemented by survey questions asking how decisions to adopt domestic technology are made when family members disagree about it.WP3 involves simulations of likely changes in unpaid work time for men and women of different ages using the methodology used in National Time Transfer Accounts (NTTAs). NTTAs use time use data to show how people of different age groups and gender produce and consume time spent for various kinds of unpaid work in households, estimating net time transfers between such groups on the national level. We will estimate future scenarios of domestic task automation and evaluate future time transfers across genders and between generations in UK and Japan factoring in expected population change and automation. We will rely on automatibility, affordability and acceptability scores developed in WP1 and WP2. We will also develop a scenario in which automation of domestic tasks will result in changes similar to those brought about by AI-powered shopping technology as analysed in WP2. Our analysis will bring invisible domestic labour that today is largely performed by women into the "Future of Work" debate. It will enrich our understanding of how time, the scarcest resource we have, will be influenced by AI-powered technologies at home.