On average, 39 percent of the time currently spent on unpaid domestic work could be automated within the next decade, according to AI experts from the UK and Japan. The results are published on February 22, 2023 in the open access journal PLOS ONE by a team led by Ekaterina Hertog at the University of Oxford, UK, and colleagues in Japan.
According to previous studies, people aged 15 to 64 in the UK spend around 43 per cent of all their work and study time on unpaid housework (housework such as cooking and cleaning, as well as childcare or elders, who could theoretically be delegated to a. paid worker or market goods instead). In the UK, working-age men spend around half as much time as working-age women on such work, while in Japan, the same figure is only 18 per cent. However, few studies to date have examined automation in relation to unpaid domestic work, or how predictions about automation differ depending on the AI experts consulted. The authors of this study asked 29 male and female AI experts from the UK and 36 experts from Japan to estimate how automated 17 housework and care work tasks could become in the next decade.
Experts have predicted that an average of 39 percent of the time people currently spend on any given domestic work task could be automated within the next decade. Estimates varied significantly between tasks, with grocery shopping considered the most automated task (59 percent). The least automated task was physical childcare (21 percent). UK-based experts believed automation could replace more domestic labor (42 percent) than Japanese experts (36 percent). The authors suggest that this may be because technology in the UK is more involved in labor replacement compared to Japan.
UK male experts tended to be more optimistic about domestic automation compared to UK female experts, which is in line with previous studies showing that men tend to be more optimistic about technology than women in general. However, this trend was reversed for Japanese experts, with female experts slightly more positive; the authors consider whether the Japanese gender difference in family tasks plays a role in these results.
Although the study’s diverse sample is not statistically representative of the field and is too small to generalize the results to all AI experts, the authors note that examining the backgrounds of the experts could improve their predictive predictions. put in context. They also highlight how these predictions not only predict the future of work, but also shape it, so that it will be important to bring more cultural and gender diversity to future research.
The authors add: “Our study with technology experts in the UK and Japan shows that domestic automation could, in 10 years, reduce the amount of time spent on housework and current care work tasks by 39%.”