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40% of time you spend on chores could be automated within next 10 years

17 March 2023

A new study suggests that automated household chores could help increase domestic gender equality.

(Image: Shutterstock)
(Image: Shutterstock)

Four in 10 hours currently devoted to unpaid housework and domestic care responsibilities could be automated within the decade, according to research, from the University of Oxford and Japan’s Ochanomizu University, in the journal PLOS ONE.

Among household tasks, time spent on grocery shopping was seen as the most automatable. On average, experts predicted time currently spent on this task would fall by nearly 60 percent. 

Meanwhile, respondents believed the time spent on physical childcare would only be reduced by 21 percent as a result of automation.

Dr Lulu Shi, a postdoctoral researcher with the Oxford Internet Institute, says, “Our research suggests, on average, around 39 percent of our time spent on domestic work can be automated in the next ten years.

“The degree of automation varies substantially across different types of work, however, only 28 percent of care work, including activities such as teaching your child, accompanying your child or taking care of an older family member, is predicted to be automated. 

“Yet, 44 percent of the housework, including cooking, cleaning, and shopping, are expected to be automatable.”
The findings are based on responses from AI experts in the UK and Japan, when asked what difference automation was going to make to housework and other unpaid work. The researchers found the estimates were influenced by the personal background of the experts.

Ekaterina Hertog, Associate Professor in AI and Society, Oxford Internet Institute and Ethics in AI Institute, explains, “We found male and female experts had different expectations about automation of domestic work, potentially reflecting the differences in their lived experiences with technology, as well as their involvement in housework and care work.”

The research found male UK experts tended to be more optimistic about domestic automation compared with their female counterparts. This is in line with previous studies, which show men tend to be more optimistic about technology than women. 

But this was reversed for Japanese male and female experts – and the authors speculate the Japanese gender disparity in household tasks could play a role in these results.

According to the study, the general level of optimism in respect of domestic automation also varied by country. On average, UK-based experts thought automation could reduce domestic work time by 42 percent, compared with a 36 percent reduction expected by Japanese respondents. The authors suggest this may be because technology is associated more with labour replacement in the UK. In Japan, meanwhile, new smart technologies are expected to work alongside humans, rather than replace them.

Previous studies show that working-age people in the UK spend nearly 50 percent of all their work and study time on unpaid domestic work such as cooking, cleaning, and care. 

The new findings suggest a large potential increase in leisure time as domestic tasks get automated.

The effects are likely to affect women more than men, however. In the UK, working-age men spend around half as much time on domestic unpaid work as working-age women. 

In Japan, the difference in time spent on domestic tasks is even more striking, with Japanese men spending just 18 percent of the time spent by women on domestic tasks. 

Technologies that save time currently spent on domestic work could, therefore, result in greater gender equality at home, according to the researchers.

The study involved 29 male and female AI experts from the UK and 36 experts from Japan. They were asked to estimate the degree to which 17 housework and care tasks might be automated over the next decade. 

The study’s diverse sample is not statistically representative but, as the authors note, the experts’ backgrounds offer the potential for contextualising their predictions.

Few studies have examined the automation of unpaid domestic work or predictions about automation and how they differ – depending on the AI experts consulted.

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