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

无偿工作的未来：人工智能改变英国和日本无偿家务工作的潜力

• 批准号: ES/T007265/1
• 负责人: Ekaterina Hertog
• 金额: $ 52.33万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FT007265%2F1
• 关键词: Future; Unpaid; Work; AI; potential

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.

“工作的未来”近年来备受关注。在了解新技术对未来就业和培训的影响方面作出了重大努力。相比之下，无报酬家务工作的未来却很少受到关注。尽管英国的工作年龄成年人将所有有偿和无偿工作时间的56%用于家务和护理工作，但日本的这一数字为38%。人工智能驱动的技术取代了家务劳动，可能会为所有年龄段的男性和女性腾出大量时间。它也有可能使人们花在难以自动化的家务工作上的时间，或者人们想自己做的家务工作（例如互动式儿童保育或老年人护理），更有效率，并有助于将其整合为更少的片段。该项目将把无报酬的家务工作纳入人工智能和劳动力未来的讨论，并评估其在两个社会和文化截然不同的国家的影响。为此，我们将考虑多种因素，这些因素将影响人工智能驱动的省时国内技术在三个不同的工作包（WP）中的传播。在WP 1中，我们将首先使用英国时间使用调查2014-15中确定的大约50个此类任务的网格来评估国内工作任务自动化的技术可能性，我们将应用广泛使用的Frey-Osborne方法的修改版本来测量自动化。然后，我们将使用一个专家小组来评估人工智能驱动的国内技术不仅在技术上可行，而且家庭负担得起的速度。在WP 2中，我们将解决影响家庭智能机器采用的社会因素。我们将首先分析购物的情况，通常在人工智能应用程序的帮助下离线或在线进行。英国和日本是电子商务的全球领导者，这使得这些国家的在线购物成为一个很好的测试案例，可以分析使用人工智能技术执行家庭任务与不使用人工智能技术执行家庭任务的不同之处。人工智能技术如何影响日常时间使用以及不同家庭成员参与活动的比例？然后，我们将进行一项实验性的小插曲调查，以评估将一系列国内任务外包给人工智能技术的可接受性。我们的小插图将描述一个虚构的家庭情况，其中执行一项特定的家庭任务。在这些小插曲中，我们将随机改变一些核心因素，如任务类型，家庭收入，小插曲将由调查问题补充，询问在家庭成员不同意的情况下如何决定采用国内技术。WP 3涉及使用国家时间转移中使用的方法模拟不同年龄男性和女性无报酬工作时间的可能变化账户（NTTA）。国家技术转让协定使用时间使用数据来显示不同年龄组和性别的人如何生产和消费用于家庭中各种无报酬工作的时间，估计国家一级这些群体之间的净时间转移。我们将估计家庭任务自动化的未来情景，并评估英国和日本未来跨性别和代际的时间转移，并将预期的人口变化和自动化考虑在内。我们将依靠WP 1和WP 2中开发的自动化、可负担性和可接受性评分。我们还将开发一个场景，在这个场景中，家庭任务的自动化将导致类似于WP 2中分析的人工智能购物技术所带来的变化。我们的分析将把今天主要由妇女从事的无形家务劳动纳入“工作的未来”辩论。它将丰富我们对时间的理解，我们拥有的最稀缺的资源，将如何受到国内人工智能技术的影响。

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• DOI: 10.2139/ssrn.4178929
• 发表时间: 2022
• 期刊: SSRN Electronic Journal
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“The future of unpaid work: Estimating the effects of automation on time spent on housework and care work in Japan and the UK”

“无酬工作的未来：评估自动化对日本和英国家务和护理工作时间的影响”

• DOI: 10.31235/osf.io/swe7n
• 发表时间: 2023
• 期刊: Technological Forecasting and Social Change
• 影响因子: 12
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• 通讯作者: Vili

The future of unpaid work: Estimating the effects of automation on time spent on housework and care work in Japan and the UK

无酬工作的未来：评估自动化对日本和英国家务和护理工作时间的影响

• DOI: 10.1016/j.techfore.2023.122443
• 发表时间: 2023
• 期刊: Technological Forecasting and Social Change
• 影响因子: 12
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