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TL;DR
A preprint based on an online survey of 8,234 workers in the UK, US, Denmark and India finds that many rank purpose, community or status above pay as a reason to work. About one in five respondents said they would not quit even for guaranteed income equal to 120% of their salary, though the survey measures stated preferences, not actual choices.
A survey of 8,234 working-age adults in the UK, United States, Denmark and India found that about one in five would not quit even if offered guaranteed income equal to 120% of their current salary, with health cover, pension and paid leave maintained. The results appear in a non-peer-reviewed arXiv preprint by Julian Jacobs of the University of Oxford and Google DeepMind, examining what workers might lose beyond pay if artificial intelligence reduces demand for human labor.
The paper, titled What is Work For? Labor, Politics, and Meaning in the Age of AI, was submitted to arXiv on October 29, 2026. Its online survey was conducted by More in Common in June and July, with roughly 2,000 respondents each from the four countries. The paper says the survey was supported by Google DeepMind, Jacobs’ employer, and that its views do not necessarily reflect the organizations’ positions.
Respondents were asked whether they would voluntarily quit at successive guaranteed-income offers, from 60% of their salary up to 120%, while retaining specified benefits. According to the paper, a slight majority would leave at 80% of salary, about three-quarters at 100%, and roughly 20% would still refuse at 120%. Among respondents who accepted an offer, the median point at which they would quit was 70% of salary. These are answers to a hypothetical question, not observed decisions.
The survey also grouped workers by the reasons they said mattered in a job. Of those the paper could classify, 33% were primarily motivated by the work itself, including purpose, learning or contribution; 23% by colleagues and belonging; 17% by status and recognition; and 26% by pay and benefits. The paper reports that 73.7% put a non-financial reason first. The categories reflect the survey’s classification method, rather than a direct measure of how people behave at work.
WHAT WORK IS FOR, ACCORDING TO WORKERS
Three in four put something other than pay first
The paper sorts workers by what they rate most important in their job. In its own figure, 73.7% of classified workers put a non-money reason first.
The work itself: purpose, learning, contributing to society.
Pay and benefits come first.
Belonging, colleagues, meeting people.
Recognition and prestige.
Pay-first share, by country
Share of classified workers whose top value is pay and benefits
Meaning is not a luxury
Share driven by the work itself (intrinsic), by household income third
Also about a third in craft and trade jobs (33%) and in services and sales (31%).
Shares of the 6,224 working respondents the paper could classify; 2,010 respondents (non-working, or no clear top value) were left out. 2,000 tied answers were assigned by a tie-break rule. Satisfied with their job: 81%.
Source: Jacobs, What is Work For?, arXiv:2610.39375v1, 29 Oct 2026 · preprint, not peer-reviewed · survey of 8,234 working-age adults in the UK, US, Denmark and India by More in Common, June–July 2026, supported by Google DeepMind.
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What Workers May Lose Beyond Pay
The findings speak to a central question in debates over automation: if AI displaces jobs, would replacing lost wages also replace what people get from working? The survey suggests that many respondents say their jobs provide purpose, social ties or recognition, alongside income. That makes the impact of job loss harder to describe using wages alone, and is relevant to discussions of income support and how employers might respond to automation.
Jacobs argues that a basic income may be necessary in an AI-related labor shock but could fail to compensate workers fully for the non-financial benefits of work. That is an interpretation of stated survey responses, not evidence that a basic income would fail in practice. The paper does not test an actual income-support program or track people who have lost jobs to AI.
The paper also reports that 40% of white-collar respondents considered AI at least somewhat likely to replace their job within ten years, compared with 29% of manual and service workers. Those figures record respondents’ expectations; they are not forecasts of job losses. They offer a snapshot of perceived exposure, which can shape how workers think about their future and how policymakers assess public concerns.
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How the Survey Framed Work
The study used a nine-item battery asking how much respondents valued features of their jobs, including pay, benefits, purpose, learning, contribution to society, belonging, meeting people and social status. It then sorted responses into four “Work Values Profiles” and compared them with answers to the guaranteed-income question, questions about how respondents would spend their time, and views about AI and politics.
The author used cross-sectional regression models with controls for factors including income, occupation, age, gender, education, part-time work and country. The paper reports that purpose-driven respondents required about 1.9 to 5.8 percentage points more guaranteed income than pay-driven respondents before saying they would quit, depending on the model. At a $60,000 salary, the paper translates that difference to roughly $1,100 to $3,500 a year. These are model-based associations, not proof that a worker’s motivation causes a particular quitting decision.
The paper’s political findings are less conclusive. It reports that purpose- and community-driven respondents were more pessimistic when they expected AI to harm jobs in their industry, but its tables found no significant difference between the groups in populist vote intention. Jacobs describes the analysis as “purely relational, not causal.”
“A basic income “may indeed be necessary” in an AI labor shock, but “could ultimately fail to compensate workers” for what work gives beyond money.”
— Julian Jacobs, paper author
Limits of the Survey Evidence
The paper is a version-one preprint and has not been peer-reviewed; the author says its numbers could change in later versions. The survey records what respondents said they would do in a hypothetical scenario, not whether they would leave a job after receiving such an offer. It also does not establish how AI will change employment or whether non-financial benefits can be replaced through other forms of social or community life.
The country samples were recruited online using quotas for age, gender, education and region, and the results should not automatically be treated as fully representative of each national workforce. The paper flags the India sample as younger, more urban and more educated than India as a whole. The relationship between work values and political attitudes is also not causal, and the reported lack of a significant difference in populist vote intention does not establish that no relationship exists.
Peer Review and Further Evidence
The next formal milestone is any revision or peer review of the October 29 arXiv preprint; the source material does not identify a journal submission or review timetable. Later versions may change the estimates or address questions about sample representativeness and the interpretation of the work-value categories.
For now, the results are best read as evidence about how surveyed adults describe their jobs and respond to a hypothetical offer. Establishing how AI affects employment, whether workers actually choose to leave when income is guaranteed, and how those who lose work value purpose or community would require evidence beyond this survey.
Key Questions
What did the survey find about quitting for guaranteed income?
The paper reports that about three-quarters would quit at 100% of salary, while roughly one in five would still refuse at 120%, with health cover, pension and paid leave retained. These were hypothetical responses.
Who conducted the research?
The preprint was written by Julian Jacobs, affiliated with the University of Oxford and Google DeepMind. More in Common conducted the online survey, which the paper says was supported by Google DeepMind.
Has the paper been peer-reviewed?
No. The paper was posted to arXiv as a version-one preprint on October 29, 2026, and had not been peer-reviewed according to the source material.
Does the study show that AI will replace 40% of white-collar jobs?
No. The paper says 40% of surveyed white-collar workers thought AI was at least somewhat likely to replace their job within ten years. That is a measure of respondents’ expectations, not a forecast of the share of jobs that will disappear.
Source: ThorstenMeyerAI.com
