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TL;DR
A June–July 2026 survey of 8,234 working-age adults in four countries found that most respondents would leave their jobs for guaranteed income below their current salary, but about one in five would stay even at 120% of pay. The findings come from an October 29 arXiv preprint, not a peer-reviewed study, and describe stated preferences rather than observed behavior or the effects of AI on employment.
A survey of 8,234 working-age adults in the United States, United Kingdom, Denmark and India found that about one in five respondents would not quit even if offered guaranteed income equal to 120% of their current salary, with health coverage, pension and paid leave intact. The findings appear in an October 29 arXiv preprint by Julian Jacobs of the University of Oxford and Google DeepMind, which examines what people value in work as AI raises concerns about jobs.
The survey’s central question asked respondents whether they would voluntarily quit if offered guaranteed income at steps from 60% to 120% of their current salary, while keeping health coverage, pension and paid leave. The paper reports that a slight majority would leave at 80% of pay, around three-quarters at 100%, and about 20% would still decline at 120%. Among respondents who accepted an offer, the median point at which they would quit was 70% of salary.
The author also grouped respondents by the job values they rated most highly. Among those classified, the paper reports that 33% prioritized the work itself, including purpose, learning or contribution; 23% prioritized colleagues and belonging; 17% status and recognition; and 26% pay and benefits. The paper’s figure says 73.7% put a nonfinancial reason first. The share primarily motivated by the work itself was similar across household-income groups, at 32% for low-income, 33% for middle-income and 34% for high-income respondents.
On perceived AI risk, 40% of white-collar respondents said AI was at least somewhat likely to replace their job within 10 years, compared with 29% of manual and service workers. These are survey responses about expectations, not forecasts of actual job losses. The paper reports associations between work values and views about AI, but says its analysis is relational, not causal.
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 Income Cannot Measure
The findings speak to a policy question likely to grow as AI changes tasks and occupations: could income support make up for work that disappears? The paper’s results suggest that respondents weigh more than wages when thinking about their jobs. Purpose, learning, contribution, workplace relationships and recognition may also matter, though the study does not measure what people would do if their jobs actually vanished.
For employers and policymakers, that distinction matters. Replacing lost earnings with cash could address some financial effects of job disruption, but it may not replace the social connections, routine or sense of contribution that some people associate with work. The study does not establish which policies would address those losses, or whether the responses would translate into real decisions. Its contribution is to document a range of stated priorities—not to show that one income policy will succeed or fail.
The results also resist a simple picture of workers as either attached to a calling or motivated only by money. Most respondents said they would leave under at least one guaranteed-income offer, while a substantial minority would stay even at the highest amount tested. The coexistence of those responses is relevant to debates over automation, income guarantees and the future organization of work.
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How the Survey Was Conducted
The 39-page paper, What is Work For? Labor, Politics, and Meaning in the Age of AI, is a single-author preprint by Julian Jacobs, affiliated with the University of Oxford and Google DeepMind. It was submitted to arXiv on October 29, 2026, in General Economics. It has not been peer-reviewed, and later versions may change its analysis or results.
The online survey was conducted by polling organization More in Common in June and July 2026. It included 2,032 respondents in Denmark, 2,072 in India, 2,052 in the UK and 2,078 in the US. The study used national quotas for age, gender, education and region. The paper says the survey was supported by Google DeepMind, the author’s employer, and that its views do not necessarily reflect those of Oxford or DeepMind.
Respondents rated job-related priorities, answered the guaranteed-income question and were asked about how they might spend their time, their perceived AI-related job risk and political attitudes. The paper uses cross-sectional regression models with controls including income, occupation, age, gender, education, part-time work and country. It records stated answers at one point in time; it does not track people’s choices over time or observe the consequences of AI adoption.
“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, author of the preprint
Limits of Stated Preferences
The survey asks respondents to imagine a guaranteed-income offer; it does not show whether they would actually leave a job under those conditions. Responses may differ when people face real choices involving career prospects, household expenses, identity or uncertainty about future income. The study also cannot establish whether AI will eliminate specific jobs or how quickly changes might occur.
The results are from an online sample in four countries, and the paper notes a particular limitation in its India sample: respondents were younger, more urban and more highly educated than the country’s population overall. Cross-country figures therefore need care in interpretation. The preprint has not been peer-reviewed, and its reported associations do not establish that work values cause particular political views or reactions to AI.
The supplied account reports that purpose- and community-oriented respondents became more pessimistic when they expected AI to harm jobs in their industry. However, the paper’s tables did not find significant differences between the work-value groups in populist voting intention. The size and direction of any real-world political effects remain uncertain.
Peer Review and Follow-Up Evidence
The immediate next step is further scrutiny of the preprint’s methods and results. Because the paper is not peer-reviewed, its findings may change in later versions or after review. Readers should also watch for research that tests whether stated willingness to quit predicts actual choices, and whether the patterns hold in more representative samples and additional countries.
As AI-related changes continue, evidence from workplaces and labor-market data will be needed to establish which tasks and jobs change, how workers respond, and what happens to income and workplace ties. For now, the study offers a survey snapshot of how respondents value work and perceive risk—not a measured account of AI-driven job displacement or a verdict on which policies will address it.
Key Questions
What did the survey find about guaranteed income and quitting?
The paper reports that a slight majority of respondents would leave at 80% of their current salary, around three-quarters at 100%, and about one in five would still refuse at 120%. The offers included health coverage, pension and paid leave.
Does the study show that AI is replacing these workers’ jobs?
No. It reports workers’ perceptions of the likelihood that AI could replace their jobs within 10 years. It does not measure actual job replacement or establish that AI caused job losses.
Is the paper peer-reviewed?
No. It was posted to arXiv on October 29, 2026, as a preprint and has not been peer-reviewed. Its findings may change in later versions.
Who conducted and funded the survey?
More in Common conducted the online survey in June and July 2026. The paper says the survey was supported by Google DeepMind, where author Julian Jacobs is employed.
Can the findings predict whether people would really quit?
Not on their own. The responses were given to a hypothetical offer, so they show stated preferences rather than observed behavior. The paper also describes its analysis as relational rather than causal.
Source: ThorstenMeyerAI.com
