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TL;DR
A preprint by Julian Jacobs reports responses from 8,234 working-age adults in four countries to questions about work, guaranteed income and AI. Most said they would leave their jobs for a guaranteed income below their current salary, but about one in five said they would not leave even at 120%; the survey measures stated preferences, not actual behavior.
A new, unreviewed research paper reports that about one in five of 8,234 working-age adults surveyed would not quit their job even if offered guaranteed income equal to 120% of their salary, with health cover, pension and paid leave retained. The study, by Julian Jacobs of the University of Oxford and Google DeepMind, examines what work provides beyond pay as artificial intelligence raises questions about employment; its results reflect answers to a hypothetical survey, not observed decisions.
The paper, What is Work For? Labor, Politics, and Meaning in the Age of AI, was posted to arXiv on October 29, 2026. It draws on an online survey fielded in June and July by polling organization More in Common, with 2,032 respondents in Denmark, 2,072 in India, 2,052 in the United Kingdom and 2,078 in the United States. The paper is a 39-page preprint and has not been peer-reviewed.
In the survey’s income-offer exercise, respondents were asked whether they would voluntarily quit for guaranteed income starting at 60% of current salary and rising in 10-point steps to 120%, while keeping specified benefits. A slight majority would leave at 80% of salary; around three-quarters would do so at 100%. At the highest offer, about 20% said they would stay. Among respondents who accepted an offer, the median reported quit point was 70% of salary.
The author also groups respondents by what they say matters in a job. Among 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’s figure reports that 73.7% placed a non-financial reason first. These figures describe the survey’s categories and answers, not a direct measurement 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 Income Cannot Measure
The findings matter to debates about how societies and employers might respond if AI changes demand for human labor. If work gives some people purpose, social ties, learning or recognition, income support alone may not replace those benefits. Jacobs argues that a basic income may be necessary in an AI-related labor shock but could fail to compensate workers for what they gain from work beyond money. That is the author’s interpretation of survey responses, not a demonstrated outcome of an actual policy.
The paper also complicates a simple picture of work as either a financial necessity or a source of meaning. Most respondents in the hypothetical exercise would leave for an offer below their current pay, while a substantial minority said they would not leave even for more. The holdout share was reported as 21% among low-income, 18% among middle-income and 22% among high-income respondents. Those results suggest that stated attachment to work was not confined to the highest-income group in this sample.
For employers, the results may be relevant to questions about how jobs are designed if AI automates some tasks. But the survey does not test whether particular workplace programs, job changes or income policies improve well-being. Its evidence is best read as a measure of stated preferences and concerns, not a forecast of how workers will respond to automation.
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How the Survey Framed Work
The study uses a nine-item set of questions about job priorities, including pay and benefits, purpose, learning, social contribution, belonging, meeting people and status. It also asks respondents what they would do with their time if they stopped working, and asks about perceived AI-related job threats and political attitudes. The analysis uses cross-sectional regression models with controls including income, occupation, age, gender, education, part-time work and country.
The paper reports that 40% of white-collar respondents considered it at least somewhat likely that AI would replace their job within ten years, compared with 29% of manual and service workers. These are respondents’ expectations, not estimates of actual job losses. The paper also says purpose- and community-motivated respondents became more pessimistic when they expected AI to harm jobs in their industry, while its tables found no significant difference between work-value groups in populist vote intention.
The survey was supported by Google DeepMind, Jacobs’s employer, according to the paper. It says the views expressed do not necessarily reflect those of Oxford or DeepMind. The author describes the analysis as “purely relational, not causal,” meaning it identifies associations in the survey rather than showing that one factor caused another.
““purely relational, not causal.””
— Julian Jacobs, in the paper
Limits of the Evidence
The results are based on a single online survey and hypothetical choices. They cannot show whether respondents would actually quit, or whether their answers would change if offered a real guaranteed income. The preprint has not been peer-reviewed, and its findings may change in later versions.
The country samples used quotas for age, gender, education and region, but the paper flags a particular limitation in India: its online respondents were younger, more urban and more educated than the country’s population overall. The reported 28.8% holdout rate there should be read with that sample limitation in mind. More broadly, the survey covers four countries and does not establish that the same patterns apply elsewhere.
The data also do not show how automation will affect actual employment, wages or job quality. While respondents reported varying levels of concern about AI replacing jobs, those perceptions are not forecasts. The paper’s political findings are limited too: its analysis does not establish causal links, and it reports no significant difference in populist vote intention across the work-value groups.
Peer Review and Further Evidence
The next research milestone is whether the paper receives peer review and whether later versions revise its analysis or conclusions. Because it is currently an arXiv preprint, readers should treat its findings as provisional research, not as settled evidence about the effects of AI on work.
Further evidence would need to examine real choices over time, including how workers respond to actual changes in pay, benefits, job duties or employment. The survey does not set out a confirmed policy timetable or establish that AI-driven job losses will occur at the rates respondents fear. For now, it offers a snapshot of how people in four countries describe the value of work and respond to a hypothetical income offer.
Key Questions
What did the survey find about quitting for guaranteed income?
A slight majority said they would leave at 80% of current salary, and around three-quarters at 100%. About one in five said they would stay even at 120%, with benefits retained.
Does the study show that basic income cannot replace work?
No. That is the author’s interpretation of stated preferences. The survey did not test a real basic-income policy or observe whether people quit after receiving guaranteed payments.
Has the research been peer-reviewed?
No. The paper was posted to arXiv on October 29, 2026, as a preprint. Its results and conclusions may change.
How worried were respondents about AI replacing their jobs?
The paper reports that 40% of white-collar respondents thought replacement within ten years was at least somewhat likely, compared with 29% of manual and service workers. These figures reflect reported expectations, not predictions of actual job losses.
Who funded the survey?
The paper says the survey was supported by Google DeepMind, Jacobs’s employer. It also states that the views in the paper do not necessarily reflect those of DeepMind or the University of Oxford.
Source: ThorstenMeyerAI.com
