🔍 Read the full analysis: Could AI Leave A Gap Beyond Jobs? A Survey Asks What Work Provides on ThorstenMeyerAI.com
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TL;DR
A preprint analyzing a survey of 8,234 working-age adults in the UK, US, Denmark and India found that about one in five respondents would not quit even if guaranteed income reached 120% of their salary and benefits. The author argues that income support during AI-driven job disruption may not replace work’s non-financial roles, but the survey records stated preferences, not actual behavior, and does not establish that AI will cause the changes discussed.
A preprint posted to arXiv on October 29 reports that about one in five of 8,234 working-age adults surveyed in the UK, US, Denmark and India would not quit a job even if they received guaranteed income equal to 120% of their salary, with health cover, pension and paid leave preserved. The study’s author, Julian Jacobs of the University of Oxford and Google DeepMind, says the responses suggest that money alone may not replace the purpose, social ties and recognition some people get from work as AI changes employment.
The paper, titled What is Work For? Labor, Politics, and Meaning in the Age of AI, is a 39-page, single-author preprint and has not been peer-reviewed. Its results come from an online survey fielded in June and July 2026 by polling organization More in Common. The 8,234 respondents were working-age adults: 2,032 in Denmark, 2,072 in India, 2,052 in the UK and 2,078 in the US. The survey used national quotas for age, gender, education and region.
In the study’s hypothetical income test, respondents were asked whether they would voluntarily leave work if guaranteed income replaced progressively larger shares of their current salary, from 60% to 120%, while benefits remained. The paper reports that a slight majority would leave at 80% of salary, about three in four at 100%, and roughly 20% would stay at 120%. Among respondents who accepted an offer, the median point at which they said they would quit was 70% of salary; the average was 76%. These are answers to a scenario, not records of people leaving actual jobs.
Jacobs grouped respondents’ stated work priorities into four profiles. Among those the paper could classify, 33% were primarily motivated by the work itself, including purpose, learning and contribution; 23% by colleagues and belonging; 17% by status and recognition; and 26% by pay and benefits. The paper reports that 73.7% placed a non-financial 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. The study says the guaranteed-income holdout share also varied little by income: 21% among low-income, 18% among middle-income and 22% among high-income respondents.
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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The findings bear on how governments and employers might respond if AI reduces demand for some kinds of labor. Income support can address lost earnings, but the survey suggests that some respondents also value work for identity, purpose, relationships or recognition. Jacobs argues that a basic income may be necessary in an AI-related labor shock yet could fail to compensate people for those non-monetary parts of work. That is the author’s interpretation of survey answers, not a measured outcome of an AI displacement program.
The reported differences in the amount respondents would require to quit were small after statistical controls. Depending on the model, people primarily motivated by purpose asked for about 1.9 to 5.8 percentage points more guaranteed income than people primarily motivated by pay. The source translates that range to roughly $1,100 to $3,500 a year at a $60,000 salary. The results do not show that purpose-driven workers will necessarily resist job changes, or that creating jobs with greater meaning would prevent unemployment.
The survey also reports different levels of perceived risk: 40% of white-collar respondents considered it at least somewhat likely AI would replace their job within ten years, compared with 29% of manual and service workers. That is a measure of respondents’ expectations, not a forecast of job losses. The distinction matters as policymakers weigh public concern against evidence about what AI will actually do to employment.
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How the Survey Tested Work’s Value
The study used a nine-item battery about what matters in a job, including pay, benefits, purpose, learning, contribution to society, belonging, meeting people and social status. It then asked people to consider a guaranteed-income offer and whether they would quit. The paper also examined how respondents said they would spend their time and asked about AI-related job concerns and political attitudes. Its statistical models use cross-sectional data and account for factors including income, occupation, age, gender, education, part-time work and country.
The author’s affiliation and the study’s funding are relevant to readers’ assessment. The paper says the survey was supported by Google DeepMind, Jacobs’s employer, and states that its views do not necessarily reflect those of Oxford or DeepMind. The source article reports that it found no analysis favoring a company, but that judgment does not change the preprint’s status. Its results may also change in later versions.
The paper’s political analysis is more limited than its work-value findings. It reports that purpose- and community-oriented respondents were more pessimistic when they expected AI to harm jobs in their industry. However, the paper’s tables do not show significant differences among work-value groups in populist vote intention. Jacobs describes the analysis as “purely relational, not causal”, meaning it cannot establish that work values or expectations about AI caused political views.
“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
What the Survey Cannot Establish
The survey measures what respondents say they would do in a hypothetical offer, not whether they would leave a real job with the same terms. The results do not establish how people would respond to an actual basic-income policy, how long their decisions would last or whether their preferences would shift under financial pressure or changing family circumstances.
The paper is a preprint that has not been peer-reviewed, and the source says later versions could change its numbers. Its online samples used national quotas, but the India sample was younger, more urban and more educated than the country as a whole; the reported 28.8% holdout rate there should be read with that limitation in mind. The survey also does not demonstrate that AI will eliminate jobs or specify how many jobs may be affected, when, or in which industries.
It remains unclear whether the reported differences across work-value groups would hold in other populations or under different survey designs. The paper’s cross-sectional analysis also cannot determine whether expectations of AI-related job losses cause pessimism, whether pessimistic people expect more disruption, or whether other factors shape both.
Peer Review and Real-World Evidence
The immediate next step is scrutiny of the paper’s methods and results by researchers and readers; it was posted as version one on October 29, 2026, and no peer-review outcome is given in the source material. Later versions may revise the analysis or figures. The survey was fielded in June and July 2026, so it also does not show whether views have changed since then.
For policy decisions, the open question is how stated preferences compare with behavior when workers face real job losses, guaranteed income and different forms of community or meaningful activity. Evidence from actual programs and labor-market changes would be needed to assess whether income support can address the non-financial losses Jacobs discusses. The source provides no timetable for further data collection or a follow-up study.
Key Questions
What did the survey find about leaving work?
The paper reports that a slight majority of respondents would leave at guaranteed income equal to 80% of salary, about three in four at 100%, and roughly one in five would still stay at 120%, with benefits retained. These were hypothetical answers, not observed job decisions.
Does the study show that AI will take people’s jobs?
No. It records respondents’ views about the likelihood of AI replacing their jobs and discusses possible labor-market disruption. It does not forecast actual job losses or establish that AI will replace a particular number of jobs.
Why might people keep working if income were guaranteed?
The paper groups non-financial motivations such as purpose, learning, contribution, belonging and status. Its results suggest that some respondents value these aspects of work, but the survey does not prove which motivation would determine a real decision to stay.
Has the paper been peer-reviewed?
No. It was posted to arXiv on October 29, 2026, as a preprint. The source says it had not been peer-reviewed and that figures could change in later versions.
Who funded the survey?
The paper says the survey was supported by Google DeepMind, where author Julian Jacobs works. It also says the views do not necessarily reflect those of Google DeepMind or the University of Oxford.
Source: ThorstenMeyerAI.com
