“AI Took My Job!”: AI, Bullshit Jobs and Why We Need More Welfare. Author: Marcus Stansbury

“[A farmer] would very likely look at what you do and I do and say, ‘that’s not real work’.”

This is what Sam Altman, CEO of OpenAI, had to say when asked about the prospect of billions of jobs being replaced by artificial intelligence within the coming decades (TOI Tech Desk, 2025). Altman finds this thought experiment makes him “a little less worried” about the looming threat of mass layoffs, but for those of us not worth $1.9 billion (Burleigh, 2025), the hypothetical opinions of imaginary farmers likely provide little comfort. A report by the Institute for Public Policy Research (2024) suggested that 59% of tasks carried out by the UK workforce are “exposed” to businesses deepening AI integration – putting nearly 8 million jobs at risk of becoming redundant – with 11% of all tasks already at risk from current AI technology. Three potential outcomes are modelled in this report: a “worst-case scenario” where all 7.9 million at-risk jobs are displaced; a “central scenario” where 4.4 million jobs disappear; and a “best-case scenario” where jobs are “augmented” to work alongside AI, with no job losses. Notably, the growing threat of AI redundancies is set to predominantly target university-educated, white collar professionals, whose incomes make them both significant tax contributors and ineligible for most all forms of social security. This, especially in the worst-case scenario, has the potential to cause a fiscal “scissor effect” crisis where tax revenues plummet as demand for benefits skyrocket, and economic growth remains stagnant, potentially leading to a recession – something to worry about regardless of whether or not your job is “real”.

The IPPR report outlined that “without government action and with companies left to their own devices, the worst-case scenario is a real possibility”. Now, a little over a year after the publication of this report, it seems the best-case scenario is already off the table, with Amazon having laid off 14,000 corporate employees in favour of AI not two weeks ago (McMahon & Chia, 2025), and Keir Starmer – almost echoing Altman’s complacency – stating “the battle for the jobs of tomorrow is happening today” in a January speech where he set out plans for the UK to become “one of the world’s AI superpowers” (Gillett et al., 2025). Since then, of the £3.35bn Labour has spent on AI contracts, only £34m has gone towards streamlining the Treasury, despite the DWP alone having an annual IT budget of over £1bn (Coates, 2025). This obvious de-prioritisation of taxation and welfare, as the Prime Minister declares his intention to indeed leave companies to their own devices, makes it seem as though the IPPR’s fears of fiscal and employment crises may be inevitable, and demonstrates the need for a radical rethinking of the scope and scale of our tax and welfare systems.

In his essay “Economic Possibilities for our Grandchildren”, Keynes (1930) outlined his belief that, so rapid was the advancement of technology in the 20th century, by the year 2000, automation would allow for a mere 15-hour work week. Indeed, in post-industrial Britain, a vast majority of, as Sam Altman’s farmer would put it, “real” jobs (farm or factory work, for example) have all but disappeared, yet average weekly work hours hover around 36 hours, over double Keynes’s prediction (ONS, 2025). What Keynes couldn’t foresee is that these jobs would simply get replaced. The decline of industry in the UK coincided with the growth of the administration sector – what Graeber (2018) calls “bullshit jobs”. Their primary value comes not from the (arguably little) labour performed, but from the lack of labour performed on shift; when there is no other point to your job than working for work’s sake, it’s an easy coping mechanism to take on working for work’s sake as a virtue in itself. This value, Graeber says, makes demands like fairer pay for, say, nurses or artists, or welfare provision for the unemployed appear as an affront to the moral values of society and ultimately serves to “maintain the power of finance capital”. These are the very jobs the IPPR says are most at risk from AI – so what’s the issue? Maybe Altman’s farmer is right? The IPPR (2024) itself outlines that market reshuffles from AI-related redundancies could be used to fill positions in short-staffed, socially beneficial sectors like health and social care, which itself could reshape social stigma around low-paid essential work. However, whilst the loss of “bullshit” jobs would definitely be a step towards a kinder, fairer society, these jobs vanishing without any form of safety net for those displaced by AI does little to mitigate individual hardship and the economic shock of sudden mass-unemployment.

Between 2022-25, the Senedd piloted a radical “basic income” for young care leavers (Gwilym & Beck, 2024). Unconditional cash transfers such as this have seen reductions in welfare stigma, improved mental health outcomes, and a sense of hope for the future in recipients (Wilson & McDaid, 2021). This safety net gave them time and work flexibility, allowing for pursuits of education or training, bargaining for fairer wages, or outright career changes (Martinelli & Vanderborght, 2022). Schemes like these kill two birds with one stone – providing a wider safety net for those at risk of AI redundancy, and for an economy at risk of the fiscal scissor effect – whilst moving away from a polarising and punitive culture of bullshit work. Yet in 2025, the Welsh BI pilot, like many others of its kind previously, was promptly scrapped due to spending cuts. This shouldn’t be happening. 60% of the UK public support a tax on homes worth over £2m, and a further 75% support a wealth tax on assets of over £1m (YouGov, 2025). There is immense hunger among the UK public for radical sociopolitical change, and in the face of a potential AI-led crisis, it is a moral imperative that policymakers, academics, and politicians take immediate action to channel this hunger into developing a social safety net that is comprehensive, effective, and kind.

References

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