Will You All Please Just Stop Shouting?

A Calmer Conversation About AI and the Future of Work

There is a particular kind of exhaustion that sets in when every platform you visit, every feed you scroll, every newsletter that lands uninvited in your inbox, tells you that the world as you know it is about to end. Or, conversely, that it is about to become so glitteringly perfect that your grandchildren will wonder how we ever managed without it. Artificial intelligence is, depending on who you read today, either the saviour of human productivity or the quiet assassin of human purpose. LinkedIn, that curious theatre of professional self-expression, now appears to be roughly seventy percent think-pieces on how AI will transform this sector or eviscerate that one, interspersed with the occasional announcement of a new job title that did not exist eighteen months ago.

And, in the great tradition of feeding the very beast one is complaining about, CWIP is going to add to this noble canon with yet another article. You are very welcome.

The irony is not lost on us. But we think the conversation is worth having in a slightly different register: one that is a little less breathless, a little more historically informed, and perhaps a good deal less dramatic than much of what currently passes for commentary on the subject.

We Have Been Here Before. Repeatedly.

Let us begin in Nottinghamshire, in the early months of 1811, when a group of skilled textile workers, in a wave of coordinated nighttime raids, broke into factories and set about destroying the knitting frames and power looms that they believed were dismantling their livelihoods. The Luddites, as they came to be known, were members of a movement of English textile workers who opposed the use of certain types of automated machinery, and they often destroyed the machines in organised raids. They had rallied under the banner of the probably fictional "Ned Ludd" of Sherwood Forest (a man almost certainly no more real than another legendary local champion of the dispossessed, Robin Hood) and they were, in their way, entirely serious about what they feared. They did not resist innovation because they feared change. They resisted because the change had largely impoverished them while enriching others.

And yet, and this is the important part, history tells us that each industrial revolution has brought the fear of job losses, but that in fact, jobs were created and living standards improved. The frames were not, in the end, the harbingers of permanent ruin. What the Luddites experienced was real pain during a period of acute transition, compounded by war, food scarcity, and the absence of any meaningful employment protection. What they did not experience, as it turned out, was the permanent technological unemployment they feared. We might note, with the gentlest of nudges, that this is not the last time that fear and reality would prove to be somewhat different neighbours.

In 1930, with the Great Depression darkening everything it touched, the economist John Maynard Keynes sat down to write what he called "Economic Possibilities for our Grandchildren." He was a worrier, Keynes, but a constructive one. He coined the phrase "technological unemployment," which he defined as "unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour," but he was careful to add: "this is only a temporary phase of maladjustment." His longer forecast was rather more optimistic. He predicted that the standard of life in progressive countries would, within a hundred years, be between four and eight times what it was in his day. He was right. In the UK, GDP per capita has increased fourfold since 1930. In the US, GDP per capita has increased fivefold. The great economist was not, it seems, prone to the catastrophising that we currently treat as a form of intellectual rigour.

Jump forward to the 1970s and 1980s, when the computer age began to quicken. The computer age and advances in robotics generated a fresh cycle of fear. The New York Times issued a cautionary warning titled 'A Robot is After your Job,' and some economists wondered if 'full employment' would ever be possible again. White collar workers feared their days were numbered. In 1995, Jeremy Rifkin published "The End of Work," in which he foresaw a post-market era of such comprehensive automation that the very concept of a job would become a historical curiosity. It is a book that remains, perhaps ironically, in print. The jobs, however, also remain.

By the 1990s, it was the internet that was doing the disrupting. Tech companies used utopian language to describe the internet as a marker of human progress that could improve productivity, provide easier access to consumer goods, and increase leisure time, while simultaneously those who worried about the workforce fretted about offshoring, the hollowing out of skilled employment and the displacement of white-collar roles by software. Some of those fears had substance; the transition brought genuine difficulty for some categories of worker. But the net outcome was not the wasteland predicted. The digital economy created entire categories of work that nobody had conceived of in 1993, and that no economist had modelled.

The Pattern Is Older Than We Think

What is striking, when one steps back to look at this through a longer lens, is not how novel our current anxieties are, but how deeply familiar they are. Technology is widely considered the main source of economic progress, but it has also generated cultural anxiety throughout history. The developed world is now suffering from another bout of such angst. Joel Mokyr, Chris Vickers and Nicolas Ziebarth, writing in the Journal of Economic Perspectives in 2015, traced this pattern of technological anxiety across two centuries and found it to be essentially cyclical: fear, disruption, adjustment, growth, and then, after a suitable interval, fear again. First, there is the concern that technological progress will cause widespread substitution of machines for labour, which in turn could lead to technological unemployment and a further increase in inequality in the short run, even if the long-run effects are beneficial. Second, there has been anxiety over the moral implications of technological progress for human welfare, broadly defined. They titled their paper, with a weariness one can only respect: "Is This Time Different?" Their answer, hedged with appropriate academic caution, was broadly no.

Prior to the era of modern economic growth, the concern that new technologies would displace labour often created political barriers to their adoption. However, over the last two hundred years, in aggregate, more new jobs have been created than lost. The broader literature on technology and employment is, it must be said, genuinely divided. At the aggregate level, there is little evidence that technological change has led to widespread unemployment over the centuries. But technology-induced job losses can be significant, and the disruption to individual workers and communities in transition periods is real and should not be minimised. That is an important qualification. The point is not that technology is painless; it never has been. The point is that the catastrophic endpoint so frequently forecast by those shouting loudest has not historically arrived, and that within the disruption there are almost always new opportunities visible to those willing to look for them rather than mourn what is being lost.

President Dwight Eisenhower, as long ago as 1955, dismissed fears of automation as "groundless," noting that the same fears had "plagued people for 150 years and always proved groundless." This is not, of course, a reason to be entirely complacent. But it does rather suggest that the tone of existential crisis that surrounds AI today might be calibrated somewhat downwards.

So What Is Actually Going To Happen?

The honest answer, which we recognise is not what LinkedIn's algorithm particularly rewards, is that we do not entirely know. What we can say with some confidence is this: AI will change how work is done, substantially and in some cases irreversibly. Tasks and activities that currently occupy hours of skilled human time will be absorbed by automated workflows. Bots will deliver more services. Data models of increasing sophistication will help organisations make better sense of the world in which they operate. It is even possible, over a longer horizon, that AI will develop something resembling a form of self-awareness that will challenge our assumptions about human cognition and knowledge itself.

But here is what we think the hand-wringers frequently miss: the human condition is not simply a list of tasks executed with varying degrees of efficiency. It is about how those tasks land, how they affect the people they touch, what they mean to the organisations that commission them and the communities that depend on them. The question of whether a particular piece of work was done by a person or a system is often secondary to the question of whether it was done with appropriate judgment, care, accountability and genuine understanding of its consequences. Technology cannot carry those responsibilities. People must.

The role of people in an AI-augmented world is therefore not to compete with the technology at its own game, because that is a competition humans will routinely lose, but to shape, direct, challenge, question and make meaning of what the technology produces. Job roles of the future will be more concerned with steering, interpreting, socialising and normalising - with bringing human values to bear on machine outputs, and with asking the questions that only those with a stake in the outcome are equipped to ask. Technology will make us more productive; humans will determine whether that productivity is put to good use.

Actually, This Is Not Even That New

Perhaps what is most puzzling about the current debate is the apparent surprise with which many commentators describe what is, in essence, a phenomenon that well-managed organisations have been navigating for decades. The idea that a workforce should combine permanent capacity for core delivery, flexible capacity for peaks and surges, specialist expertise brought in for defined purposes, and enabling technology to maximise human effectiveness, is not an insight generated by the AI revolution. It is simply good workforce design, and organisations that have done it thoughtfully have been reaping the benefits for a long time. The future of work that is described in breathless LinkedIn posts as some kind of revelation looks, from certain angles, rather like the present of work in organisations that paid attention.

During the early phase of the Industrial Revolution, the displacement effect dominated, hurting workers; in the 20th century, the reinstatement effect became stronger, driving up wages and living standards. The same interplay is at work now. Displacement is real, but reinstatement (the creation of new roles and new value) follows, as it always has. The skill, if there is one, lies in managing that interval between the two with policy, investment and genuine concern for those caught in the transition, rather than either ignoring the disruption or catastrophising it into paralysis.

A Quiet Suggestion

What CWIP would gently propose, at the risk of being shouted at from all sides, is this: by all means engage seriously with AI, understand it, experiment with it, and think carefully about its implications for your workforce. But do so with the benefit of historical perspective, an awareness of the deeply ingrained human tendency to mistake short-term turbulence for permanent catastrophe, and a healthy scepticism about the motivations of those whose business models depend on either selling you the technology or selling you the fear of it.

The emerging technologies of today deserve to be embraced in the way that, at every point in history, the genuinely transformative ones have been absorbed over time: through curiosity, adaptation, learning, and a willingness to grow without excessive drama. Get your heads down. Do the work. Ask the right questions. That, in the end, is rather more useful than adding another post to the pile.

We trust you can find your own way back to LinkedIn from here.

References

Eisenhower, D.D. (1955) Remarks on automation and technological unemployment, cited in: Pessimists Archive Newsletter (2023) *Robots Have Been About to Take All the Jobs for 100 Years*. Available at: https://newsletter.pessimistsarchive.org/p/robots-have-been-about-to-take-all [Accessed: May 2026].

Frey, C.B. and Osborne, M.A. (2017) 'The future of employment: how susceptible are jobs to computerisation?', *Technological Forecasting and Social Change*, 114, pp.254–280.

International Monetary Fund (2025) 'A New Industrial Revolution?', *Finance and Development*, December 2025. Available at: https://www.imf.org/en/publications/fandd/issues/2025/12/a-new-industrial-revolution-niall-kishtainy [Accessed: May 2026].

Keynes, J.M. (1930) *Economic Possibilities for our Grandchildren*. First published in *The Nation and Athenaeum*, October 1930. Reprinted in: Keynes, J.M. (1931) *Essays in Persuasion*. London: Macmillan.

Mokyr, J., Vickers, C. and Ziebarth, N.L. (2015) 'The history of technological anxiety and the future of economic growth: is this time different?', *Journal of Economic Perspectives*, 29(3), pp.31 - 50. https://doi.org/10.1257/jep.29.3.31.

Rifkin, J. (1995) *The End of Work: The Decline of the Global Labor Force and the Dawn of the Post-Market Era*. New York: Putnam.

Smithsonian Magazine (2023) 'What the Luddites Really Fought Against'. Available at: https://www.smithsonianmag.com/history/what-the-luddites-really-fought-against-264412/ [Accessed: May 2026].

TIME Magazine (2025) 'What 1990s Internet History Tells Us About the AI Boom', 31 July 2025. Available at: https://time.com/7302216/internet-history-ai/ [Accessed: May 2026].

World History Encyclopedia (2026) 'Luddite'. Available at: https://www.worldhistory.org/Luddite/ [Accessed: May 2026].

Wajcman, J. and Jones, P.K. (2012) 'Border communication: media sociology and STS', *Media, Culture and Society*, 34(6), pp.673 - 690.

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