View: The one thing that can slow AI's breakneck speed

When they are not indulging in circus-worthy boardroom battles, promoters of AI have sought to allay the fears of governments and corporations by selling a future full of hope and assurance. Par for the course. Every political and economic revolution has offered these twin promises in lieu of a change that requires widespread – willing or unwilling – compliance and support to succeed.

During the Industrial Revolution, capitalists organised workers in mills and factories to ensure the division of labour could increase output and profitability. The great hope then was that mechanisation would accelerate the pace of trade, while enriching lives of workers, many of whom were skilled craftsmen, through guaranteed employment and regular wages.

Some of this came to pass, to the great delight of Utilitarian philosophers, including Thomas Gradgrind in Charles Dickens’ 1854 novel, Hard Times. Gradgrind believed that simple mathematical facts were sufficient to overcome the burden of proof. But unreasonably long hours, subsistence wages, and little scope for advancement transformed the worker into a ‘cog in the wheel’, essential for productivity but utterly lacking in independence. The world was more unequal than before, with wealth being consolidated at an unprecedented rate.

Then came the Corporate Revolution of the 20th century, powered by assembly lines and ever-advancing tech. Realising that simply organising labour was insufficient to sustain growth and profits, capitalists organised markets around efficient processes and supply chains, giving rise to new service industries in the process.

In 1930, John Maynard Keynes was so impressed by the momentum of tech change that he predicted, despite the prevailing Depression, a 15-hour workweek for developed nations by the end of the century. At first, growth of global trade, rampant consumerism, and a general improvement in the material aspects of life after 1950 supported this hypothesis.

As jobs became more specialised and streamlined, however, workhours rose swiftly while real wages stagnated. This made most workers siloed functionaries in commodified jobs, fearful of becoming victims of retrenchment and job discontinuance. The world was even more unequal, with income disparities that beggared belief. And now, the doyens of the Digital Revolution assure us that intelligent automation, LLM platforms like ChatGPT, and other AI-powered algorithms can utterly transform the workplace, freeing up human time for more intellectual work and creative pursuits. Which all sounds good, if you are willing to suspend disbelief. Except for two things: It contradicts a commercial entity’s raison d’etre.

It ignores – despite the touting of human agency as a company’s most valuable resource – that labour is expensive to hire, manage and retain.

The two prior revolutions attest to the fact that there is one demi-urge, the capitalist, and one overarching reward: profit. Labour is only a necessary factor in the equation as long as the costs of organising labour do not supersede the marginal return linked to its inclusion and organisation.

In his seminal 1937 article, ‘The Nature of the Firm’, Ronald Coase identified three things that enabled firms to grow large while remaining profitable:

Lower cost of organising factors of production.

Smaller margin of predictive and forecasting error when dealing with market uncertainty.

Sustained low supply price of these factors.

It is evident to all but the most incredulous that AI may very likely help a corporation to achieve the first two. But it is also capable of supporting the third consideration even more dramatically, by making certain functions of labour – the most unpredictable, unreliable, and uneconomical factor in many service-focused and specialised manufacturing firms – redundant altogether. As a first step, in a farcical homage to the concept of a shorter workweek, RHRP – reduced hours for reduced pay – may very well be in the offing.

One has only to look at the rise of human-like intelligent chatbots, coupled with hiring freezes and layoffs across geographies. To say nothing of recent investments in human-like robots by Jeff Bezos, Nvidia and Microsoft, to follow this to its logical conclusion. In the future, wealth will no longer need to be concentrated, as it may cease to proliferate.

Yet, all may not be lost (or gained, depending on which side of the turnstile you’re standing). AI’s ruthless efficiency orientation could eventually make its developers and champions as redundant as humbler functionaries it currently seeks to replace. And nothing reinforces common sense and moderation like an imminent threat to one’s own self-preservation.

This may be the assurance in which to place our Great White AI hope.


This website uses cookies. By continuing to use this site, you accept our use of cookies.