May 2 , 2024
By Daron Acemoglu , Simon Johnson
Artificial intelligence (AI) and its threat to good jobs would seem to be an entirely new problem. But we can find useful ideas about how to respond in the work of David Ricardo, a founder of modern economics who observed the British Industrial Revolution firsthand. The evolution of his thinking, including some points he missed, holds many helpful lessons for us today. Private-sector tech leaders promise us a brighter future of less street at work, fewer boring meetings, more leisure time, and perhaps even a universal basic income.
But should we believe them?
Many people may lose what they regarded as a good job – forcing them to find work at a lower wage. After all, algorithms are already taking over tasks that require people's time and attention. In his seminal 1817 work, "On Principles of Political Economy and Taxation," Ricardo took a positive view of the machinery that had already transformed cotton spinning. Following the conventional wisdom of the time, he famously told the House of Commons that "machinery did not lessen the demand for labour."
Since the 1770s, the automation of spinning has reduced the price of spun cotton and increased demand for the complementary task of weaving spun cotton into finished cloth. Since almost all weaving was done by hand before the 1810s, this explosion in demand helped turn cotton handweaving into a high-paying artisanal job employing several hundred thousand British men (including many displaced, pre-industrial spinners). This early, positive experience with automation likely informed Ricardo's initially optimistic view.
But, the development of large-scale machinery did not stop with spinning. Soon, steam-powered looms were being deployed in cotton-weaving factories. No longer would artisanal "hand weavers" be making good money working five days per week from their cottages. Instead, they would struggle to feed their families while working much longer hours under strict factory discipline. As anxiety and protests spread across northern England, Ricardo changed his mind. In the third edition of his influential book, published in 1821, he added a new chapter, "On Machinery," where he hit the nail on the head: "If machinery could do all the work that labour now does, there would be no demand for labour."
The same concern applies today. Algorithms' takeover of tasks previously performed by workers will not be good news for displaced workers unless they can find well-paid new tasks.
Most of the struggling handweaving artisans during the 1810s and 1820s did not go to work in the new weaving factories, because the machine looms did not need many workers. Whereas spinning automation had created opportunities for more people to work as weavers, the automation of weaving did not create compensatory labour demand in other sectors. The British economy overall did not create enough other well-paying new jobs, at least not until railways took off in the 1830s. With few other options, hundreds of thousands of hand weavers remained in the occupation, even as wages fell by more than half.
Another key problem, albeit not one that Ricardo himself dwelled upon, was that working in harsh factory conditions – becoming a small cog in the employer-controlled "satanic mills" of the early 1800s – was unappealing to handloom weavers. Many artisanal weavers operated as independent businesspeople and entrepreneurs who bought spun cotton and sold their woven products on the market. They were not enthusiastic about submitting to longer hours, more discipline, less autonomy, and typically lower wages (at least compared to the heyday of handloom weaving). In testimony collected by various Royal Commissions, weavers spoke bitterly about their refusal to accept such working conditions or how horrible their lives became when they were forced (by the lack of other options) into such jobs.
Today's generative AI has enormous potential and has already chalked up some impressive achievements, including in scientific research. It could well be used to help workers become more informed, more productive, more independent, and more versatile. Unfortunately, the tech industry seems to have other uses in mind. As we explain in "Power & Progress", the big companies developing and deploying AI overwhelmingly favour automation (replacing people) over augmentation (making people more productive).
That means we face the risk of excessive automation: Many workers will be displaced, and those who remain employed will be subjected to increasingly demeaning forms of surveillance and control. The principle of "automate first and ask questions later" requires – and thus further encourages – the collection of massive amounts of information in the workplace and across all parts of society, calling into question how much privacy will remain.
Such a future is not inevitable. Regulation of data collection would help protect privacy, and stronger workplace rules could prevent the worst aspects of AI-based surveillance. But the more fundamental task, Ricardo would remind us, is to change the overall narrative about AI. Arguably, the most important lesson from his life and work is that machines are not necessarily good or bad. Whether they destroy or create jobs depends on how we deploy them and who makes those choices. In Ricardo's time, a small cadre of factory owners decided, and those decisions centred on automation and squeezing workers as hard as possible.
Today, an even smaller cadre of tech leaders seems to be taking the same path. However, focusing on creating new opportunities, new tasks for humans, and respect for all individuals would ensure much better outcomes. It is still possible to have pro-worker AI, but only if we can change the direction of innovation in the tech industry and introduce new regulations and institutions.
As in Ricardo's day, trusting in the benevolence of business and tech leaders would be naive. It took major political reforms to create genuine democracy, legalise trade unions, and change the direction of technological progress in Britain during the Industrial Revolution. The same fundamental challenge confronts us today.
Daron Acemoglu is an institute professor of economics at MIT, and Simon Johnson, a former chief economist at the IMF), is a professor at the MIT Sloan School of Management and a co-author (with Daron Acemoglu) of "Power & Progress: Our Thiusand-Year Struggle Over Technology & Prosperity." This article is provided by Project Syndicate (PS).
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