Artificial intelligence is big business’s new flavor of the month. Companies are rushing to showcase how they will be using new generative AI models, and the media is full of stories about the technology’s transformative potential. There is no denying that it could significantly increase productivity. But who stands to benefit? The ongoing Writers Guild of America (WGA) strike may offer an answer.
Hollywood screenwriters are confronting a future that all knowledge workers will soon face — and without the benefit of union representation. At issue is how AI will be used, and by whom. Will TV and movie producers see AI as a way to replace writers and cut costs, or will they use it to create higher-quality content, empowering creative workers to be more productive and earn higher incomes?
We have been down a similar road before. In the early twentieth century, rapid improvements in manufacturing technologies such as moving assembly lines and electrical machinery led to a sharp increase in productivity. Henry Ford, a pioneer in applying these technologies, estimated that motor-enabled machinery “alone has probably doubled the efficiency of industry,” while also making it possible to build much larger factories. But workers did not automatically share in these gains. On the contrary, that did not happen until new tasks had been created, and until workers had acquired enough bargaining power to demand higher wages. These are the two pillars of shared prosperity.
While Ford and his contemporaries certainly did automate some processes, their improved factories also introduced a lot of new activities that required human labor — from material preparation and machine maintenance to coordinating operations. These tasks expanded workers’ contribution to production and translated into a big increase in the demand for labor. In 1899, the US car industry employed a few thousand workers, producing around 2,500 vehicles per year. By 1929, Ford and GM were each making 1.5 million cars annually (with total US auto production around 4.5 million), and the industry employed more than 400,000 people.
The second pillar is bargaining power. The famous sit-down strike at GM in 1936-37 was a key step in achieving union recognition, improved working conditions, and higher compensation for workers. Over several decades, the new balance that developed between management and workers in automobile manufacturing contributed to rapid wage growth. Part of what made this possible was an emphasis on continually training and upskilling workers to handle new tasks. Both employers and employees benefited from the productivity gains.
By the 1960s, US auto production had doubled since the 1920s, with the four largest manufacturers employing 1.3 million workers — more than three times the industry’s employment four decades earlier. Moreover, inflation-adjusted profits for the dominant firms, GM and Ford, were around five times higher than in previous decades.
The rise of organized labor in the auto industry also established a model of capital-labor negotiations for other industries to follow. Imagine what would have happened if manufacturing companies attempted to adopt ‘worker-less factories’ in the 1950s, as some had started advocating. Productivity growth (not to mention shared prosperity) would have suffered greatly as the human contributions to technical work, design, maintenance, inspection, and creative problem-solving were undermined or lost.
Today, we are confronting equally revolutionary changes, now that executives are considering how to apply generative AI to all components of knowledge production and distribution. Leading tech-focused companies face many of the same choices that car manufacturers had to make at the beginning of the twentieth century. Should powerful new technologies be used to automate knowledge work and sideline workers? Or could AI become a tool to boost worker productivity and creativity? Much will depend on whether workers have a voice, and on how such choices affect productivity and product quality.
There are grounds for thinking that the WGA strike could be more important even than the struggles for union recognition at Ford and GM’s factories a century ago. For starters, Hollywood’s creative workers are uniquely well-organized and powerful compared to workers in other industries. If they fail, other knowledge workers will stand even less of a chance of shaping the future of work and technology.
The choices ahead of us are epochal, because there is an obvious temptation for movie producers to choose the low road of “just automate everything you can.” This approach may be profitable in the short term if it allows for more shows to be cheaply produced, with fewer screenwriters, actors, and other staff. But studio profits and high-quality output are not the same thing. There still is no substitution for human ingenuity and creativity. Look past the hype, and it should be clear that predicting the next word in a sentence and aggregating the “wisdom” available on the internet are unlikely to generate superior artistic output – even if large language models could produce mediocre sitcoms.
The low road is especially costly because of what it misses. Generative AI could become a tremendously beneficial tool in the hands of creative artists, by helping with research and the development of new ideas. If we can find our way to this high road, AI could drive further technological progress and bolster the returns from human ingenuity.
Much is riding on the writers’ strike. Obviously, it would be a disaster for workers if they are sidelined by movie studios. Knowledge workers – and, indeed, all workers – should hope that the WGA and its members succeed in showing not only how unions can raise wages in the short term, but also how technology can be used to support creativity, rather than simply displacing it.
Daron Acemoglu
Daron Acemoglu, Institute Professor of Economics at MIT, is a co-author (with Simon Johnson) of Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity.
Simon Johnson
Simon Johnson, a former chief economist at the International Monetary Fund, is a professor at MIT’s Sloan School of Management.
Austin Lentsch
Austin Lentsch is a policy fellow at MIT’s Blueprint Labs.
Copyright: Project Syndicate.
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