There’s a long history of management painting automation that’s as inevitable as the sunrise. It’s a repeating pattern summarized by the late technology historian David F. Noble productive forces, his account of the introduction of machine tools to America. “‘Automatic’ or ‘self-acting’ machines enabled management both to eliminate labor altogether and to control the production process more directly,” he wrote. “The machines, in turn, served to discipline and slow down the serving operators, indirectly reducing the ‘labor problem’ through the apparent demands of the production technology itself.”
Power and Progress: Our Thousand-Year Struggle for Technology and Wealth, a book by MIT economists Daron Acemoglu and Simon Johnson, due out next month, chronicles a thousand years of elites — from medieval European nobles to modern tech CEOs — who benefited from technological advances at the expense of workers. Generative AI fits well into this historical context. “We argue that this obsession with machine intelligence is unhelpful because that’s what it’s all about substitute people,” explains Johnson. “On the other hand, if you focus on making machines useful For people—nurses, doctors, teachers, etc.—that will be a lot more helpful for productivity and, potentially, pay.”
The future prospects are terrible. He calls August’s personal dystopia the Nora Ephron scenario, in which the AI learns to emulate cultural titans, eclipsing new human writers. Studios are unlikely to use AI scabs during this strike, not least because AI tools crossing the picket line introduce danger Variety of copyright issues, but it’s not hard to imagine that this could happen at some point. (“You can’t protect studio heads from their bad ideas,” he says.)
And then there’s probably the worst-case scenario worth considering right now: a producer asks a writer to edit a script (which pays less than producing an original work) and doesn’t tell them that it was created by a chatbot. “This is a crisis in our compensation, a crisis in our leftover inventory, and a crisis in our artistic ability to do the things that we’re being asked to do in this industry,” August says. “So that’s a basic nightmare scenario. And that feels very obvious if we don’t solve the problem.”
More positive results This includes improved productivity, such as switching from a typewriter to a word processor. Commentators are unsureHowever, the question arises as to whether this increase in productivity will lead to tangible improvements, such as a higher standard of living. ChatGPT is already good for brainstorming: if you need 15 different names for a Mandarin bagel shop, as August puts it, AI does a good job. And he sees the possibility that technology could create opportunities for more diverse writers, such as improving screenplays for someone for whom English is not their first language.
Automation and redundancy are not necessarily closely related, and the adoption of disruptive technologies – such as Self checkout machine– is a choice. There are examples where workers’ perspectives on new technologies, not just management’s, have been successfully taken into account. In their book, Acemoglu and Johnson quote West Coast dockers who are calling for retraining in new technologies. They won, leading to a reduction in job losses and an increase in productivity. Katya Klinova, head of Al, Labor and Business at the Partnership on AI, points to Unite Here, which represents hospitality workers, who in 2018 successfully won the right to negotiate how Marriott plans to introduce new technologies such as online services, computers and even robots.