The debut of generative AI tools like ChatGPT, which gathered tens of millions of users within months of its fall 2022 release, has caused a stir on the internet. The generative AI tools that Google and Microsoft are now developing are also being tested. And people feel uneasy.
According to a recent Jobs for the Future study of 2,204 adults, 37% of adults have a negative outlook on how AI will affect employees in the future, and 25% think AI would impair their industry.
Technology changes at work are nothing new. According to Syracuse University assistant professor of sociology Aaron Benanav, the story of how technology is changing the way we work only dates back at least the last 200 years since the industrial revolution.
According to Felix Koenig, an assistant professor of economics at Carnegie Mellon University, what distinguishes generative AI from other forms of artificial intelligence is the possibility that it may have an impact on higher-paying professions in conventional professional sectors like legal and financial services. Perhaps people have the impression that those positions are exempt.
According to a recent Pew Research Centre survey, jobs where AI might replace or assist with the most crucial tasks tended to be in “higher-paying fields where a college degree and analytical skills can be an advantage.
According to Benanav, history may be able to forecast how generative AI may affect or transform work in the future. Here are some potential outcomes for certain roles, according to historians.
Technology might “transform good jobs into bad jobs.”
The characteristics and requirements of some employment may alter as a result of generative AI.
According to Jason Resnikoff, assistant professor of contemporary history at the University of Groningen in the Netherlands, tools like ChatGPT might be used to “break that one job into five jobs, 10 jobs, or even, like, 50 jobs,” taking a complex position that only one person was performing. In order to finish the bigger project, each of these positions would ultimately require less knowledge and experience.
One possibility is that we’ll have an assembly line for a TV show script, he adds, adding that AI would produce terrible dialogue, and then there’d be the dialogue finisher. Then it’d come up with a horrible concept, and there’d be the premise coordinator. You’d have a variety of writing occupations, none of which are writer-related. And, in theory, each of these positions would require less talent and pay less than the current job of a writer.
Another choice, he believes, is to create a two-tier structure.
According to Resnikoff, the top tier would consist of a very thin layer of extremely well-paid artisans who operate in small shops. Workers in the second tier would have dreadful, very precarious jobs. According to him, all other television is written by a machine and all these peons working at it, whereas top-tier writers might work on every aspect of a script.
Resnikoff’s term for these types of jobs, “s—– jobs,” captures the essence of the kind of job deterioration that would emerge from moving in this route. According to Resnikoff, historically, splitting up larger tasks that required a lot of ability and knowledge into a number of smaller ones has enabled employers to tell employees, You’re doing so much less, so we’re going to pay you half of what you made before.
According to him, introducing new technology has served as a means of converting good jobs into bad jobs.
One person could do a job historically done by many
Another result of this new technology is that some jobs may completely disappear. Koenig uses the example of what transpired after the 1920s introduction of talkies, or motion pictures with sound.
Before then, live music was performed in the background while silent films were being screened in movie theatres. According to him, there was a significant union-driven campaign against the advent of talkies, or sound recorded films. Part of the reason for this was the worry that all of these musicians will be replaced.
Despite the fact that talkies didn’t completely eliminate the requirement for a musician to compose music for movies, he claims that now one person may play once and be heard millions of times.
He claims that the pianist still performs the piano the same way they did 100 years ago. However, a single individual today completes the work that was previously completed by hundreds of people. Globally, 300 million jobs could be lost due to generative AI, according to a new Goldman Sachs research.
New employment often come into existence
The workplace might benefit from generative AI in various ways.
Benanav uses the requirement for academics to write grants as an example. With the aid of a machine, such could be formulaic and take much less time. He claims that when it comes to programming, it aids engineers in creating simple code outlines or, occasionally, entire parts of code.
Additionally, according to Koenig, this type of transformation usually results in the creation of new occupations that previously didn’t exist.
In reality, new positions have already appeared. Since the beginning of 2023, the freelance marketplace Fiverr has seen a large number of new generative AI-focused gigs appear on their site, including AI consultant and AI video editor. New full-time roles like AI research scientist and creative director have also been reported by ZipRecruiter.
‘The future is open’
It’s crucial to keep in mind that profit is what really drives things, no matter how the workforce evolves now or how the employment market develops in the future, according to Resnikoff. For a variety of reasons, businesses are encouraged to put their bottom line first, which occasionally entails lowering the cost of labor.
But in the end, the decision to create lower-paying employment or to eliminate them entirely truly rests with the individuals in control of their respective workforces.
Given these facts and the variety of options available, Benanav would remind staff members that “the future is open.
He claims that the job could get better or worse, and that you should work to try to make the circumstances where it’s going to get better.
