In the upcoming months (and years, really), expect the discussion about how AI technology will impact the future of work—and by that, I mean jobs—to be a hotly debated subject of optimism and pessimism.
Since Google, Spotify, Amazon, and other companies have made job cuts and explicitly said that they need to reallocate resources to AI-forward jobs and projects, it is clear that businesses are preparing for the potential productivity and profit increases that could result from the adoption of generative AI and automated technology.
This month, the International Monetary Fund reported that AI would likely affect over 40% of occupations globally. According to the World Economic Forum’s September “Jobs of Tomorrow” report, AI will be one of the factors for 23% of global jobs to change over the next five years. According to the WEF, this transition will change the nature of current employment and create new ones in fields including AI development, interface and interaction designers, data curators, AI ethics and governance experts, and AI content makers. (Recall that Goldman Sachs said last year that 60% of workers currently have jobs in industries that did not exist in 1940.)
Given that experts concur it will take time to develop a workforce skilled in AI education, whose current occupations will be most impacted and how do companies locate the suitable candidates for those new roles? And who will carry out that retraining? Who is to blame for revising job definitions as corporations make adjustments to their operations—the government, the employees, or the companies themselves?
Mixing all of the aforementioned is the answer. According to Robert Seamans, a professor at New York University and the director of the NYU Stern Center for the Future of Management, employers should invest in employee training to equip them with new skills, workers should acquire new skills, and the government should enact laws that support a workforce skilled in artificial intelligence. However, he is especially hopeful that businesses will step up.
“From a policy point of view, there’s a lot of focus put on programs that help the worker to gain the skills that they need to succeed in the jobs of the future … but it puts a lot of the burden on the worker to basically make bets on the skill sets that are going to be needed one year, let alone five years, in the future,” he stated in a question-and-answer session for the series of lectures last week.
Seamans wants to see businesses offered incentives for retraining and investing in their employees. “The firms would then be able to take advantage of a much better trained workforce,” he says. “Instead of trying to identify the people, trying to understand what skills we need right now and trying to identify who out there has those skills [and] trying to convince them to come — let’s just take the employees that we have. We have a rough idea of the skills we think that they need, and we’re being encouraged by the government to sort of invest in training in those skills.”
The good news is that companies with the highest levels of AI optimism still have time to devote to employee training. According to an MIT research published on January 22, businesses looking to use AI to replace workers or move duties won’t see a return on their investment in the technology for some time. According to their analysis, which focused on computer vision-related employment, “at today’s costs, US businesses would choose not to automate most vision tasks that have ‘AI Exposure,’ and that only 23% of worker wages being paid for vision tasks would be attractive to automate.”
The researchers concluded, “AI job displacement will be substantial, but also gradual.” “Therefore there is room for policy and retraining to mitigate unemployment impacts.”
Veteran tech investor Esther Dyson added her perspective on AI and employment. She suggests that rather of concentrating on AI careers, we should consider improving ourselves as “better humans: more self-aware and more understanding of the world around us, better able to understand our own and others’ motivations.”
Using AI, not competing with it, is how Dyson put it in an essay for The Information. “People should train themselves to be better humans even as we develop better AI. People are still in control, but they need to use that control wisely, ethically and carefully.”
