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Commerce throws some money at the AI jobs chicken-or-egg problem.
It’s been several months since the Department of Commerce announced it was reworking $25 million in Economic Development Administration dollars to go toward AI jobs. When Commerce made that announcement, I wondered aloud if by the time the money hit the street we would know what AI jobs are.
Politically, the Trump Administration insists AI is a job-maker, not a job-killer. But knowing what those AI jobs are is a key condition for doing that, and frankly, employers don’t know if they will have “AI jobs” yet. In fact, their incentives around AI currently are more about ending old jobs than creating new ones. Trump II has a limited policy menu from the White House as to how it can engage this issue, which mostly consists of a choice between “Defer to employers” and perhaps “Defer to employers, but dressed as Spider-Man.” So it can’t push the issue too far to get an answer.
In other words, it’s a chicken-or-egg problem. Trump II’s political bet is that it can get a bunch of people into AI jobs if it promotes them, but we need to know what the hell an “AI job” is to promote them.
EDA’s $25 million AI grant solicitation finally hit the street this week. I can’t say that it provides answers, but around some typical haughty AI language, it has some interesting cues on how Trump II is now engaging the questions.
AI represents a new frontier for workers, including new high-wage careers and enhanced productivity, but will also require new skills and transitions in the labor market for workers to share in the prosperity that AI will create. The greatest workforce challenge of AI may be the speed of change itself. As AI accelerates shifts in job tasks and skill requirements, companies, educational institutions, and the workforce system must adapt in real time. Without significant reform to create more agility and innovation in worker training, the United States risks falling behind in the race to develop an AI-ready workforce. . . .
The bottleneck to harnessing AI’s full potential is not necessarily the availability of models, tools, or applications. Rather, it is the limited and slow adoption of AI, particularly within large, established organizations. Many of America’s most critical sectors, such as healthcare, are especially slow to adopt due to a variety of factors, including distrust or lack of understanding of the technology, a complex regulatory landscape, a lack of clear governance and risk mitigation standards, and a workforce not yet equipped to shape the AI transformation.
Here’s how I read all that as a former policymaker: None of y’all got it together yet, so we’re spending money to help y’all figure it out.
And here’s how I read the projects funded by these grants: spending toward training workers in AI so that industries can figure out how to use AI and make sure there are jobs for workers in AI.
That seems backwards. That said, I do think this is the best you could frame solving the actual problem of “Employers don’t know what they want from the AI, and we don’t know how to train workers here” in language that could make it through the White House’s “Employers are always right” filters.
And there are some things to like here under the hood. The funding opportunity talks about integration of AI into workplaces, which is where the research suggests there may be actual new jobs to be had (and at least a decent chance of keeping a job at a certain employer).
The question is whether that will get through and produce projects that lead to good and interesting results. I don’t think every reader—including those at employers that might benefit from the cash—will do the close reading I did and may be confused as to why they are training workers in skills they don’t know if their company even needs yet.
Meanwhile, the White House seems to be less bullish these days on the “light regulation” that AI companies have pushed for after a recent scare from a new Anthropic model. I don’t see the White House taking a heavier hand around AI and jobs—although ask me again after the midterms if companies keep blaming layoffs on The Robots—but we’re near a point where the Administration needs to start delivering on its promises of a Robo-Jobs Utopia.
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My thoughts on that story about how big employers are doubling down on hiring from elite colleges after complaining about the talent market.
Specifically, this story.
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