<\/p>\n
But a closer look at the data shows that students are not necessarily turning away from AI-related careers. Rather, they appear to be tailoring their skills to the changes they see underway as AI becomes increasingly important for various disciplines. Interest is rising in AI-adjacent fields like data science and cybersecurity. One fast-growing major: artificial intelligence itself (a recent addition to many college offerings).<\/p>\n
Anxiety over the potential of AI to replace workers is nothing new. I wrote \u201cHow Technology Is Destroying Jobs\u201d in 2013, describing how a slew of new digital technologies, including AI, were beginning to threaten white-collar work. I wasn\u2019t alone. It was a popular theme at a time when the labor market was sluggish and jobs were scarce.\u00a0<\/p>\n
In one of his last days in office in late 2016, President Obama issued a report written by his top economic and science advisors warning that AI was threatening workers. Among the findings was that automated vehicles\u2014especially driverless trucks\u2014could eliminate 2.2 million to 3.1 million existing US jobs.\u00a0 Around the same time, one of the pioneers of AI, Geoffrey Hinton, said that \u201cpeople should stop training radiologists\u201d because it was \u201ccompletely obvious\u201d the occupation was soon to be replaced by AI.<\/p>\n
None of these predictions came true, of course (nor did so-called technological unemployment occur during several earlier tech-related job panics). The forecasts were often wrong about the pace of the technological advances\u2014we\u2019re still waiting for fleets of driverless trucks on the highways\u2014and failed to understand the complex portfolio of tasks that make up many jobs. AI has indeed become a tool for screening radiology images, but there are more radiologists than ever. It turns out that human radiologists perform a multitude of valuable tasks, including interpreting results and interacting with patients, that can\u2019t be accomplished with AI (yet).<\/p>\n<\/p><\/div>\n
Perhaps this time is different, and we can put aside the lessons of economic history. Certainly, AI has gained unimaginable powers to do humanlike tasks. Perhaps it will devour jobs in ways that we\u2019ve never seen before. And perhaps that will happen abruptly, without a warning buried in the labor statistics. But the previous bouts of AI job anxiety still hold a prescient lesson: Our real focus needs to be less on the dystopian fears and more on the very real transitions in the workplace that will likely affect millions of people.<\/p>\n
\u201cEven if there is not mass or even increased unemployment, the transition could still be very difficult,\u201d says Jed Kolko, senior fellow at the Peterson Institute for International Economics and former undersecretary of commerce in the Biden administration. \u201cAnd what does a difficult transition period mean? It means people losing jobs, or people\u2019s jobs being redefined in ways that make those jobs pay worse or be less meaningful. And some people whose jobs are threatened may not be able to adapt.\u201d<\/p>\n
The more we understand this transition, the better prepared we\u2019ll be to deal with it.\u00a0 And for that we\u2019ll need better and more complete data.<\/p>\n
For McEntarfer, the former commissioner of the BLS, the real question is the speed of any disruption. \u201cIf it happens at the normal pace of technological change, labor markets will have time to adapt. If there is a sudden and severe disruption, then that will be a big challenge for policymakers,\u201d she says. \u201cThat\u2019s really the most important question facing us right now: how rapid this transformation is going to be.\u201d And, she adds, \u201cwe\u2019ll know by watching the data.\u201d<\/p>\n
Two decades ago, the country was caught flat-footed by the so-called China shock as free-trade policies led to an influx of imports and the devastation of manufacturing jobs in many parts of the country. It took years for researchers to understand the data showing how the trade policies, generally welcomed by economists, were destroying communities. Today the threat of an economic transformation brought on by AI is far larger and points to potentially far more damage for huge groups of workers.<\/p>\n<\/div>\n
#reality #check #jobs #hysteria<\/p>\n","protected":false},"excerpt":{"rendered":"
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