{"id":20723,"date":"2026-04-06T16:41:09","date_gmt":"2026-04-06T16:41:09","guid":{"rendered":"https:\/\/ideainthebox.com\/index.php\/2026\/04\/06\/the-one-piece-of-data-that-could-actually-shed-light-on-your-job-and-ai\/"},"modified":"2026-04-06T16:41:09","modified_gmt":"2026-04-06T16:41:09","slug":"the-one-piece-of-data-that-could-actually-shed-light-on-your-job-and-ai","status":"publish","type":"post","link":"https:\/\/ideainthebox.com\/index.php\/2026\/04\/06\/the-one-piece-of-data-that-could-actually-shed-light-on-your-job-and-ai\/","title":{"rendered":"The one piece of data that could actually shed light on your job and AI"},"content":{"rendered":"
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This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first,\u00a0<\/em>sign up here<\/em><\/a>.<\/em><\/p>\n

Within Silicon Valley\u2019s orbit, an AI-fueled jobs apocalypse is spoken about as a given. The mood is so grim that a societal impacts researcher at Anthropic, responding Wednesday to a call for more optimistic<\/em> visions of AI\u2019s future, said<\/a> there might be a recession in the near term and a \u201cbreakdown of the early-career ladder.\u201d Her less-measured colleague Dario Amodei, the company\u2019s CEO, has called<\/a> AI \u201ca general labor substitute for humans\u201d that could do all jobs in less than five years. And those ideas are not<\/a> just coming from Anthropic, of course.\u00a0<\/p>\n

These conversations have unsurprisingly left many workers in a panic (and are probably contributing to support for efforts to entirely pause the construction<\/a> of data centers, some of which gained steam last week). The panic isn\u2019t being helped by lawmakers, none of whom<\/a> have articulated a coherent plan for what comes next.<\/p>\n

Even economists who have cautioned<\/a> that AI has not yet cut jobs and may not result in a cliff ahead are coming around<\/a> to the idea that it could have a unique and unprecedented impact on how we work.\u00a0<\/p>\n

Alex Imas, based at the University of Chicago, is one of those economists. He shared two things with me when we spoke on Friday morning: a blunt assessment that our tools for predicting what this will look like are pretty abysmal, and a \u201ccall to arms\u201d for economists to start collecting the one type of data that could make a plan to address AI in the workforce possible at all.\u00a0<\/p>\n

On our abysmal tools: consider the fact that any job is made up of individual tasks. One part of a real estate agent\u2019s job, for example, is to ask clients what sort of property they want to buy. The US government chronicled thousands of these tasks in a massive catalogue<\/a> first launched in 1998 and updated regularly since then. This was the data that researchers at OpenAI used in December to judge how \u201cexposed<\/a>\u201d a job is to AI (they found a real estate agent to be 28% exposed, for example). Then in February, Anthropic used this data in its analysis of millions of Claude conversations to see which tasks<\/a> people are actually using its AI to complete and where the two lists overlapped.<\/p>\n

But knowing the AI exposure of tasks leads to an illusory understanding of how much a given job is at risk, Imas says. \u201cExposure alone is a completely meaningless tool for predicting displacement,\u201d he told me.<\/p>\n

Sure, it is illustrative in the gloomiest case\u2014for a job in which literally every task<\/em> could be done by AI with no human direction. If it costs less for an AI model to do all those tasks than what you\u2019re paid\u2014which is not a given, since reasoning models and agentic AI can rack up quite a bill<\/a>\u2014and it can do them well, the job likely disappears, Imas says. This is the oft-mentioned case of the elevator operator from decades ago; maybe today\u2019s parallel is a customer service agent solely doing phone call triage.\u00a0<\/p>\n

But for the vast majority of jobs, the case is not so simple. And the specifics matter, too: Some jobs are likely to have dark days ahead, but knowing how<\/em> and when<\/em> this will play out is hard to answer when only looking at exposure.<\/p>\n

Take writing code, for example. Someone who builds premium dating apps, let\u2019s say, might use AI coding tools to create in one day what used to take three days. That means the worker is more productive. The worker\u2019s employer, spending the same amount of money, can now get more output. So then will the employer want more employees or fewer?\u00a0<\/p>\n

This is the question that Imas says should keep any policymaker up at night, because the answer will change depending on the industry. And we are operating in the dark.\u00a0<\/p>\n

In this coder\u2019s case, these efficiencies make it possible for dating apps to lower prices. (A skeptic might expect companies to simply pocket the gains, but in a competitive market, they risk being undercut if they do.) These lower prices will always drive some<\/em> increase in demand for the apps. But how much? If millions more people want it, the company might grow and ultimately hire more<\/em> engineers to meet this demand. But if demand barely ticks up\u2014maybe the people who don\u2019t use premium dating apps still won\u2019t want them even at a lower price\u2014fewer coders are needed, and layoffs will happen.<\/p>\n

Repeat this hypothetical across every job with tasks that AI can do, and you have the most pressing economic question of our time: the specifics of price elasticity, or how much demand for something changes when its price changes. And this is the second part of what Imas emphasized last week: We don\u2019t currently have this data across the economy. But we could<\/em>.\u00a0<\/p>\n

We do have the numbers for grocery items like cereal and milk, Imas says, because the University of Chicago partners with supermarkets to get data from their price scanners. But we don\u2019t have such figures for tutors or web developers or dietitians (all jobs found to have \u201cexposure\u201d to AI, by the way). Or at least not in a way that\u2019s been widely compiled or made accessible to researchers; sometimes it\u2019s scattered across private companies or consultancies.\u00a0<\/p>\n

\u201cWe need, like, a Manhattan Project to collect this,\u201d Imas says. And we don\u2019t need it just for jobs that could obviously be affected by AI now: \u201cFields that are not exposed now will become exposed in the future, so you just want to track these statistics across the entire economy.\u201d<\/p>\n

Getting all this information would take time and money, but Imas makes the case that it\u2019s worth it; it would give economists the first realistic look at how our AI-enabled future could unfold and give policymakers a shot at making a plan for it.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

This story originally appeared in The Algorithm, our weekly newsletter […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[226],"tags":[],"class_list":["post-20723","post","type-post","status-publish","format-standard","hentry","category-technology"],"acf":[],"_links":{"self":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/posts\/20723","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/comments?post=20723"}],"version-history":[{"count":0,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/posts\/20723\/revisions"}],"wp:attachment":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/media?parent=20723"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/categories?post=20723"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/tags?post=20723"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}