"AI went from being very terrible to seemingly genuinely quite good at a professional level in a very short space of time..." says the Verge's AI reporter. But AI systems "are still truly, truly terrible at some areas of math... even the days of the week." If you look at academic math papers, a lot of the time you won't see numbers... So they're still terrible, but they're now also very good at this other part. As to why, at some point you reach a critical mass of what these systems can do. We saw it with writing, we've seen it with programming. They're very good at forging connections between different areas, applying old methods in new ways, those kinds of things. It appears that the newer models they're training have apparently reached that level where it clicks, and now it can do math... There are areas now where it seems to be producing work that is on par with good mathematicians, alongside other parts where yeah, it can't count. All caught up in that is whether it's going to rewrite employment structures or funding structures... One would hope [math researchers] would branch out into all of these new exciting areas or pose new questions. But AI won't do that, and that's the concern. And then that would leave the field quite sterile, and it will have all of these things that have been done, and maybe nothing left to pursue... [A] lot are scared that it's closing off the field. So by definition, those breakthroughs that lead to something surprising and new that you can say, "Oh, this works here," may not be happening anymore... There were some bleak responses from graduate students I saw in essays posted online. Where's their place in this as future researchers? Do they have a place in this? Is it as glorified AI proof checkers? That will be quite an unsatisfying career, I imagine. Or maybe not, I don't know. We will see. I think anything used properly will be a net boon. They also had an interesting response when asked if AI democratizes access to high-level mathematical proofs: A lot of the mathematicians I spoke to were almost quite weary of this, actually. They love the idea, in theory, of democratizing access. They're also quite fed up with AI-generated or -assisted papers that are flooding every publication imaginable, as well as the pre-print servers that they use in these fields. Some of those I spoke to said things like, "Oh, I got three emails this week alone with people being like, 'Hey, is this legit?'" Because they thought they'd solved something with ChatGPT or with Claude, and they also don't have the mathematical skills to check whether they've actually solved something. On the flip side, there are parts where they said, "Well, we've got a talented undergrad who's done something that a talented undergrad would probably have never managed, and here they are doing grad-level work and they've produced a paper that is legit." And in the bigger scheme of things, a few I spoke to said, "Well yeah, a lot of these are in the ivory tower. Having access to this kind of thing globally could really boost access to the kind of things here." On the flip side, the cost. These things cost a lot to run.

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47% of recent graduates say AI has already impacted hiring in their field, according to an April survey from ZipRecruiter. "But is AI really the problem, or is it more complicated?" asks NPR. "Here's what economists have to say." According to the Federal Reserve Bank of New York, the unemployment rate for recent graduates — which it defines as 22-to-27-year-olds with a new bachelor's degree or higher — was 5.7% as of June, more than the rate for all workers, which stands at 4.1%... Stanford University economist Erik Brynjolfsson says AI is impacting the labor market for entry-level roles. "AI is not the whole story, but it's part of the story and the evidence is building," he says. Using payroll data, Brynjolfsson and his co-authors found that since late 2022 — when large language models like ChatGPT started popping up — early-career workers ages 22 to 25 in AI-exposed roles, like software developers and marketing managers, have experienced a 16% relative employment decline. In comparison, employment rates for older workers in AI-exposed fields and for all workers in jobs that aren't easily automated — like home health aides, physical therapists and construction workers — remained stable or have grown over that same time period... [Though he also says often when companies pull back on hiring, they cut junior roles first.] Harvard University economist David Deming isn't convinced that AI is to blame for the challenging early-career job market. "If you look very carefully at the timing, it looks like the decline in junior hiring actually started a bit like six months before ChatGPT was released. And so what that tells me is it's something else," Deming says. "I think it's more like remote work." A recent analysis from the New York Fed found that companies are less likely to hire recent college grads into roles that can be done remotely. As remote jobs increased following the COVID-19 pandemic, so did unemployment among younger college grads, the New York Fed found. The analysis also found that AI didn't explain the rise in unemployment among younger workers and that remote work was more of a driving force... Employers hiring for remote jobs may be less likely to choose an entry-level candidate because it's harder to train them from afar... [And with remote positions, there's many more senior candidates to choose from.] And here's another thing to consider: University of Chicago economist Anders Humlum says if AI were replacing entry-level jobs, you'd expect to see companies that rely heavily on AI to hire fewer workers. But that's not what the data shows. Humlum points to a study done by the financial accounting firm Ramp and the workforce research company Revelio Labs. The study examined AI spending and employee head count across more than 21,000 U.S. firms, from early 2021 to early 2026. It found that at companies making the largest AI investments, entry-level head count grew by 12% over the two years following AI adoption.

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According to a post from chief product officer Hari Srinivasan, "over a million people" have clicked on LinkedIn's new "Seems like AI slop" button, which launched after one analysis found 41% of the platform's longform posts were fully AI-generated. The Verge reports: In Thursday's post, Srinivasan said that users are overall "now experiencing 40% less views on what we classify as AI slop from just a few weeks ago." LinkedIn is also adding a new message that will tell users who make a post if "Some members told us this post seems like AI." "We approached this assuming good intent; I know I'm increasingly conscious on how to not sound like AI & the goal is to provide helpful feedback," Srinivasan said.

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