Canaries in the Coal Mine? - Page 1
Forum section: electronics / general

author: Picuino
author_rank: Super Contributor
timestamp: August 30, 2025, 02:14:16 pm
content: Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligencehttps://digitaleconomy.stanford.edu/wp-content/uploads/2025/08/Canaries_BrynjolfssonChandarChen.pdf"""AbstractThis paper examines changes in the labor market for occupations exposed to generative artificial intelligence using high-frequency administrative data from the largest payroll software provider in the United States. We present six facts that characterize these shifts. We find that since the widespread adoption of generative AI, early-career workers (ages 22-25) in the most AI-exposed occupations have experienced a 13 percent relative decline in employment even after controlling for firm-level shocks. In contrast, employment for workers in less exposed fields and more experienced workers in the same occupations has remained stable or continued to grow. We also find that adjustments occur primarily through employment rather than compensation. Furthermore, employment declines are concentrated in occupations where AI is more likely to automate, rather than augment, human labor. Our results are robust to alternative explanations, such as excluding technology-related firms and excluding occupations amenable to remote work. These six facts provide early, large-scale evidence consistent with the hypothesis that the AI revolution is beginning to have a significant and disproportionate impact on entry-level workers in the American labor market."""

author: Picuino
author_rank: Super Contributor
timestamp: September 01, 2025, 07:06:04 pm
content: https://medium.com/enrique-dans/when-ai-replaces-not-augments-a-data-driven-look-at-youth-employment-trends-cbda4ef3ccdf

author: tom66
author_rank: Super Contributor
timestamp: September 03, 2025, 08:53:52 am
content: Anecdotally, I've heard stories of junior software engineers finding it really hard to get a job. Quite a bit of the "boring" work like reviewing PRs and writing test benches can be done by AIs, which could be impacting employment there. The trouble is, you do need junior engineers to get a position to create enough senior engineers for the future, so it'll inevitably come back again just because the market has dried up. Assuming AGI doesn't come and bite us all in the rear end.

author: JPortici
author_rank: Super Contributor
timestamp: September 03, 2025, 11:36:32 am
content: Quote from: tom66 on September 03, 2025, 08:53:52 amIf anything LLMs can bullshit people into thinking they're AGI. That would be fun to watch, for a timeMeanwhile, constantly battling the junior when he tells me "i asked chat gpt and he told me..." and i reming him i give zero crap about chatgpt. do the research however you want but then give me YOUR results. I don't understand why it's so hard to get this

author: tszaboo
author_rank: Super Contributor
timestamp: September 03, 2025, 11:44:10 am
content: Quote from: tom66 on September 03, 2025, 08:53:52 amI see it as a force multiplier. A senior engineer with experience can use AI, and when AI makes a mistake he might have a better chance of finding and fixing it. Or calling out the bllsht by the AI.So if you are good at something, you get better. If you are just starting out, you might be worse with the help of the AI. The implications are not good. I'm happy that I don't have to finish university now.

author: abeyer
author_rank: Frequent Contributor
timestamp: September 03, 2025, 08:11:03 pm
content: Quote from: tom66 on September 03, 2025, 08:53:52 amNot that AI isn'talsocontributing... but at least in the US, the job hunting pain for juniors had started well before those tools were as capable and getting as much traction as they are at the moment.The bigger preexisting problem was a nasty combination of two things:There was a glut of people on the market who had been over-promised and under-trained by bootcamp programs that sold themselves as a way to get a six figure salary in two months with no prior experience and no formal education. This meant a lot of competition for junior positions in general, and made it painful for businesses to recruit for them because there were hundreds/thousands of identical looking candidates applying to every one.Businesses over-hired during the pandemic and since then have been trying to shed headcount overall... which means they're hiring less overall, and what they do hire is typically more senior and/or niche skills.

author: Siwastaja
author_rank: Super Contributor
timestamp: September 04, 2025, 05:52:32 am
content: Just the bubble of excess number of software developers with low average skill level, and seriously bloated development processes. This bubble had to burst. As many have noted, it started bursting even before "AI". AI just a scapegoat. Layoffs are hard to explain, but AI allows it to be explained to boards of directors and managers ("we automated the job, isn't that great?") and also to the workers ("sorry, this is just inevitable, but AI is great would you not agree?"). In reality, all of this is just about reducing unnecessary work (and automating some of it as a smoke screen).

author: JPortici
author_rank: Super Contributor
timestamp: September 04, 2025, 07:21:32 am
content: Quote from: abeyer on September 03, 2025, 08:11:03 pmThis is true all over europe as well

author: SiliconWizard
author_rank: Super Contributor
timestamp: September 04, 2025, 02:45:51 pm
content: Quote from: Siwastaja on September 04, 2025, 05:52:32 amYes and no. I'll explain what I mean: the goal is always about reducing *costs*. That's all there is to it. While reducing "unnecessary work" may look like a good means to this end, it's a very elusive one when it comes to engineering in general and software development in particular.Almost nobody, and especially almost no manager - in particular among those that are high-level enough to decide - know how to estimate the engineering work needed for some project and even less so how to define what is strictly necessary and what is not. While that's an approach that works for production, it's well known that it pretty much doesn't for any kind of intellectual work.So those who think they can tell what kind of work on an engineering project is necessary and what is not are deeply deluded, or crooks. Sure, many large teams are suboptimal for various reasons, but getting to define exactly who is necessary and who is not? Let me know how that goes in practice.Just my 2 cents. Engineering is not production, and any attempt at managing it the same way has usually utterly failed. The Mythical Man-Month is just one essay dealing with the concept. And yes, "AI" is just one more silver bullet that's being used for pretending we can handle engineering like production, there we go again.