321–330 of 486 posts
Earlier quoted context omitted.
Self-care is being Karen since when?
It's not. I was trying to evoke a world where it's become so common place that you're a nuisance if you're one of those people who questions it.
This article shows its more likely tech/software is probably the first major job to be disrupted significantly before other industries. There is an assumption from tech workers that you need a tech person to employ the AI to do the automation meaning they are the last to go. I think that assumption is questionable if AI gets good enough. Especially if I can get "spec writers/QA's/BA's/etc" to do the automation of industries once the regulation/liability side is worked out per industry. Hearing and seeing more than just rumors of AI tooling that mirrors whole software developer workflows being trialed in large tech firms now; SWE is the lowest juiciest hanging fruit.
I still assert that the next industry to feel the most pain is the SWE's and tech workers themselves. Skills and expertise in an AI world are no longer moats to your job security and ability to provide for yourself -> regulation, lack of data, physical world interaction, liability, locality. Most professions have some of the above.
Anecdotally in my local social circle as an SWE I'm now seen as the person with the least desirable job from a social status and security perspective, a massive change from 5 years ago. People would rather be a "truck driver" or in this case a "radiologist". I hope I'm wrong of course for my own personal sake.
Earlier quoted context omitted.
As an ER doc I look at a lot of my own studies, because I'm often using my interpretation to guide real-time management (making decisions that can't wait for a radiologist). I've gotten much better over time, and I would speculate that I'm one of the better doctors in my small hospital at reading my own X-rays, CTs, and ultrasounds. I am nowhere near as good as our worst radiologist (who is, frankly... not great). It…
I’m fascinated. What makes a great radiologist so much better than the average?
I hurt my arm a while back and the ER guy didn't spot the radial head fracture, but the specialist did. No big deal since the treatment was the same either way.
I find that SWE's and tech staff usually think -> if it take my job that means everything else is able to be automated and we no longer need people to automate things. This and other articles show me most professions have more than just the skill component to them unlike SWE. The more I read the more likely I think it will probably only be software and tech as a relatively high paid job (there are industries at lower…
This said, interpreting images is not an image problem - it’s a human body reasoning problem. If you can’t have AI that replaces any engineer, I’d assume replacing a doctor will be just as unlikely. The healthcare bar is much higher - works in 80% of the coding scenarios may be good enough for software, it’s not good for life critical decisions.
So likely we’re not seeing any impact on jobs from AI in relevant health sectors. Now if you your friends think that the rest of paper pushing won’t be affected, or that their jobs entail some unique people skills, they’re in for a big surprise.
I'm an interventional radiologist with a master's in computer science. People outside radiology don't get why AI hasn't taken over. Can AI read diagnostic images better than a radiologist? Almost certainly the answer is (or will be) yes. Will radiologists be replaced? Almost certainly the answer is no. Why not? Medical risk. Unless the law changes, a radiologist will have to sign off on each imaging report. So say yo…
This is like saying that self-driving cars won't ever become a thing because someone behind the wheel needs to be to blame. The article cites AI systems that the FDA already has cleared to operate without a physicians' validation.
It's the same way that we can save time and money if we just don't wash our hands when cooking food. Sure it's true. But someone WILL get sick and we WILL get in trouble for it
I'm an interventional radiologist with a master's in computer science. People outside radiology don't get why AI hasn't taken over. Can AI read diagnostic images better than a radiologist? Almost certainly the answer is (or will be) yes. Will radiologists be replaced? Almost certainly the answer is no. Why not? Medical risk. Unless the law changes, a radiologist will have to sign off on each imaging report. So say yo…
But this indicates lack of incentives to reduce healthcare costs by optimisation. If AI can do something well enough , and AI + humans surpass humans leading to costs reductions/ increased throughput this should be reflected in the workflows. I feel that human processes have inertia and for lack of a better word, gatekeepers feel that new, novel approaches should be adopted slowly and which is why we are not seeing t…
But it doesn't lead to increased throughput because there needs to be human validation when people's lives are on the line.
Planes fly themselves these days, it doesn't increase the "throughout" or eliminate the need for a qualified pilot (and even a copilot!)
When Tesla demoed (via video) self-driving in 2016 with a claim "The person in the driver’s seat is only there for legal reasons. He is not doing anything. The car is driving itself" and then when they unveiled Semi in 2017 - I tweeted out and honestly thought that trucking industry is changed forever and it doesn't make sense to be starting in trucking industry. It's almost end of 2025 and either nothing out of it o…
Look at Waymo, not Robotaxi. Waymo is essentially the self driving vision I had as a kid, and ridership is growing exponentially as they expand. It's also very safe if you believe their statistics[0]. I think there's a saying about overestimating stuff in the short term and underestimating stuff in the long term that seems to apply here, though the radiologist narrative was definitely wrong. [0] https://waymo.com/saf…
"We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten."
I think about this quote a lot these days, especially while reading Hacker News. On one hand, AI doesn't seem to be having the productivity and economic impacts that were predicted, but on the other, LLMs are getting gold medals at the Math Olympiads. It's like the ground is shifting beneath our feet, but it's still too slow to be perceptible.
Earlier quoted context omitted.
As an ER doc I look at a lot of my own studies, because I'm often using my interpretation to guide real-time management (making decisions that can't wait for a radiologist). I've gotten much better over time, and I would speculate that I'm one of the better doctors in my small hospital at reading my own X-rays, CTs, and ultrasounds. I am nowhere near as good as our worst radiologist (who is, frankly... not great). It…
I’m fascinated. What makes a great radiologist so much better than the average?
Earlier quoted context omitted.
But this indicates lack of incentives to reduce healthcare costs by optimisation. If AI can do something well enough , and AI + humans surpass humans leading to costs reductions/ increased throughput this should be reflected in the workflows. I feel that human processes have inertia and for lack of a better word, gatekeepers feel that new, novel approaches should be adopted slowly and which is why we are not seeing t…
Three things explain this. First, while models beat humans on benchmarks, the standardized tests designed to measure AI performance, they struggle to replicate this performance in hospital conditions. Most tools can only diagnose abnormalities that are common in training data, and models often don’t work as well outside of their test conditions. Second, attempts to give models more tasks have run into legal hurdles:…
> The performance of a tool can drop as much as 20 percentage points when it is tested out of sample, on data from other hospitals. In one study, a pneumonia detection model trained on chest X-rays from a single hospital performed substantially worse when tested at a different hospital.
That screams of over fitting to the training data.
I find that SWE's and tech staff usually think -> if it take my job that means everything else is able to be automated and we no longer need people to automate things. This and other articles show me most professions have more than just the skill component to them unlike SWE. The more I read the more likely I think it will probably only be software and tech as a relatively high paid job (there are industries at lower…
I think you haven’t seen what most white collar jobs entail. Briefly - it’s stuff software has been automating Incompletely, somewhat badly for the past 70 years. If you automate x% of software developers it means you already automated at least the same percent of every white collar job out there. Exceptions are regulated sectors - like healthcare. This said, interpreting images is not an image problem - it’s a human…
Most engineers, even accountants, any profession with a title really that required some study usually have the moat of liability and/or locality. SWE's don't really have this in general - a unique job that while requiring a degree for many high tech orgs, will be the first to go. As you said 80% is enough for many domains here. Any other engineering profession (e.g. electrical, civil) has other moats that mean they won't be as disrupted.
Most of the people I talk to w.r.t this issue studied in general professions or trades, physical jobs. i.e. SWE is especially affected especially at the higher end where study was required because for the same "effort" of a CS/Engineering degree you could of been in any other profession where there was more protection from AI (bootcamps aside). AI may have the CS/SWE university pathway be redundant - ironic if most college/uni jobs are still safe except for the industry that birthed the AI in the first place.