I’m a neurology ICU nurse. The creep of AI in our hospitals terrifies me.
I’m a neurology ICU nurse. The creep of AI in our hospitals terrifies me.
www.codastory.com
I’m a neurology ICU nurse. The creep of AI in our hospitals terrifies me
19 comments
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"The reasoning for bringing in AI tools to monitor patients is always that it will make life easier for us, but in my experience, technology in healthcare rarely makes things better. It usually just speeds up the factory floor, squeezing more out of us, so they can ultimately hire fewer of us. " - yup and there's not much we can do about it without harming a lot of people.
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Yay we don't have to work anymore! Good news right? Right?!
/s
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The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.
-Bill Gates
19 comments
You need AI to reword this spaghetti of an article. I know plenty of nurses, most of them shouldn’t be making decisions.
But I do agree that slapping AI on everything is a poor idea.
Hasn't AI already been shown to be better at catching things like cancer than humans?
There are some things that computers can be better at than humans.
Yes! And we should use it when it has been proven effective. But the AI shouldn’t be able to administer drugs.
Machine learning for helping a radiologist analyze images is super helpful and a mature field.
Whatever "AI" LLM nonsense tech bros are trying to add in to everything in the last 2 years is probably not all that helpful, but i could be proven wrong
It's also been shown to hallucinate whole parts of the doctor/nurse discussion and instructions
Dogs are can be also better at detecting cancer than humans. And dogs tend to hallucinate less
Yes... well, sorta. For example, AI was found to be better at identifying TB than medical doctors. The catch here is that it also falsely diagnosed st a much higher rate than doctors. When an investigation was done as to how the AI was evaluating the imaging that it was given, they found that sets of virtually indistinguishable images were given different diagnoses by the AI. In many cases where there were no visible indicators of TB, a positive diagnosis wss given. The reason for this is that the AI was not weighting their TB diagnosis based on markers that doctors would look for alone, but also the age of the machine. Older machines have a much greater chance of being located in developing countries where TB is both more common and more deadly, leading to the age of the machine being considered an important factor, whereas a human would know that the age of a machine has absolutely zero relationship with the chance of getting TB, and doctors in these areas are already aware of and watching out for TB as it's a much more serious illness than in Germany, for example.
Idk much about the cancer thing, but basically the machine learning for diagnosis thing is iffy at best afaik.