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> Generalist biomedical artificial intelligence (AI) systems that flexibly encode, integrate, and interpret this data at scale can potentially enable impactful applications ranging from scientific discovery to care delivery.
The problem with AI models is it may bring us medical innovations that are actually harmful to humanity, such as increased lifespans, which in turn will drive further overpopulation.
From the abstract: > Generalist biomedical artificial intelligence (AI) systems that flexibly encode, integrate, and interpret this data at scale can potentially enable impactful applications ranging from scientific discovery to care delivery. The problem with AI models is it may bring us medical innovations that are actually harmful to humanity, such as increased lifespans, which in turn will drive further overpopul…
From the abstract: > Generalist biomedical artificial intelligence (AI) systems that flexibly encode, integrate, and interpret this data at scale can potentially enable impactful applications ranging from scientific discovery to care delivery. The problem with AI models is it may bring us medical innovations that are actually harmful to humanity, such as increased lifespans, which in turn will drive further overpopul…
I know you're trolling, but don't worry AI would have the answer to this solution too!! Don't you get it?
From the abstract: > Generalist biomedical artificial intelligence (AI) systems that flexibly encode, integrate, and interpret this data at scale can potentially enable impactful applications ranging from scientific discovery to care delivery. The problem with AI models is it may bring us medical innovations that are actually harmful to humanity, such as increased lifespans, which in turn will drive further overpopul…
All being said and done with respect to AI in medicine, Doctors and medical professionals will be the very last people to be replaced. Care (both physical and mental) will be the last bastion of humanity disrupted by AI.
Why? Medical practice is very knowledge intensive, especially general practice. Very prone to human error, have you seen the stats on accidental deaths in hospitals? Excellent high-value use for (future) learning systems which can ingest and apply a large body of knowledge and reason in the face of a huge poorly understood graph of causal factors. No, the last people to be replaced will be those doing unpaid labour,…
I choose my GP based on my ability to trust and empathize with him, not because of his grades in medical school.
Medicine is an intrinsically human activity. It may be augmented and improved by AI, but people are still going to want human medics around, it’s just the nature of being sick.
From the abstract: > Generalist biomedical artificial intelligence (AI) systems that flexibly encode, integrate, and interpret this data at scale can potentially enable impactful applications ranging from scientific discovery to care delivery. The problem with AI models is it may bring us medical innovations that are actually harmful to humanity, such as increased lifespans, which in turn will drive further overpopul…
If we actually reach a point of technological singularity, it may well be the case that we are living amongst the stars within 10 years. Nobody knows. I wouldn't worry too much.
From the abstract: > Generalist biomedical artificial intelligence (AI) systems that flexibly encode, integrate, and interpret this data at scale can potentially enable impactful applications ranging from scientific discovery to care delivery. The problem with AI models is it may bring us medical innovations that are actually harmful to humanity, such as increased lifespans, which in turn will drive further overpopul…
You don't think they may also bring us transportation, agricultural and logistical innovations that will make increasing the population a non-issue? If we actually reach a point of technological singularity, it may well be the case that we are living amongst the stars within 10 years. Nobody knows. I wouldn't worry too much.
No, new developments in transportation are unlikely to solve anything, except give some people more space in the short-term, and cause even more habitat destruction. New efficiencies in agriculture will help in the short term, but then make producing new humans even more efficient, causing even more destruction.
As for your predictions that we will be living in the stars, that's depressing. On spaceships and barren planets? Think terraforming will help? We can't even take care of one of the easiest planets on the solar system, earth.
I won't take any of this seriously until they make their model and weights available. This type of PR research is what is really holding back AI for medical images.
My impression of what's holding back improvements to CV and ML for medical images is that close to none of the research in the field will ever be put into practice. There's a huge amount of research done and then the companies actually producing the software used by technicians and doctors choose a tiny number of things to pick up, incorporate, test, get certified, and it takes years. People working in the field have…
The evaluation was done on 246 X-rays, which is good; it would be better if they were not all chest X-rays (to see generality), and if there were more than only four radiologists from the same country.
The achieved 0.25 clinically-significant errors is impressive, although it is only for the best of 3 models, which can incur bias; averaged across models, it is 0.27, a bit worse than human error. Additionally, I am wondering where they get the human baseline; they state:
> These results are on par with human baselines from prior work [14]
but the citation[1] doesn’t give data in the same format (and its format is honestly better: it indicates that humans make no urgent errors or worse in 64% of reports).
Surprisingly, there is no improvement with model size; the largest model performs the worst.
Earlier quoted context omitted.
Why? Medical practice is very knowledge intensive, especially general practice. Very prone to human error, have you seen the stats on accidental deaths in hospitals? Excellent high-value use for (future) learning systems which can ingest and apply a large body of knowledge and reason in the face of a huge poorly understood graph of causal factors. No, the last people to be replaced will be those doing unpaid labour,…
It is technically possible today for patients in hospital to have their food delivered by robot, yet most people would have a strong aversion to that idea: the presence of other humans helps us to have the will to get better. I choose my GP based on my ability to trust and empathize with him, not because of his grades in medical school. Medicine is an intrinsically human activity. It may be augmented and improved by…
I agree the direct interface to a lot of medicine needs to be a human as we need human assurance when we are sick and scared. Bed side manner can’t be replace to devalued. But we suffer from critical shortages of medical workers, many of whom can be augmented powerfully with knowledge machines.
My understanding is the real barrier is providers themselves find the user interfaces counter intuitive, aren’t afforded time to train on new systems, and are under so much pressure to produce with such a limited staff they can’t spend the time and energy to work these tools into their workflows. Add on to that the regulatory hurdles to innovation, general risk aversion in the development field, complexities of selling unproven tech into unsophisticated hospital network administration, etc, it’s no wonder it’s a slow slog. It’ll take someone like Kaiser really committing material capital, time, resources, and mandating adoption with a significant training program to see any success.