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Dr Khullar suggests that AI will exacerbate biases in medical practice. His fundamental concern is that machine learning will codify biases and become self-fulf
by kevinalexbrown 8y ago
Dr Khullar suggests that AI will exacerbate biases in medical practice. His fundamental concern is that machine learning will codify biases and become self-fulfilling prophesies. But there is scant evidence that AI will worsen these disparities.
If anything, a machine-learning point of view better addresses his concerns than a traditional one, because they can be much more quickly updated to correct for identified biases. Doctors spend years and years of hard work becoming efficient and effective human algorithms themselves, and updating those human algorithms in the face of newer evidence is difficult. In standard practice, biases are often invisible and uncodified to begin with. "Moral intuition" is something all doctors use, but it's also something of a black box in nearly every real-world use case.
- deleted 8y ago[deleted]
- TuringNYC 8y agoI'm speaking as former CTO/Co-Founder of medical image ML firm (for 3yrs): 1. there is already a major bias in medical diagnosis - a bias favoring those who can actually pay 2. automating even parts of the diagnostic process saves money and reduces cost, that is a huge benefit to everyone 3. not everything gets done immediately. lets figure out the basics first (getting classifiers working on whatever dataset we have) and then focus on getting it to work on everything. It isnt like medicine was right from day one...heck, I seem to recall leeches and bloodletting being the norm for a long time. 4. Almost every doctor i spoke to was afraid of ML/AI because it pierced their forced scarcity and threatened their wages. I might argue that Health Disparities are worsened currently because medical boards throttle residency programs and fellowships to create an artificially constrained supply and hence high prices. (before I get the rot response of...of course doctors will never go away...:yes, they wont go away, but they will focus less on rote things and increase throughput thus increase supply thus decrease wages. 5. We got all our training data from minorities. Incidentally, foreign countries are a lot more generous with training data. For our ML diagnostic firm, we had envisioned giving the product away for free in poorer countries where we could just get training data.
- nradov 8y agoHow do medical boards throttle residency programs? The biggest limiting factor today is the Medicare funding cap. https://news.aamc.org/for-the-media/article/gme-funding-doctor-shortage/ https://news.aamc.org/for-the-media/article/gme-funding-doct...
- TuringNYC 8y agoIn the US, the average resident makes ~57k USD these days. If you're familiar with medical bill rates in the US, a week of billings covers the entire annual salary. For specialists (e.g., derm, radiology, etc) a day of billing can cover the entire annual salary for the resident. Even if you assume not all bills are collected, or that many are negotiated down by insurers, the profit margin on residents is off the charts. Given billing rates, "we dont have money" is a very convenient answer for why there arent more residents (and hence more future supply of doctors.) Heck, given the wild profit of a resident, I'd personally fund their annual salary for a share of the annual billings. The real answer is...current doctors, specifically specialty boards must actually be willing to train a resident, however they are funded (medicare, by hospitals, by me, etc.) -- and specialty boards do not. It would increase supply and decrease their future wages. Openings are very carefully throttled to create artificial scarcity. Medical specialty boards are essentially cartels. This is hard to imagine as a technologist because we largely operate in a free market. Anyone can enter the market and opt to work for less money than you. A foreign worker can try to do your job for less. The job can be off-shored.
- nradov 8y agoYou don't understand how it works. Specialty boards don't control funding for residency programs.
- felix_nagaand 8y agoThen explain how these things work instead of just giving a glib "you're wrong. Why? Because I said so. "
- screye 8y agoFairness in AI/ML has been a huge talking point over the last 2 years in the community. I know of around 2 panels/conferences with major industry/academic participation in the US that are scheduled in the next few months. Contrary to the image of mathematicians being rather consequence averse metric driven people, I have found University labs place a large emphasis on trying make sure their models do not have such biases. It is a serious issue worth attention, but the response from the community has been prompt.