That’s not what the article is about. I think putting some more objectivety into the decisions you listed for example benefits the majority. Human factors will lean toward minority factions consisting of people of wealth, power, similar race, how “nice” they might be or how many vocal advocates they might have. This paper just states that current AIs aren’t very good at what we would call moral judgment.
It seems like algorithms would be the most objective way to do this, but I could see AI contributing by maybe looking for more complicated outcome trends. Ie. Hey, it looks like people with this gene mutation with chronically uncontrolled hypertension tend to live less than 5years after cardiac transplant - consider weighing your existing algorithm by 0.5%
Creatinin in urine was used as a measure of kidney function for literal decades despite African Americans having lower levels despite worse kidneys by other factors. Creatinine level is/was a primary determinant of transplant eligibility.
Only a few years ago some hospitals have started to use inulin which is a more race and gender neutral measurement of kidney function.
No algorithm matters if the input isn’t comprehensive enough and cost effective biological testing is not.
Tho those complicated outcome trends can have issues with things like minorities having worse health outcomes due to a history of oppression and poorer access to Healthcare. Will definitely need humans overseeing it cause health data can be misleading looking purely at numbers
I wouldn’t say definitely. AI is subject to bias of course as well based on training, but humans are very much so, and inconsistently so too.
If you are putting in a liver in a patient that has poorer access to healthcare they are less likely to have as many life years as someone that has better access. If that corellates with race is this the junction where you want to make a symbolic gesture about equality by using that liver in a situation where it is likely to fail? Some people would say yes. I’d argue that those efforts towards improved equality are better spent further upstream. Gets complicated quickly - if you want it to be objective and scientifically successful, I think the less human bias the better.
That’s not what the article is about. I think putting some more objectivety into the decisions you listed for example benefits the majority. Human factors will lean toward minority factions consisting of people of wealth, power, similar race, how “nice” they might be or how many vocal advocates they might have. This paper just states that current AIs aren’t very good at what we would call moral judgment.
It seems like algorithms would be the most objective way to do this, but I could see AI contributing by maybe looking for more complicated outcome trends. Ie. Hey, it looks like people with this gene mutation with chronically uncontrolled hypertension tend to live less than 5years after cardiac transplant - consider weighing your existing algorithm by 0.5%
Creatinin in urine was used as a measure of kidney function for literal decades despite African Americans having lower levels despite worse kidneys by other factors. Creatinine level is/was a primary determinant of transplant eligibility. Only a few years ago some hospitals have started to use inulin which is a more race and gender neutral measurement of kidney function.
No algorithm matters if the input isn’t comprehensive enough and cost effective biological testing is not.
Well yes. Garbage in garbage out of course.
That’s my point, this is real world data, its all garbage, and no amount of LLM rehashing fixes that.
Sure. The goal is more perfect here, not perfect.
Tho those complicated outcome trends can have issues with things like minorities having worse health outcomes due to a history of oppression and poorer access to Healthcare. Will definitely need humans overseeing it cause health data can be misleading looking purely at numbers
I wouldn’t say definitely. AI is subject to bias of course as well based on training, but humans are very much so, and inconsistently so too. If you are putting in a liver in a patient that has poorer access to healthcare they are less likely to have as many life years as someone that has better access. If that corellates with race is this the junction where you want to make a symbolic gesture about equality by using that liver in a situation where it is likely to fail? Some people would say yes. I’d argue that those efforts towards improved equality are better spent further upstream. Gets complicated quickly - if you want it to be objective and scientifically successful, I think the less human bias the better.
Everyone likes to think that AI is objective, but it is not. It is biased by its training which includes a lot of human bias.