[mmaunder]

I have the utmost respect for the work that Jeremy and team and Fast.ai have accomplished but in this post Rachel is railing against the free market, bugs in software and preexisting biases in humans to create an incredibly cynical and unrelated cocktail.

There are many things broken about our world. We should work hard to fix them. But the promise of AI as a research tool to create the kinds of breakthroughs that humans aren’t capable of is undeniable.

Footnote: I think the context of her thinking is very much around the categorization and management of patients, which doesn’t necessarily relate to “AI will cure cancer”.

[jph00]

Rachel and I are well aware of the promise of AI as a research tool. I created the first company that focussed on deep learning in medicine. Rachel has a PhD in math and is now doing a masters in immunology, and is trying to help figure out to bring AI to medical research.

The point of the article is that AI as a research tool is insufficient to result in improvements to patient outcomes on its own. The article includes, for instance, the example that better MRI interpretation doesn't help those people that are being refused an MRI.

Rachel and I quit our jobs and spent years, entirely for free, helping make AI more accessible to more people. We did that because we think AI is great! Pointing out that helping patients requires more than just AI is not anti-tech, it's pro-human.

We can care about both the technology and the context in which it operates.

[jdthedisciple]

> The article includes, for instance, the example that better MRI interpretation doesn't help those people that are being refused an MRI.

Aren't those two entirely orthogonal issues though?

[hobom]

Like the OP, I also greatly respect the work Rachel and you did for AI.

Nevertheless, I can't help but think that you are seeing this issue to negatively.

"The point of the article is that AI as a research tool is insufficient to result in improvements to patient outcomes on its own." This seems unlikely if you consider this question as-is. Past technological improvements has made healthcare better overall without requiring societal changes necessarily. Take mRNA vaccines, a technology that has improved Covid-19 outcomes tremendously. Sure, certain groups have less access than other groups, but surely even marginalized groups are better off overall because of the existence of these vaccines. Health is not a zero-sum game.

And I think this negative attitude also misses the potential of AI by default. Yeah it sucks that not everyone gets MRI access, but those that do will benefit, including marginalized groups. I guess it feels wrong to some people to express a positive sentiment at an unjust state of affairs, but improved diagnosis and treatments translate into lives saved.

You also have to compare AI to the status quo. Sure, AI will have biases, but so do humans (as Rachel points out!) and the decisive question is whether AI has less biases (similarly to how safety of self driving cars is judged). With AI you at least have a chance of analyzing the decision making, and making it objective. We should be extremely excited about this possibility!

[mmaunder]

Thanks Jeremy. Makes sense. What you all have accomplished is incredible, particularly in democratizing AI via your learning materials. Fast.ai is required learning for our team.

[idopmstuff]

Yeah, I was kind of baffled by this - she starts by talking about the problems with automated systems, but when she gets to the part about the medical system she starts with the example of human doctors not listening to their patient. Not to say AI is inherently better than humans in this kind of situation, but it's very strange to make the case that AI in medicine is bad because human doctors have bias.

I expected the article to be about how people misunderstand the difference between knowledge and intelligence. No matter how smart AI is, it can't just magically invent a cure for cancer - it has to gather the knowledge of how things interact and what effects drugs have.

Still, AI does have lots of potential to improve things there. My wife is a Research Associate in a biotech startup, and she could basically be replaced by humanoid robots to run experiments (probably don't even have to go that far - there are cloud labs already) and AI to run analysis. The analysis will be much faster and the robots can work 24/7, so you could really increase throughput of experimentation.