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Chapter 1: What recent changes did OpenAI announce and what do they mean?
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Casey, I miss you.
You are in New York? I am, Kevin. And of course, I miss you as well. But it's always fun to visit the mothership. You know, Ezra Klein just challenged me to a burping contest. So I've got that to look forward to later. Burping or burpy? You know what? I guess I should go read that email again. Okay.
Well, I miss you. We have an empty chair here in San Francisco, and it's not the same.
It's not the same, but I've been catching up on all the latest AI news, Kevin, and I had to ask, have you seen this thing about Codex and the goblins?
Yes, this is the new update to OpenAI's codex that is, like, obsessed with goblins?
Yes, apparently the company had to add instructions to its latest model to forbid codex from randomly mentioning an assortment of mythical and real creatures, including goblins, gremlins, raccoons, trolls, ogres, and pigeons. Or as we call them, our slate of guests on Hardfork.
LAUGHTER
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Chapter 2: How is AI transforming the medical field according to Dr. Adam Rodman?
That makes sense to me. It does seem like their Codex app in particular was really well received. But there's been this other transformation that seems to be unfolding, Kevin.
This week, the Information had this really interesting story where apparently OpenAI projected at the start of the year that its $8 a month subscription, which is called ChatGPT Go, which sort of gives you a little bit of the good stuff, but not as much as if you're paying $20 or more for ChatGPT. They predicted that its Go subscriptions would grow 3%. 36 times this year to 112 million people.
Well, meanwhile, it's $20 a month plus subscriptions would fall 80% to about 9 million. So that's like a really interesting business pivot that I would love to know more about. Of course, it sounds a lot like the new Netflix plan that they rolled out a while back, right? Where it's sort of like, well, you know, it's going to be a
I was curious what you make of that strategy because part of me feels like, well, they'd much rather have the $20 subs than the $8 subs, but maybe there's just a lot more of those $8 subs out there.
Yeah. I think what's happening here is that the market is essentially splitting into two. There's the casual hobby users who are using AI chatbots like ChatGPT, like Cloud for souped up Google queries to help them write e-mails and maybe only using it a couple of times a day. And if you're doing that, you probably don't want to pay $20 a month.
You're probably more comfortable paying $8 a month, or maybe you don't want to pay anything at all, and you'd just rather use the free ad-supported tier of all of this stuff. And then there's the professional users for whom this is worth way more than $20 a month and who are willing to pay many multiples of that to get the access to the latest models, to have higher rate limits.
And so I think all of the companies now are sort of... you know, doing this kind of experimentation with how much can we charge the professional users without losing them to a rival company and how cheap can we make the kind of lower-end subscriptions or the free tiers so that people who are more casual users won't be tempted to go use Google instead.
That makes sense. I'll say for my part, I'd be willing to pay even more for a chat GPT if they would just let the Codex app talk about goblins. I say, free the goblins!
These models are so weird. It is so weird that we have this technology that is now load-bearing infrastructure for the entire economy. That every business is using to completely reinvent the way that it works. And that out of nowhere, if not specially restrained, it will just start talking about goblins.
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Chapter 3: What is Talkie and how does it differ from modern LLMs?
This has been a huge change in my recent visits to doctors, which is that I now am having this series of conversations leading up to the visit with AI systems about what is going on. I am coming armed with what I believe to be good information about what is going on, and that allows me to have a different, more elevated conversation with the doctor. And this is not just me.
People are increasingly turning to chatbots for medical information. According to some recent data, approximately a third of Americans report turning to AI for healthcare information. And companies are racing to respond to that demand by making better tools that are specifically designed for use in healthcare.
So to help us make sense of the landscape for AI and medicine and healthcare, we've invited back to the show one of our favorite doctors, Adam Rodman. He is an internal medicine physician at Beth Israel Deaconess Medical Center and an assistant professor at Harvard Medical School.
Yeah, we last talked to him in November of 2024. And since then, he's continued to study the way that people and AI interact in the healthcare space. And we have a lot of questions for him. Like, what should we do about your rash, Kevin?
Yeah.
Yes. So let's fork over our co-pays and bring in Dr. Adam Rodman.
Dr. Adam Rodman, welcome back to Hard Fork. Oh, it is a pleasure to be here. Am I a friend of the show at this point?
Well, let's see how this interview goes.
You're at least a doctor of the show. You are our primary care physician. So when we last talked to you in late 2024, I think this was a moment where the medical community was starting to say, wait a minute, these AI models are getting pretty good at things like diagnostics. But I think a lot of the field was still kind of in wait-and-see mode.
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Chapter 4: What historical insights can an LLM trained on pre-1930s data provide?
So give us a sense of how this open evidence tool works. What situations is it used for, and what are its strengths and weaknesses?
Oh, that's a great question. So how open evidence works, like all of these tools is a trade secret, but it uses some sort of like retrieval augmented generation and an evidence retrieval tool. And they have all these deals with the big medical journals. So New England Journal of Medicine, JAMA,
And when you ask a clinical query, it searches the evidence and then tries to identify high quality sources. And then it always grounds what's coming back in the literature. So you have gray hairs like me who kind of use open evidence the way that I would use a Google search or one of the old tools.
So I use it as a souped-up way to search the literature rapidly and often go to the primary sources, or I use it as a faster way to get a reference. So a drug that I haven't dosed in a long time, open evidence pulls the drug monographs from the FDA. I can very quickly pull that up. Mm-hmm.
Younger doctors, I have noticed, and I don't know this empirically, but younger doctors are more likely to ask questions like, what could be going on? Can you give me a second opinion? What is the next thing that I should do? So ways that I don't traditionally use decision support or reference tools, but sort of a new way.
And of course, younger doctors also use it in the reference ways that I do.
Okay.
Now, are they actually uploading patient data to this? Or are they just sort of describing patients in generic and anonymized ways to get back some decision support?
Yeah.
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Chapter 5: How are doctors currently using AI in their practices?
Yeah.
I'm curious, Adam, out here in San Francisco, there are all these fitness people and health maxers, people who love to track themselves using all manner of devices, and people are getting these full-body workups from companies like Function Health that are sort of concierge medicine things, and they'll get 100 labs done, and then they'll upload all that data into Claude or ChatGPT and just sort of
treat it as a sort of first line medical professional in their lives. Do you think that is a good practice or is that just making people way too worried about things that maybe they don't need to be worried about?
Yeah, so that's making people way too worried about things they don't need to worry about. And this is chat GPT, LLMs in general. I mean, the dark side of talking to an LLM about your symptoms is they are so sycophantic, they can drive you into like the cyberchondria worry hole.
The evidence is not there yet that the sort of large routine testing functional medicine and putting it into an LLM does anything to improve health outcomes. Now, if your LLM is telling you to work out and eat healthier, that's probably pretty good. Sleep.
Yeah. What about the integrations like ChatGPT Health, which lets you sort of convert your Apple Watch or Fitbit data into something that ChatGPT can analyze? There's also a new version of ChatGPT for clinical use called ChatGPT for Clinicians. Are any of these integrations or projects more promising in your view?
Not yet, but I think it could be at some point. I mean, so ChatGPT for Health pulls in your data from the medical record and lets you chat with your medical records. Now, reason number one for concern is privacy. That's obviously going to have your entire medical history going to an AI company. It's also going to not be redacted by you in a way to remove identifiable things.
Reason number two, I think, if we're talking about health record data, it's really messy. They include tabular data. They include copy-forwarded data that's been copied and pasted. And they also, if you've ever read your health records, they include things that are wrong. There's a lot of errors or misdocumented things in your health data.
And it turns out that just copying a bunch of information, like... LLMs aren't magical. You can't just copy your entire medical record in and think that you're going to get good performance. And I would never bet against the technology. I think that we will get to the point that we have ways to build representations of humans and understand their health.
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Chapter 6: What are the benefits and risks of AI in patient care?
It's more at this point, right, with where AI is now, it's more having sort of that knowledge and we'll call it wisdom to know when the system might be suggesting something wrong, which is something that right now, and this may change, we get by seeing a lot of cases and reflecting on them.
So right now, you're going to get the best performance if you have an experienced human trained in the old-fashioned way with an AI system. But I think your guy's point is at some point that might not matter. The AI systems might just outperform all of us. And then, yeah, I guess it's like just use the graphing calculator. But we're not there yet.
Would the AI models be better if we were less protective of privacy for medical data?
Yeah.
I mean, that's such a loaded question. So the first thing that I'm going to say before I answer that is patient privacy is very important. And we should respect people's privacy and their ownership of their data. But yeah, so in short, like the reason they're not better at certain things is that you need to get LLMs better. You need to label.
and then train them on the sort of labeled health data. And in the US, there are appropriately many restrictions on how health data can be used. I suspect that these companies like OpenAI, by having chat GPT for health, they will gain some more of their own data, which they say they're not going to train on.
I trust that they're not going to train on it, but they'll be able to use that data to at least evaluate their models and try to make them better.
Hmm.
I think they should train on it. I mean, obviously, that'd be a huge illegal violation of privacy. But it would also make the AI doctors better. Yeah, much better. And I think, you know, a lot of people would be sort of willing to make that trade-off.
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Chapter 7: How does patient data privacy impact AI model training?
We know there's leakage right now, so you shouldn't use it to evaluate your forecasting scaffold yet.
But, like, how is it getting that data if it's only being fed scanned OCRed books from archival sources?
Because archival sources have wrong dates in them all the time. Or it's kind of unclear what the, like, date of a text is because there's, like, an updated edition. Or sometimes there's, like, a preface that's been added later. Or sometimes even just in the middle of the text, there'll be, like, someone inserted some future notice, like, you know, note.
And, like, later on, like, historian's note, da-da-da-da-da. And so it's just really hard to check all these little edits that people make, and then they still maintain the original publication date on the metadata.
I see. I asked Taki what it knew about me, and it said, Kevin O'Hara... which is not my name, was born in Dublin in 1840, and having been educated at the School of the Christian Brothers, became a teacher in it. He afterwards adopted the profession of journalism and was for some years connected with the staff of the Nation newspaper.
It also said I had written several popular songs, including Molly Asthor and the Irish Immigrant. Now, obviously, most of that is wrong, but it did connect me to journalism. which I found interesting and maybe like some other evidence of some data contamination. But like, is this thing accessing the internet in some way?
Or like, how would it have known that I, or at least Kevin O'Hara, this character sort of connected to me in the model, was a journalist? Yeah.
That's a great question. I guess I'll say the training data was 240 billion tokens. It's this vast ocean of stuff. Maybe there was a list of journalists that got put in somewhere that had your name in it. I guess one thing about this model is it hallucinates like crazy. This was a huge problem with the chatbots that people were meant to use professionally.
I think it's been addressed to a large extent in frontier models, but we made zero effort to address that in any of our post-training so far.
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Chapter 8: What future advancements in AI and medicine can we expect?
Today's show was engineered by Daniel Ramirez. Original music by Marian Lozano, Diane Wong, Rowan Nemisto, and Dan Powell. Video production by Sawyer Roque and Chris Schott. You can watch this whole episode on YouTube at youtube.com slash heartfork. Special thanks to Paula Schumann, Pui Wing Tam, and Dahlia Haddad. You can email us at heartfork at nytimes.com with your most recent diagnosis.
We'll tell you if we think you should get it looked at.