I'm Kevin Roose, a tech columnist at the New York Times.
And I'm Casey Newton from Platformer.
And this is Hard Fork. This week, OpenAI's big reset. We'll talk about the company's new business strategy and its dramatic trial with Elon Musk. Then, Dr. Adam Rodman returns to the show to tell us about the latest advances in AI and medicine. And finally, can an AI made out of very old text still predict the future? We're talking about Talkie.
So Casey, there's been a lot happening with OpenAI in particular this week. There seems to be something of a major strategic reset happening over there. They've got a new deal with Microsoft, an expansion of their deal with Amazon, changes to their Stargate compute strategy, and a new push toward new kinds of ad-supported subscriptions. And of course they've got this big trial with Elon Musk that started this week in Oakland. So, let's get through all of it. But first, before we do that, let's make our disclosures. I work for the New York Times, which is suing OpenAI, Microsoft, and Perplexity.
And my fiancée works at Anthropic.
Okay. So, let's start this week with this new Microsoft deal. So, Microsoft and OpenAI have of course been partners for many years. Microsoft remains the biggest investor in OpenAI. Their stake is valued at about $135 billion, but their relationship has also been strained over the years by various factors. And this week, they seem to be sort of consciously uncoupling or at least rewriting their partnership agreement and allowing OpenAI to be a little bit more promiscuous in who they do deals with.
Yeah. I mean, OpenAI just had this real challenge, which was that until this week, they were really only allowed to serve their models on Microsoft's infrastructure. And one thing we talk about on the show a lot is just that a lot of the big cloud service providers, their infrastructure is just maxed out. And Microsoft is one of those. And so for OpenAI's revenue to grow, they needed to find other ways that they could deliver their services. And so, to my mind, that was maybe the most important thing about this deal.
Yeah. So under this new rewritten version of the Microsoft and OpenAI deal, Microsoft will no longer have to share revenue with OpenAI. The new deal also removes the part of the original agreement that had to do with AGI. The old agreement said that basically once OpenAI reached AGI, Microsoft would stop getting certain revenue share payments. But under the new agreement, OpenAI will keep sharing revenue with Microsoft until 2030, no matter what benchmarks they hit. So the AGI clause is gone. And I for one will be sad to see it go because I think it was sort of the funniest clause in the entire AI world, right? It was like basically like, well, if we ever get to a point where OpenAI says the magic word, then the entire world changes and now they're not allowed to say the magic word anymore, right? So, AGI has been poorly defined for many years and everyone has got their own definition, but it did have this one interesting contractual stipulation and now even that is off the table. So, now we just have sort of AGI as evaluated by vibes.
So, Casey, what did you make of this loosened partnership between OpenAI and Microsoft?
Well, I think it seems like probably a good deal for both of them, right? Like there was a moment when it seemed for both companies like being very, very closely aligned was the best thing for both. Arguably for a time it was. But with all of the various revenue, compute and customer needs that both of these companies are now trying to serve, I think it's benefiting both of them to play the field and sign other partnerships. So my read on this was like this is basically good for both of them. But what about you?
Yeah, I think it's good for both of them. I think it's a little better for OpenAI. They got most of what they wanted. I think the bigger deal for them is the ability to work with other cloud providers. So now they can work with Amazon or Google Cloud Platform and big corporate customers who use those cloud platforms can now use OpenAI models. They don't have to go to Azure to do that. I think that allows them to strike these other bigger deals and to reach other corporate customers who may have been limited before by the fact that like it's really hard and annoying to change cloud providers.
Yeah. And speaking of big deals, Kevin, they signed what seemed like a pretty big one with Amazon this week.
Yeah. So, OpenAI wasted no time in its new open marriage with Microsoft. It went back out on the market and found themselves in bed with Amazon.
They found themselves in bedrock with Amazon. But I'm sorry, go on.
Yes. So, on Tuesday, OpenAI and Amazon announced an expansion of their deal that they had announced back in February that will allow OpenAI to sell its models through AWS's Bedrock AI platform and make Codex, its coding model, available on Bedrock as well. OpenAI and Amazon will reportedly also develop customized models to power Amazon's consumer-facing applications and Amazon will invest $50 billion in OpenAI. So there's some interesting stuff here. I think the interesting subtext to me is that Amazon for a number of years now has been pretty closely tethered to Anthropic as its primary sort of frontier model developer. And so OpenAI is kind of taking advantage of its newfound freedom by trying to elbow into Amazon and maybe displace Anthropic as their favorite model provider.
Well, I know that Amazon was talking a really big game about this deal. The CEO of AWS was giving interviews essentially saying like, OpenAI belongs to us now. It was kind of the boy's mind situation. Remember the old Brandy and Monica hit from back in the day? This is kind of bringing that back in a little bit more of an AI flavor. I also have to say I find it very interesting that Amazon named its platform Bedrock because that's where the Flintstones are from. It seems rather backward-looking for a leading AI company, Kevin, wouldn't you say?
That's great analysis. Thank you.
Thank you. Thank you.
By the way, I think that this is a really important point and a reason that we are talking about it to a big general audience, which is that the story that you just described, Kevin, is one of a world where no one has the resources they need to serve the demand for AI that they have. And I think, you know, at a moment where we're still sort of seeing a lot of skepticism, there's so much bubble talk. I just want to posit that as a really important point in understanding what sort of bubble this is because even the biggest companies do not have the resources that they need to serve that demand.
Yeah. And I think that's a good point and it's really a profound shift in the way that skeptics have been talking about this AI boom. I remember just even a couple of months ago the leading sort of strain of criticism was that these AI companies would never be able to generate the demand to pay for all of the expensive data centers and infrastructure projects they wanted to do. And now that's shifted to well there's so much demand, what if they can't build enough to support the demand they have.
Yes. And on that front, it does seem with at least one of these mega building projects, there have been some problems recently, Kevin.
Yes, this was another story that hit this week. The Financial Times reported that Stargate, OpenAI's joint $500 billion infrastructure project, is also undergoing a bit of a shift. The FT reported that in recent weeks, OpenAI has halted planned data centers in the UK and Norway, declined to expand its flagship site in Abilene, Texas, and seen several senior figures tied to Stargate leave for rival Meta. The FT further notes that OpenAI has shifted to leasing capacity from third parties instead of building out all of their own facilities. Casey, what did you make of this?
I think this was a case where like reality has just finally intruded on the Stargate project. Like when all of these deals were getting announced initially, this is how they sounded. Well, we're going to spend $1 trillion that we don't have to build 40 quadrillion data centers. And at the time, people said, 'That kind of seems like a lot. Can you guys actually live up to that?' And they said, 'Uh, yeah, just watch us.' Well, guess what? They couldn't. And now they're changing course.
Yeah. I don't think this signals that they are sort of retreating from their compute ambitions. I think it's more about like they are realizing that if they want to go public, which they do, they need to sort of get their house in order. And one way to get your house in order is to move some of this data center and infrastructure building off of your balance sheet and onto third parties.
Yes. But there is one point in there, Kevin, that I do want to ask you about, which is that Burt Berbergen at the Wall Street Journal over the past week had this really interesting story where he said that OpenAI had failed to meet some of their internal user number targets and some of their revenue targets and that this was possibly creating some tension between Sam Altman and his CFO Sarah Frier as they consider potentially doing an initial public offering later this year. So curious what you made of that story and does this maybe help explain why OpenAI has had to pull back on some of its big Stargate ambitions.
Yeah, I mean I think there are competing forces within all of the big AI companies right now. One side is sort of the indefinite optimists, the people who think that demand for AI is just going to be essentially infinite and that as much compute and as much money as they need to spend acquiring compute, it will all be paid back many times over because the world is about to change into something most of us barely recognize. And so kind of just trust us on that is sort of one camp. And then there are the sort of, you know, the number crunchers who are trying to fit all of this into a kind of financial projection that will make sense to investors who are not as convinced that the world is about to change forever and who want to see things like what is your plan for actually making the revenue that you're going to need to pay for all this stuff. So I think this is happening in a way at OpenAI that is now because of Berbergen's story is out there. But I think this kind of tension exists at all of the big AI companies. And so I think right now what we're seeing is kind of that power struggle breaking out into the open.
Yes. And for what it's worth, OpenAI did call this story prime clickbait, which I think just refers to clickbait that's really, really good. Is that what that means?
Yes. Sort of like Wagyu clickbait.
Yes. Exactly. This clickbait was dry-aged for a month before it was served and it's delicious.
Yeah. And I think one thing I want to flag on this is that these growth projections that OpenAI reportedly did not hit, those were in 2025. I think it is fair to wonder if something has changed in just the last few months because of the enormous rapid growth of tools like Codex and Claude Code. We have seen just reports of astronomical growth in those tools. So it may be that OpenAI was having some growth issues late last year but that because of this agentic coding boom things have started to turn around. We just don't know yet.
Yeah, that makes sense to me and 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 36 times this year to 112 million people while meanwhile its $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 lot cheaper, but we'll show you ads. I was curious like what you make of that strategy because, you know, part of me feels like, well, they'd much rather have, you know, the $20 subs and the $8 subs, but maybe there are 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, right? There's the sort of casual hobby users who are using AI chatbots like ChatGPT, like Claude, for sort of souped-up Google queries to, you know, help them write emails and maybe only using it a couple times a day. And if you're doing that, you probably don't want to pay 20 bucks a month. You're probably more comfortable paying eight bucks 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 bucks a month and who are willing to pay many multiples of that to get access to the latest models, to have higher rate limits. And so I think all of the companies now are sort of 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 ChatGPT if they would just let the Codex app talk about goblins.
I say free the goblins. These models are so weird. Like it is so weird that we have this technology that is now sort of 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.
Which to me is just like a satire of the AI safety conversation, you know? Like lately OpenAI has sort of been very skeptical of AI safety and casting a lot of aspersions on doomers, but it's like, well, we did have to add safety guardrails to prevent goblins from taking over our coding app and that's a real story. So as usual I'm just loving life here in 2026. What a world.
So, those are a bunch of stories about OpenAI's strategic pivot, its reset. But there is this other big variable here, this potential fly in the ointment, and that is the long-awaited Elon Musk trial that got underway in a federal courtroom in Oakland this week. Casey, can you remind us what this case is about?
Yeah, so Elon Musk was famously one of the co-founders of OpenAI. He gave the company some of its initial funding but left in a power struggle between himself, Sam Altman, Greg Brockman, and some others. And a few years after all of that went down, and notably after Elon started his own AI company, he sued OpenAI and said, 'I have been defrauded. This was only ever supposed to be a nonprofit, and you've gone and turned it into one of the world's most valuable companies through its for-profit arm.' Notably, Kevin, he made 26 claims when he originally filed this lawsuit in 2024, but only two have survived to trial: unjust enrichment and breach of charitable trust. The trial is just getting underway. They've done jury selection and they've had a couple witnesses testify. Elon Musk himself took the witness stand and said, quote, 'This lawsuit is very simple. It is not okay to steal a charity.' He also said that if OpenAI is allowed to get away with this, quote, 'it will give license to looting every charity in America.' Basically he is saying this thing that started as a nonprofit that was supposed to continue as a nonprofit became through some corporate restructurings a for-profit company that has raised many billions of dollars and that if this is legal to do every charity would do this. Why wouldn't you want to take your donors' money and turn yourself into a well-funded startup?
Yes. Now, one inconvenient truth that Elon Musk faces here, which is that OpenAI's for-profit business is still controlled by a nonprofit. There's this foundation that houses the public benefit corporation. And while I do empathize with those who say, 'Hey, it really seems like the nonprofit hasn't done all that much and, you know, most of their money is being used for for-profit activities,' this was litigated and the nonprofit, you know, still does have like voting control over the for-profit.
Yeah. So Elon Musk is saying this is a case of looting a charity. OpenAI's lawyers have accused Elon basically of just being bitter that the company has succeeded without him. Its lead counsel, William Savit, said during the trial, quote, 'We are here because Musk didn't get his way at OpenAI. My clients had the nerve to go on and succeed without him. Mr. Musk did not like that.' They have also been pointing out that Elon had also wanted to make OpenAI have a for-profit subsidiary back when he was with the company and that he's just mad that he didn't get to control it.
Yeah. To underline that, like in 2017, 2018 there are emails from Elon Musk where he talks about turning this into a for-profit. So, you know, whatever concerns he had about looting the charity, you know, today, like he did not have them back at the time, right? He also wanted to fold OpenAI into Tesla, that was revealed in some of these emails. Tesla, of course, being a for-profit company. So, seems like this is not exactly a consistent and principled stand. But Casey, what are the stakes here? Like if Elon Musk does manage to convince a jury that this was a case of OpenAI looting a nonprofit for its own commercial gain, like what could the remedies be? Could this be fatal for OpenAI or is this just sort of an attempt to slow them down and distract them with a big trial?
I think that it is much more the latter. Like based on my reading of the case and what I've seen sort of legal experts say about it, the whole case is very unusual that it even made it to trial. Like for the most part, if you donate money to a nonprofit, you actually don't have a say in what happens to it after that. So it's very unusual that the judge even granted him standing to sue here. And as I noted, she threw out most of his claims. That said, let's say that, you know, there's some single-digit percentage chance of him winning something here. What he wants to do is to take more than $150 billion that is currently under the control of the for-profit business and give that back to the nonprofit, which would create a lot of headaches and roadblocks for OpenAI as it tries to build out Stargate and do everything else it wants to do.
Yeah, I think the lawsuit and this ongoing litigation between Elon Musk and OpenAI has been very distracting for OpenAI. But like as a journalist and as a person who wants to know more about the inner workings of how these companies run, I think it's been actually very valuable for a lot of these emails and early communications between OpenAI leaders to be released as part of this litigation. I have found it very useful in understanding some of the early dynamics at OpenAI and it also just illustrates the degree to which these projects are all just sort of fueled by grudges, right? Like there's sort of one level of interpretation which is like all of these people are just like obsessed with building the machine god and that this is all sort of related to their visions of the future. And then there's like another more base level which is just like these people are all just rivals and they have these petty long-standing grudges and they just don't like each other very much. And so you can interpret a lot of what happens in AI through the lens of personal animus.
Yes, I've said this before and it is rude, but a shocking percentage of the AI industry is just people who decided they didn't want to work with Sam Altman and who now have their own companies.
Right. So Casey, some people have been looking at all of this drama and intrigue surrounding OpenAI from the trial to the Microsoft deal to these missed growth projections and saying some version of like OpenAI is in trouble. They are not going to make it to an IPO. They are going to sputter out and maybe end up in some real hot water. And maybe Elon Musk wins this trial and it's sort of the end of OpenAI as we know it. What do you make of those gloomy predictions?
Yeah, I mean look there are some fundamentals for OpenAI that remain worrisome, right? They're planning to burn tens and tens of billions of dollars in cash before they achieve profitability. They still have this very ambitious infrastructure buildout that is quite expensive. And so like I'm not going to sit here and say that like all of the numbers seem to pencil out for this company. On the whole, like if I try to, you know, put myself into the shoes of their CFO and I look through all of the stories that we just talked about, I think these seem like smart things to me. You know, it kind of seems like they're starting to dot their i's and cross their t's and get this company in a shape where retail investors will be excited to invest in the stock, which by the way, I think they will be. So yeah, it's one of these companies where like it is a generationally weird enterprise, but when I look at this particular set of stories, I think they're basically doing the right thing. What do you think?
Yeah, I mean, I think there's this interesting fallacy in the AI industry where it's like there will be only one winner, right? Everything is zero-sum. If OpenAI is having a bad month, it's because, you know, Anthropic is having a good month or Google DeepMind is having a good month and vice versa. Like their sort of growth comes at the expense of all the others. And I think that feeling is shared by among others the executives of these companies. But I just don't think it's true. Like I think that there are going to be a handful of companies that are just going to kind of rise and fall together, right? That if your models are in the sort of top tier, you are going to be fine as long as they stay in the top tier and the sort of rising tide of AI adoption will sort of lift all boats. That's more my feeling.
Well, will this rising tide lift all AI podcasts as well, do you think?
Okay. Me too.
Kevin, is there a doctor in the house?
Uh, there sure is, Casey. Today we are going to have a conversation with a doctor about AI and medicine because this is an area where there has just been a lot happening recently and we needed someone qualified to come in and debrief us.
Yeah. You know, as we've sort of looked across the landscape just over the past few months, we've seen company after company introduce their own product at the intersection of AI and medicine. There's ChatGPT Health, ChatGPT for clinicians, Amazon has something called Health AI. Microsoft has Copilot Health and of course all the while doctors are experimenting with this technology and as best as we can tell actually getting really excited about what they're seeing.
Yeah. And 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. And so I am coming armed with what I believe to be good information about what is going on. And that allows me to sort of have a different more elevated conversation with the doctor. And this is not just me. Like 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?
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?
Let's see how this interview goes.
You're at least a doctor of the show. You are a 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. Now, almost two years later, we have a lot of new tools and a lot of new studies about the use of AI in medicine. So just catch us up on like what has been going on with AI in medicine for the last call it year and a half.
Yeah, it's been crazy. AI and medicine has gone from, well depending on how you measure it, it's probably the fastest adopted medical technology of all time. We went from this being super novel, almost no one used AI tools to this being a routine part of most doctors' weekly practice.
And give us a sense of like the AI stack for a doctor. What are the tools that they are using right now and how, in particular, like what are the mainstream doctors, like the people that you know aren't yet on the bleeding edge?
Yeah. So the biggest sort of normal doctor technology which most of your listeners or a good portion of your listeners have encountered are what are called AI scribes. That's a sort of voice-to-text algorithm that listens to you talk to your patients and then writes a first draft of your note. And these have gone from like kind of a novel experimental technology to commodity in probably less than two years. They're everywhere. Doctors really like them and then patients really like them because they spend more time like talking. And then the second sort of I'd say normal doctor use case is for decision support. So there's this one company called Open Evidence that has created a free tool that has gone from again zero to crazy numbers of adoption. I will tell you younger doctors like my residents use it all the time and that is just, it's funny because it's a BYO AI, right? We always have usually the hospital or the health system buys tools. This is a bring-your-own-AI-to-work day and I don't know the actual numbers but it's probably close to half of US doctors are using this right now.
Wow. So yeah, the statistics that I've seen are that more than 40% of doctors now are using this which is pretty crazy uptake for something that was just started a couple of years ago back in 2022. In March, Open Evidence reported that in a single 24-hour period, doctors consulted the AI system a million times. I've been fascinated by Open Evidence. I've never used it myself, but I have friends who are doctors or nurses, and they have said what you've said that basically just everyone, especially on the younger end of medicine, is just using this thing constantly. So, like give us a sense of like how this Open Evidence tool works, like 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 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. You have my hair is grayish. 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. 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.
Now, are they actually uploading patient data to this? Like, or are they just sort of describing patients in sort of generic and anonymized ways to get back some decision support?
My understanding is largely number two. I'm sure the company has a good sense on how many people. I hope no one is copying protected health information and putting into it. Certainly what I've observed from like my colleagues and my students most people use it the way you would use like a search tool when you have a question which is, hey, I'm giving this person ceftriaxone, what's the right dose for an intra-abdominal infection? So sort of generic questions that are being interpreted through the physician.
And are there any AI tools that are integrated with patient health records? This has been an area where I think there's just been a lot of pushback of like I don't want my personal health data, protected health data going into one of these cloud-based AI systems. But are there hospital systems or medical systems that are bringing this stuff directly into contact with patient data?
Oh, 100% yes. Right now most of the sort of in contact with patient data are less about physician-facing decisions and more about like billing. There are companies that are like integrating with the electronic health record and those are not standard yet. And then the EHR companies themselves. So like Epic is obviously the biggest EHR vendor in the US. They're doing a lot of work on building in native things. So for example, at my health system, if I want to send a message to the patient, the helpful AI at the top already has like maybe you should say this. It's usually not that helpful and I don't think I've used it once in my life, but there are a lot of those things that are being experimented on actually built into the patient's health data.
I'm curious how doctors are feeling about all of this. We saw a survey from the American Medical Association that found that more than 80% of physicians now report using AI professionally. Is that physicians racing out and grabbing these tools and bringing them to the office because they're so helpful or is this the classic case of a CEO saying, 'Hey, you got to use AI or you're out of here'?
So doctors are BYO AI. A lot of that AI use is AI scribes and decision support software. And I'll tell you, some people are just using straight up like ChatGPT or Gemini or Claude for their decision support software. So I think one of the reasons doctors thus far have been more positive about it than perhaps the overall population is they're largely tools that doctors are bringing themselves that they think make their lives better and at least not yet many things that are being imposed upon us.
Yeah, I've noticed that when I and my friends go to the doctor now, we often are presenting our information to a chatbot first and then coming into the doctor with sort of a readout of what the chatbot has told us. This is of course not a new phenomenon. People have been doing this like with WebMD results for many years. But is this something that you're seeing now is that many more patients are coming to you having already discussed whatever's going on for them with a chatbot?
Yes, this is the other big change is that there's, you know, there's someone else in the exam room with me and often it's ChatGPT. They're talking sometimes with my hospitalized inpatients, they're talking to ChatGPT while I'm in the room with them. And I think this is interesting because this is a kind of a new competency for doctors. We have to talk to our patients about AI. And I have started to talk to my patients about what I think are like safe uses, what are like safe uses while telling me, and then things that they definitely shouldn't do. My patients may talk to me more about it because I am like a doctor and an AI researcher, but like a lot of my patients are using AI routinely.
Well, give us a flavor of what you're telling them because, you know, I am definitely somebody who has looked up bicep groups before. I've gone to the doctor and I would say I found it enormously helpful. But I can also imagine, you know, more skeptical doctors being annoyed at a patient telling them, you know, what ChatGPT says to do. So...
Yeah. So, here's my, I'll give you my spiel. This is, I give them a, what is it? A green light, yellow light, red light. I don't know why I'm doing circles. Everyone knows what street lights look like. So, the green light uses are general health questions. So, you, I have recently diagnosed with diabetes. I really love seafood. Can you help come up with a diabetic diet for me? The green light uses are also preparing for clinic visits. So, I'm about to go see Dr. Rodman. I want to make sure that I ask the right questions. Here is the last note or the last thing he wrote. Obviously, strip out anything identifying. I don't put your personal health information. And like help come up with good questions to ask him. And then other green-light activities might be like wearable data. I don't know how good they are at wearable data, but I will tell you if a patient is going to give me like five years of their Apple Watch data, they're probably going to get it better from ChatGPT than from me pretending to look at five years of Apple Watch data because it's a 20-minute visit. The yellow light, Casey, I think is a lot of the things that you're saying. So I tell my patients it's okay to explore new symptoms. It's even okay to seek out second opinions when talking to a chatbot that can really help prepare you as long as you understand that it's not a replacement for a doctor and that is the first step to talking to a human.
So LLMs are, they're really powerful, and I mean there is some evidence, of course, that like when any human uses them, you don't always get laboratory-level performance, and there can be like, they can give you dangerous advice. But diagnosis and like exploring symptoms, as long as you use it in a way to prep to see your doctor, can be very helpful.
The red light, what I tell them never to do is like ask medical management decisions. Like don't say, 'My doctor said to do this, is this right?' Like I have cancer, God forbid you have cancer, is this the right chemotherapy option? Like a lot of those decisions are so nuanced and so much information, those are things that the models don't do well, and they're so sycophantic they can convince you that they're saying the right thing even when they're wrong.
