So, Rachael, a little while ago, you got into a little spat online. Tell me what that was about.
So a few weeks ago, a startup in San Francisco announced that it was going to launch a new product, which is a whole body imaging technique. And it led to this really interesting kind of nasty discourse between medical doctors like me and folks in tech. And that conversation came down to doctors being very wary that this kind of data can sometimes cause more harm than good. And folks on the tech side saying, basically, how can more data ever be bad? Isn't more data always helpful in informing decisions, research, et cetera, et cetera.
And it led to this conversation between you and I about: Is more data about your body always good? That's the question that we're going to be talking about today in a bunch of different ways. It's not entirely new. People have been trying to track data about their body and their health forever in more systematic ways, maybe over the last 10 years. But the prospect of A.I. really kind of changes the landscape here and makes us think again about what the future holds. Is it science fiction to imagine that there will be a day when an A.I. could predict 20 years in advance when a person is staring down the barrel of a neurodegenerative disease and act at a time when maybe we could actually reverse it? We're now looking at a future where many people are telling us that machine learning can process huge amounts of data much more quickly, much more intelligently than anyone has before, and essentially learn things about how we are living, what health is, what illness is, and how we might be able to do better to manage our health going forward. I'm David Wallace-Wells, I'm a writer for New York Times Opinion and a columnist for The Times Magazine.
I'm Rachael Bedard, I'm an internal medicine doctor in Brooklyn and a contributing writer at New York Times Opinion.
So before we talk about the very now and the kind of distant future, let's talk a little bit just about the recent past. Over a couple of decades, doctors have become a little bit more skeptical than I think the average layperson about the possibility that knowing more is always good. Tell me about where that came from, what that suspicion arises around, and what normies like me don't understand.
So I think there are a few factors here. One is over the last several decades, our ability to collect data about the body has taken off radically. So imaging techniques, blood tests, tracking devices, all of these things can provide so, so much information that may or may not correlate in any meaningful way to what people feel in their bodies, how they're functioning, their clinical outcomes. When you're talking about studying people who feel healthy to see if actually they might be sick, you're talking about screening a healthy population for hidden pathologies. And there have been lots and lots of studies over time to try to do this. And what we have found is the results are really mixed. So the most famous cautionary tale is South Korea, in the early part of this century, instituted a policy where they were screening universally for thyroid cancer with thyroid ultrasounds, thyroid ultrasounds, not invasive. They don't cause any harm to do fine. What they found, though, when they followed that experiment over time, was that the incidence of finding thyroid cancer went up 15 times. And it made no difference to mortality from thyroid cancers. Which means you were basically finding 15 times more cancers that weren't actually clinically significant, that weren't going to hurt people.
Well, let me just pause you there. How can that be? I mean, I understand there are some things that are below a clinical threshold, which maybe we don't want to worry about, but how can it be that when we are seeing so many more cases of something, it doesn't have any population level benefit?
It could be in two ways. One thing is that there are just absolute like indolent cancers that can exist in small, very, very, very slow growing ways that are just not going to ever become clinically significant in a person's lifetime. Prostate cancer. There's this old adage that more men die with undiagnosed prostate cancer than get diagnosed with it in their life.
Yeah, I've heard people say we shouldn't even talk about it as a cancer. We should treat it as something else because the word cancer scares people into treatment.
So that's one thing. The other thing is whether or not screening when somebody is asymptomatic is actually useful. So it may be that if you wait until people's thyroid cancer becomes clinically significant until it's found because they have symptoms or on an exam of their neck. If you wait until then and intervene at that point, it's fine. The vast majority of thyroid cancers are caught pretty early, and when they're caught, they're very treatable and people do really well. And so there may be no additional benefit to catching them way earlier. It doesn't. That example, that cautionary tale does not mean that we've closed the case on how we should look for thyroid cancer forever. But it means given the screening technique that we know how to use now, applying it at the population level to asymptomatic people seems to have no clinical benefit and instead causes a fair amount of harm, because that fifteenfold increase in cases means follow up surgery, biopsies, surgeries, and all of those things.
One big question that I have about this, not just about thyroid cancer, but the question of what we can learn about the body in general is if we look at the state of play now and we say, given the treatment techniques we have, given the screening techniques we have now, expanding our screening to the whole population isn't going to have a benefit. Is that because we already know everything there is to know that is useful about such a disease or other diseases, or is it something about the limits of our screening in a future where we could zoom down, have much more information about particular cancers? Presumably more data would be good, right?
It really matters if you know what you're going to do with the data. So let me give you an example. That's a more live question, which is screening for Alzheimer's disease. Alzheimer's disease is incredibly prevalent, clinically devastating, on the rise. And until relatively recently, we had very few interventions to offer people if you knew that they were at increased risk for Alzheimer's. We didn't have anything that made the disease slow down or reverse its course. In the last 10 years, we have both found new screening techniques, blood tests that can find evidence of early plaques in the brain, basically, that are developing well before you have any clinical symptoms. And the other thing that's happened in the last 10 years is for the first time, there have been new, approved treatments for people who are in very early stages of Alzheimer's. That's a total game changer because in that case, if you'd had that blood test 20 years ago and you didn't really have anything to offer people, the rationale for screening would be really low. Because you would say you're just going to tell people this. They don't know for sure that it means they're going to get Alzheimer's, but it maybe freaks them out for the rest of their lives. Alzheimer's is in my family. I would never have gotten this screening test 20 years ago. It's really different if you have an intervention to offer people that may be meaningfully disease modifying. And so the question of whether screening is useful and the data is useful also goes in tandem with what are you going to do with the result when you get it.
So what's the big problem with this particular full body scan that we're talking about today? Why is this an example of something that is going to give us information that is not useful, maybe counterproductive as opposed to helpful to the people who are getting it?
So embedded in that question is the whole thing. So let's unpack it. So the first thing is like when you talk about it being helpful to the people who get it, it really depends what the person's getting it for. If you're like, I don't know, Joe Rogan and you're a fitness obsessed gym bro who is working out several hours a day and really obsessively tracking your diet and all of these metrics about yourself. And you want to collect these images because you want to be able to see the relative proportions of muscle to body fat in your body. Whole body ultrasound is probably OK for that. And if that's something that Joe Rogan finds like meaningful on a personal level to himself, he's like, this makes me feel better about the way that I'm taking care of myself. Go with God, Joe Rogan.
And that's what the company is saying right now. The company is saying this is not for medical use. This is a general wellness thing that people can use in order to track their body composition.
That's, though, a really different prospect than the way in which this conversation about it online was extrapolating the potential benefits of such a technique, which were you're going to be able to get a monthly scan that will track the appearance of abnormalities in the body that may or may not be clinically significant. And make sense of them. And that becomes a problem for a few reasons. The first is that we know when we scan people that we're finding stuff in their bodies all the time that we don't know what it means. We call them incidentalomas because they're incidental findings that are totally indeterminate significance. We're always finding schmutz on people's adrenal glands. And there are guidelines about how big does the schmutz have to be for you to decide that you're going to scan again. And which interval. Etc. Etc. But that stuff's meaningfully costly and potentially harmful because you have to pay for scans. And with time and money, you get biopsies. All of these things that are potentially harmful without any benefit. So that's one reason that it makes doctors really nervous. The other reason I think that it makes me really nervous is because this is part of this larger trend of direct to consumer access to medical testing, or what is medical testing adjacent, right. There are also companies where you can be ordering your own lab panels and then getting back all of this blood work. And whether or not that's meaningful data about your health is hard to say. And once you get it back, when there are abnormal values, your next step is you're taking it to your doctor and saying, this seems to say these values are off. Like, what am I going to do about it. Well, some people are taking it to a doctor, but also a lot of people are just monitoring it themselves. Well, monitoring or taking action on it themselves.
What? Like what's that? What are they doing?
And there's a conceptual shift that's happened. Previously they had assumed that they were in relatively good health. They start to see some indicators that may or may not mean anything, but they've already stopped thinking of themselves as being in good health and started thinking of themselves, if not unhealthy, then on some spectrum of wellness and performance. Emotionally, they maybe should be doing better. They should be addressing this or that, and whether or not those improvements will actually help their being in the long run, they're already mindful of what they could or should be doing.
So they've already redefined their measure of wellness from how am I feeling to what does my watch say about how I'm feeling.
Totally, totally. So in preparation for our conversation today, I have been wearing, for the first time in my life, a fitness tracker, a watch-type device, for the past week.
You're really a late adopter.
I'm a really late adopter, and I'm also, although I'm a Luddite, I don't have anything.
You don't have anything. You're just vibes in David Wallace-Wells's body.
Not me. I've been tracking my data for a week and I cannot make any sense of it. Last night it told me I had a bad sleep, but I felt I had a great sleep and I really did like look at the data this morning. And I was like, well, what does it know that I don't know about what was happening.
You did have that feeling. You didn't have the feeling of like, I know better than this watch.
Well, I was like, I feel pretty good. Two nights ago, I slept terribly. And the watch thought it went fine. And then this morning, the device thinks that I slept badly. And I woke up feeling much better. And mostly, I'm going to defer to my own experience. But I did like look at the graph to be like, what does it know that I don't know.
I mean, there's data that's come out that says there's a placebo effect and a nocebo effect to all of it. Which is like if the device suggests to you that you had a bad sleep, people experience more tiredness that day, whether or not it's true.
Yeah, I mean, it reminds me a little bit of some of the conversation around mental health and diagnostic inflation, the idea that once we have supplied the public with knowledge about what constitutes depression or anxiety, once we've lowered the taboos against those diagnoses. Probably that's all to the good. But there are also some people who would have thought of themselves as healthy previously, who now understand themselves as struggling or mentally ill, and the effect that has on their lives is ambiguous.
Yeah, I mean, and that gets to I think both like the benefit and the peril of the wearable phenomenon. A study in the Journal of the American Medical Association found like 40 percent of Americans reported wearing a wearable so much in 2024, and the promise and the peril of it is mindfulness is actually pretty important. So the peril is what you just described or what I just described about my sleep. It gives you data that says, actually you don't feel that good. Actually, your resting heart rate is kind of high and you're sitting there thinking, but I don't feel anxious, I feel fine and it gets you worrying. And that can obviously get into a pretty vicious circle pretty quickly. On the other hand, the benefit of wearing something like this is it can offer you data that then does the opposite. That puts you into a virtuous cycle. So like step counters, there's data for step counters that says that it does encourage people to walk more when they're tracking because it gamifies getting exercise.
I mean, the thing that I have found most useful about this past week's experiment has been tracking my steps and thinking, well, I really do want to hit a certain number every day. And I'm going to go, I'm going to go get it, get one more walk in order to get there. And that obviously is to the benefit. So there's a lot of stuff going on here. There's a kind of a sociological story about the sorts of people who are drawn to this. And why are people drawn to these measures of self-optimization and why are they starting to see their body in terms of data, which can be extracted. Also, to what extent is that really a phenomenon of achievement culture among the well-off or something that might be extended profitably through the rest of the population. There's that whole bucket, the kind of cartoon Bryan Johnson — like, I'm going to — Do you want to say who Bryan Johnson is?
