Making Sense - Sam Harris - #162 — Medical Intelligence

00:00:00.000 Welcome to the Making Sense Podcast.

00:00:08.820 This is Sam Harris.

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00:00:46.780 Welcome to the Making Sense Podcast.

00:00:48.980 This is Sam Harris.

00:00:51.320 Okay, I'm in lovely London, getting ready to record some podcasts.

00:00:55.860 It really is lovely.

00:00:57.060 The weather is perfect.

00:01:00.040 That makes London especially nice.

00:01:03.360 So I'm going to record a housekeeping here, and then get out of my hotel room.

00:01:09.760 A few things to say that have no relationship to today's podcast.

00:01:14.920 I am recording this right after the Andy Ngo assault in Portland, a few days after.

00:01:23.600 This strikes me as entirely the product of Twitter, or of social media in general.

00:01:32.220 This is like a physical manifestation of all that is crazy online.

00:01:38.720 I think these protests probably wouldn't occur.

00:01:43.740 Andy Ngo, the journalist who was attacked, probably wouldn't have been there.

00:01:49.840 All of the acrimony and insanity that won witnesses in the aftermath would have no forum.

00:01:56.480 It's a very strange phenomenon.

00:01:57.920 I'll catch you up for those of you who don't know what I'm talking about.

00:02:00.300 Andy Ngo is a journalist and editor at Quillette, which is an online magazine that's often unfairly described as being conservative.

00:02:09.940 It's conservative in the way that the IDW, the Intellectual Dark Web, is conservative.

00:02:16.520 It's really just a centrist magazine that has spent a lot of time criticizing the insanity on the left.

00:02:27.140 So it is branded by the left, certainly the far left, as conservative, if not enabling of fascism and racism and xenophobia and Islamophobia.

00:02:39.960 All of those things have been alleged.

00:02:43.380 Now, I don't know Andy.

00:02:44.520 I think I met him once very briefly.

00:02:47.640 He covered the release of the documentary Islam and the Future of Tolerance, which depicted my collaboration with Majid Nawaz.

00:02:55.060 I don't know his personal politics, and his politics are absolutely irrelevant to what happened in Portland.

00:03:03.640 I didn't contribute much to the resulting cacophony on Twitter.

00:03:08.600 I posted one thing, but I'll just say a few things here.

00:03:12.580 So what has been happening in Portland, apparently, is that Antifa, the so-called anti-fascist cult,

00:03:21.880 has been demonstrating periodically and allowed to do so with real impunity by the mayor, Ted Wheeler.

00:03:33.500 And my one tweet on this topic tagged him.

00:03:38.660 It seems to me he's been totally irresponsible in the scope he has given to these protests.

00:03:45.080 I mean, I've seen video with Antifa stopping traffic and pulling people out of cars.

00:03:52.660 It's madness.

00:03:53.760 It's a complete breakdown of social order.

00:03:56.580 And in the video where you see Andy Ngo attacked, that's what you witness.

00:04:02.520 A complete breakdown in social order.

00:04:05.820 And apparently the police in Portland have been told not to intervene by the mayor.

00:04:10.900 Anyway, this is the kind of story that will be picked up by the right wing.

00:04:18.320 You know, Andy Ngo will be on Fox News talking about his attack.

00:04:22.220 One can only hope that mainstream sources like the Washington Post and the New York Times

00:04:28.900 will talk about Antifa honestly here.

00:04:33.040 I mean, Antifa is often described as a group of people who are protesting the extreme right.

00:04:40.060 Well, they may be doing that, but they're also attacking innocent bystanders and journalists.

00:04:49.520 So what we have here is a group that imagines it opposes fascism, but they behave just like fascists.

00:04:57.880 And perhaps this is no surprise. 0.89

00:05:00.620 If you travel far enough to the right or to the left on the political spectrum, you find yourself surrounded by sociopaths. 0.98

00:05:09.560 And Antifa, while there may be some blameless members of this movement, seems to be chock full of sociopaths.

00:05:18.120 At least judging from their handiwork that you can see attested to in these videos.

00:05:23.280 But anyway, the response to this phenomenon, which again is a total breakdown of civil society, right?

00:05:31.200 You've got people who are attacking nonviolent bystanders in a context which, again, appears to be a pure confection of social media.

00:05:43.840 Because most of the people in these protests, most of the members of Antifa, you see, are also filming.

00:05:51.880 I mean, everyone has their phones out or their cameras out, filming themselves to broadcast this online.

00:05:59.300 It is a bizarre moment.

00:06:01.220 Anyway, the video that shows Andy getting attacked starts after the attack has occurred.

00:06:07.860 I mean, there's a few other videos, so you can sort of triangulate on this.

00:06:11.620 But the video that's widely being shown is one which starts after he's already been hit at least once.

00:06:19.580 And then you see someone run up and hit him twice in the face as hard as he can.

00:06:25.680 And then I think the same attacker then returns a moment later to kick him in the groin twice as hard as he can.

00:06:35.000 There's a few things to point out about this.

00:06:36.380 When you punch someone in the face as hard as you can, especially when they're not prepared for it, 0.94

00:06:45.420 I mean, you just blindside them, there is absolutely no guarantee that you're not going to kill them, right?

00:06:53.680 I mean, people get hit in the face, knocked out, they fall down, they hit their head on the pavement, and they die, right?

00:07:03.280 This happens.

00:07:04.200 It's not a high probability way to murder somebody, but it's not an especially low probability way of doing it either, right?

00:07:12.920 Especially if you know how to throw a punch.

00:07:15.300 I mean, if you knock someone out cold and there's only concrete to catch their fall, 0.82

00:07:21.960 you can certainly kill someone this way.

00:07:24.840 So you should be morally prepared to deal with that aftermath, right?

00:07:30.300 To know that that's what you're doing, and to know that you may very well spend a long time in prison as a result of what you've done.

00:07:40.920 And I might add, in prison, you might meet some real neo-Nazis and aspiring fascists to keep you company.

00:07:49.240 And that's actually what one hopes for these people in the video.

00:07:54.000 If you think this is effective political work so as to get people to worry more about authoritarianism

00:08:04.120 and about the heavy-handedness of the state and about the rise of the far right,

00:08:10.060 it has absolutely the opposite effect.

00:08:13.800 You know, you see a few videos of Antifa.

00:08:16.980 You want the far right to show up,

00:08:19.700 and you certainly want the state to clamp down on this kind of behavior.

00:08:25.000 This has absolutely the opposite political effect.

00:08:28.980 It will guarantee four more years of Trump at a minimum for this kind of thing to become more commonplace.

00:08:37.540 And what's especially damaging is for the left to get this so wrong ethically online.

00:08:45.440 Here you have leftist journalists from Slate and Vice and other organizations supporting this attack on Andy.

00:08:57.920 At the very least, blaming him for having brought it on himself, right?

00:09:01.800 For being there.

00:09:02.980 Why were you there in the first place?

00:09:05.200 You knew that all your prior coverage of Antifa caused them to hate you, right?

00:09:10.400 This is just so wrong-headed.

00:09:12.940 If the left can't get this right, if liberals can't get this right,

00:09:17.320 we have some very dark days ahead.

00:09:20.100 Anyway, back to the attack.

00:09:21.800 So, he gets punched in the face twice.

00:09:25.020 He gets kicked twice.

00:09:26.980 Then he gets milkshakes and eggs thrown at him and dumped over him.

00:09:33.900 These are not people who have hit him in the face themselves.

00:09:37.720 These are people who, upon witnessing a totally non-violent person,

00:09:42.460 get punched in the face hard twice and kicked in the groin.

00:09:48.400 Their contribution to this moment is to then hurl a milkshake or an egg at him 0.64

00:09:54.260 or some other object.

00:09:56.040 He gets hit with other things as well.

00:09:58.400 It's not clear from the video.

00:10:00.560 I'll also point out that the person who punched him in the face was wearing black gloves.

00:10:04.120 A lot of these guys wear these tactical gloves that have reinforced knuckles.

00:10:08.820 You know, some people ride motorcycles with these gloves,

00:10:13.340 but these are also gloves that members of the military wear.

00:10:17.100 It's not like getting punched in the face with a naked fist.

00:10:21.880 Imagine kind of hard plastic knuckles being built into vinyl gloves.

00:10:28.400 So, that only makes things worse.

00:10:32.080 So, watch the video and rewind it and just follow each beat in it.

00:10:38.880 You'll see a few people trying to protect Andy.

00:10:42.560 But, this whole thing is so ugly and it could get so much worse so quickly.

00:10:49.420 There's been some discussion about whether or not the milkshakes that were being thrown at Andy

00:10:55.680 actually had quick-drying cement in them.

00:10:59.000 Cement, apparently, is quite caustic and therefore can burn you.

00:11:03.740 This stuff is being thrown in his eyes.

00:11:06.320 So, I don't know if that was the case,

00:11:08.360 but the whole thing was ghastly and made especially so

00:11:14.300 because in the aftermath, you saw people who have reputations they should worry about

00:11:22.500 defending this violence and ridiculing anyone who complained about it.

00:11:30.480 Or they'll immediately pivot to,

00:11:32.720 well, what about where were you during Charlottesville, right?

00:11:36.080 Or putting kids in cages at the border is worse, right?

00:11:40.700 That what-aboutery completely misses the point.

00:11:45.400 Yes, there are many things to complain about and worry about.

00:11:49.840 And I spent a fair amount of time talking about what's wrong with Trump

00:11:54.580 and what could become far worse with him, given another four years.

00:12:00.360 And I'm also concerned about the far right.

00:12:03.040 But I'm concerned about the complete breakdown of moral intelligence

00:12:08.020 in the mainstream left at moments like this.

00:12:13.940 This is a crystal clear and very dangerous violation

00:12:18.300 of the most basic norms of civil society.

00:12:23.580 Attacking a journalist, beating him and publicly humiliating him

00:12:28.960 for merely covering a public protest.

00:12:32.660 It should be impossible for liberal people

00:12:36.540 to get their analysis of this wrong.

00:12:40.060 And yet, they reliably do.

00:12:43.560 Anyway, that was the big thing that happened in the last few days.

00:12:47.580 It bears absolutely no relationship to the topic of today's podcast.

00:12:51.960 And now I will move on.

00:12:54.440 Today I'm speaking with Eric Topol.

00:12:57.600 Eric is a world-renowned cardiologist

00:13:00.080 and the executive vice president of the Scripps Research Institute.

00:13:05.880 He's actually one of the top ten most cited medical researchers

00:13:09.920 and the author of several books,

00:13:13.980 The Patient Will See You Now,

00:13:16.020 The Creative Destruction of Medicine,

00:13:18.500 and the book under discussion,

00:13:20.280 Deep Medicine,

00:13:21.380 How Artificial Intelligence Can Make Healthcare Human Again.

00:13:24.360 And we do a deep dive into the current state of medicine.

00:13:28.580 We talk about why we have soaring medical costs

00:13:31.780 and declining health outcomes in the U.S.

00:13:34.440 We talk about the problems of both too little and too much medicine.

00:13:40.300 Talk about how slowly the field has adopted useful technology.

00:13:46.220 And then we get into the current status of AI in medicine

00:13:50.540 and how it could completely transform the field

00:13:54.460 for the better, mostly, but also in ways for the worse.

00:13:58.880 Anyway, I found it a fascinating conversation.

00:14:02.240 I felt it brought me up to speed with these rapid changes.

00:14:06.620 And now, without further delay, I bring you Eric Topol.

00:14:09.660 I am here with Eric Topol.

00:14:17.680 Eric, thanks for coming on the podcast.

00:14:19.860 Oh, great to be with you, Sam.

00:14:21.600 So, if I recall correctly,

00:14:24.120 we met at a whole genome sequencing conference.

00:14:29.900 And I was impressed both with the promise

00:14:32.580 of sequencing the genome at that point

00:14:34.880 and also impressed in the aftermath

00:14:36.980 that there seemed to be almost nothing to do with the information.

00:14:41.120 It felt like it was a few years too early.

00:14:43.420 I mean, are we at a point now where

00:14:44.880 if we had met at that conference,

00:14:46.780 there'd be more that would be actionable?

00:14:49.140 Are we still in kind of a place

00:14:51.280 where there's not a lot to do

00:14:53.160 with one's whole genome being sequenced?

00:14:56.020 Well, it's definitely improving.

00:14:58.080 So, whereas when we first met,

00:15:00.220 it might have been less than 1% chance

00:15:02.440 it would be actionable,

00:15:03.900 now it's getting up to 5%.

00:15:04.980 So, it's definitely getting better,

00:15:07.900 but we still have a ways to go.

00:15:09.320 And it'll take having like a billion people

00:15:11.700 with whole genome sequencing

00:15:12.900 and all their data

00:15:13.740 to finally make it very informative.

00:15:16.860 Well, it is cool,

00:15:17.980 but we're sort of,

00:15:18.560 I mean, we're going to talk about this

00:15:19.760 in some depth

00:15:20.940 in response to your new book,

00:15:23.880 Deep Medicine,

00:15:24.700 where you're talking about

00:15:25.860 how we can use AI,

00:15:28.400 not just with respect to genetics,

00:15:31.640 but really all of medicine.

00:15:32.940 But before we dive in,

00:15:34.580 what's your background as a physician?

00:15:38.520 I'm a cardiologist.

00:15:39.960 I started in practice in cardiology in 1985.

00:15:44.860 So, I've been kind of an old dog

00:15:47.100 30-some years now.

00:15:50.040 Yeah, and then you started

00:15:51.600 the Scripps Institute

00:15:53.360 for Translational Medicine?

00:15:55.140 Yes.

00:15:55.820 That was back in the beginning of 07.

00:15:57.980 It was basically a new,

00:16:01.760 broadened mission of Scripps Research,

00:16:04.300 which had been since 1923

00:16:06.940 a basic science institute.

00:16:08.800 And this is really the applied limb,

00:16:10.740 which is giving it

00:16:11.880 a lot of translational

00:16:13.240 medical research capabilities.

00:16:16.560 Right.

00:16:16.780 So, I can start with a big picture

00:16:18.800 before we get into

00:16:20.200 the high-tech discussion here.

00:16:22.880 It does seem that medicine

00:16:25.280 is broken in many ways,

00:16:27.980 and our discussion

00:16:28.740 will mostly be focused on the U.S.

00:16:31.420 In the U.S., we spend,

00:16:33.760 you know, I have this from your book,

00:16:35.520 $11,000 per person per year

00:16:38.360 on medicine.

00:16:40.140 And, you know, that's still climbing.

00:16:42.420 In 1975, I think it was

00:16:44.000 something like $550.

00:16:46.180 And yet our outcomes

00:16:47.900 don't compare very well

00:16:49.840 with the rest of the developed world.

00:16:51.800 How do you account for that?

00:16:53.580 And how do you view

00:16:55.440 the rising expenditure

00:16:57.880 and seeming plateauing

00:17:00.320 or, in some cases,

00:17:01.160 declining outcome measures?

00:17:03.680 Well, you're absolutely right

00:17:04.720 about the numbers, Sam.

00:17:05.840 And I think the basis of this,

00:17:09.040 which is outcomes

00:17:10.200 of not just lowered life expectancy

00:17:12.820 now in the U.S.

00:17:14.120 three years in a row,

00:17:15.180 which is unprecedented,

00:17:16.280 but also extends

00:17:17.480 to all the important metrics

00:17:19.500 like infant mortality,

00:17:21.460 childhood mortality,

00:17:22.740 maternal mortality,

00:17:23.980 and on and on.

00:17:25.060 So when you look at

00:17:26.200 why has the model

00:17:28.320 in the U.S.

00:17:29.720 gone south,

00:17:31.000 you start to see,

00:17:32.160 well, there's two

00:17:32.820 likely explanations.

00:17:35.460 A big one

00:17:36.320 is that

00:17:37.380 we have

00:17:38.320 major inequities

00:17:40.180 in our care.

00:17:41.120 We don't provide care

00:17:42.280 for all citizens,

00:17:43.240 unlike all the other countries 0.98

00:17:44.880 that are being compared with.

00:17:47.740 The other extreme

00:17:48.920 is that we overcook,

00:17:50.880 that we do too much,

00:17:52.300 so the people

00:17:53.060 who have coverage,

00:17:54.780 they get over-tested,

00:17:56.800 over-treated,

00:17:57.780 and that leads

00:17:59.000 to all sorts of problems,

00:18:00.280 including bad outcomes.

00:18:01.840 So we've got

00:18:02.920 lots of serious problems.

00:18:04.960 Yeah.

00:18:05.380 Well, I must say,

00:18:06.700 I feel like

00:18:08.500 I have a fair amount

00:18:09.820 of experience

00:18:11.280 with the latter problem

00:18:13.540 of too much medicine,

00:18:15.340 or at least

00:18:15.620 too much medicine

00:18:16.380 being offered,

00:18:18.320 and it's often said

00:18:19.800 that, you know,

00:18:20.520 we have the best medicine

00:18:21.560 in the world

00:18:22.160 if you're

00:18:23.480 well-off

00:18:24.980 or well-connected,

00:18:26.680 and yet

00:18:27.760 I always find it

00:18:29.280 incredibly humbling

00:18:30.840 and fairly depressing

00:18:32.600 how hit-or-miss

00:18:34.300 my encounters

00:18:35.040 with medicine are.

00:18:36.560 I'm not a doctor,

00:18:37.740 but my background

00:18:39.140 in neuroscience

00:18:39.620 gives me, you know,

00:18:40.840 a better-than-average

00:18:42.040 position

00:18:43.000 as a consumer

00:18:43.720 of medicine,

00:18:44.400 but I also find

00:18:46.160 whenever I get put

00:18:47.500 into the machinery

00:18:48.480 of the medical system,

00:18:50.500 whether it's because

00:18:51.120 I'm sick

00:18:51.680 or because someone

00:18:52.260 close to me is sick, 0.87

00:18:53.620 one of my kids is sick,

00:18:56.000 rather often

00:18:57.060 I experience

00:18:58.680 a fairly

00:18:59.620 tortuous adventure

00:19:01.360 where,

00:19:02.760 as you said,

00:19:03.540 too much medicine

00:19:04.540 is offered

00:19:05.040 or it could be drugs

00:19:06.700 with serious side effects

00:19:07.860 that are kind of

00:19:08.620 dispensed

00:19:09.220 with a totally

00:19:10.320 cavalier attitude.

00:19:12.540 Risky procedures

00:19:13.380 are recommended

00:19:14.420 almost reflexively,

00:19:16.740 and, you know,

00:19:17.740 there's a whole process

00:19:19.300 of declining

00:19:20.200 to go down this path

00:19:22.060 rather often,

00:19:23.440 and then, as you know,

00:19:24.500 most conditions

00:19:25.020 are self-limiting,

00:19:25.880 and then you feel

00:19:26.620 totally justified

00:19:27.400 for having declined,

00:19:28.760 and then, you know,

00:19:29.600 there's experiences

00:19:30.860 where, you know,

00:19:31.520 scary diagnoses

00:19:32.700 are given

00:19:33.380 only to be overturned

00:19:34.760 by a second opinion,

00:19:36.360 and diagnostic tests

00:19:38.440 are ordered

00:19:39.040 where it's revealed

00:19:40.980 that there really

00:19:42.720 is no thought

00:19:43.900 as to basically

00:19:45.120 the doctor

00:19:45.580 was going to recommend

00:19:46.500 the same treatment

00:19:47.860 or the same lifestyle change

00:19:49.260 regardless of what

00:19:50.240 showed up

00:19:50.760 on that particular test.

00:19:51.720 I mean, it's just,

00:19:52.380 I find my encounters

00:19:53.320 with medicine

00:19:54.020 weird

00:19:55.160 almost, you know,

00:19:56.660 more often than not,

00:19:58.120 and this is,

00:19:59.320 and I consider myself

00:20:00.180 to be probably

00:20:01.020 in the most fortunate

00:20:03.760 possible position

00:20:05.040 with respect to

00:20:06.060 being a consumer

00:20:06.740 of medicine,

00:20:07.360 and yet,

00:20:08.020 with a possible exception

00:20:09.120 to your own,

00:20:10.340 where you're a celebrated

00:20:11.960 physician, right?

00:20:13.380 You're a physician with,

00:20:14.920 you know,

00:20:15.140 you're not just

00:20:16.020 an average physician,

00:20:16.980 you're a very connected one,

00:20:19.740 and, you know,

00:20:21.000 you've made significant

00:20:22.280 contributions to your field,

00:20:23.820 and yet you open your book

00:20:26.220 with a totally harrowing

00:20:28.500 encounter

00:20:29.000 with your own,

00:20:31.000 you know,

00:20:31.600 medical history.

00:20:33.800 I'm sure you've talked

00:20:34.800 about this a lot

00:20:35.400 because you open your book

00:20:36.440 with it,

00:20:36.780 and it's fairly arresting,

00:20:37.880 but perhaps just give us

00:20:40.200 your experience with,

00:20:41.980 you know,

00:20:42.520 something like medical

00:20:43.760 malpractice,

00:20:44.780 which you as a physician

00:20:46.360 still, it seems,

00:20:49.300 couldn't protect yourself from.

00:20:51.200 Right.

00:20:51.700 Well, Sam,

00:20:52.160 it was harrowing.

00:20:53.320 That was a good word

00:20:54.880 to assign to it.

00:20:56.860 I was having a knee

00:20:57.780 replacement.

00:20:59.280 It was almost

00:20:59.860 three years ago now,

00:21:01.160 and I had thought

00:21:02.720 it would be

00:21:03.440 pretty straightforward

00:21:04.560 because I was

00:21:06.060 pretty physically fit

00:21:07.320 and, you know,

00:21:08.640 thin and relatively young

00:21:10.640 compared to a lot of people

00:21:11.740 who have knee replacements,

00:21:12.980 and I had referred

00:21:13.780 many patients

00:21:15.060 to the same orthopedist,

00:21:17.080 so I had some confidence,

00:21:19.320 but what happened was

00:21:20.800 I had a disastrous

00:21:22.420 post-operative complication,

00:21:24.740 which I didn't even,

00:21:25.380 I'd never heard of the word

00:21:26.620 arthrofibrosis,

00:21:28.400 and part of that really was

00:21:30.280 I had a high risk

00:21:31.320 that I didn't know about

00:21:32.300 because I had a congenital condition

00:21:34.260 called osteochondritis dissecans,

00:21:36.660 which set me up for that,

00:21:38.040 so this really was horrendous.

00:21:43.500 You know,

00:21:43.760 I couldn't sleep.

00:21:45.360 I was in pain.

00:21:46.560 I was taking opiates,

00:21:48.440 and I went,

00:21:49.840 showed up,

00:21:50.400 you know,

00:21:51.460 with all this,

00:21:52.920 you know,

00:21:53.180 really bad state

00:21:54.680 with my wife

00:21:55.580 to the orthopedist

00:21:56.820 about a month

00:21:57.540 after the surgery,

00:21:59.340 and he said to me,

00:22:00.940 I need to get

00:22:01.560 some anti-depression medications.

00:22:04.180 Right.

00:22:04.780 And I said,

00:22:05.700 what?

00:22:06.420 You know,

00:22:06.780 so this is

00:22:08.020 like the shallow medicine,

00:22:09.860 you know,

00:22:10.340 robotic.

00:22:11.140 I mean,

00:22:11.340 here's a human expert

00:22:12.960 who did the surgery.

00:22:14.740 That wasn't the issue.

00:22:15.820 It was the post-operative care,

00:22:17.380 and I think

00:22:19.400 that's telling.

00:22:20.420 I think that

00:22:21.000 almost everyone now

00:22:22.900 who I talk to

00:22:23.700 has had either

00:22:24.600 on their own

00:22:25.600 or their family members,

00:22:26.960 loved ones,

00:22:27.680 have had a roughed-up experience,

00:22:29.860 and that's what it was for me.

00:22:32.260 Yeah,

00:22:32.520 so

00:22:32.820 maybe this doesn't account

00:22:34.780 for

00:22:35.440 your experience.

00:22:37.740 I mean,

00:22:37.800 on some level,

00:22:39.120 there's a fair amount

00:22:40.400 of bad luck there,

00:22:42.080 and also just,

00:22:43.140 I mean,

00:22:43.380 obviously the diagnosis

00:22:44.520 was missed,

00:22:45.080 or your risk potential

00:22:46.820 for that complication

00:22:47.980 was missed,

00:22:49.140 and we could talk about

00:22:49.960 the way in which AI

00:22:50.960 might make that

00:22:52.120 less likely to happen,

00:22:54.040 but I don't know.

00:22:54.720 It feels like

00:22:55.160 there's just a problem

00:22:56.300 in the culture

00:22:58.460 of medicine.

00:23:00.060 I mean,

00:23:00.200 medicine is kind of

00:23:01.760 a priesthood.

00:23:02.840 I mean,

00:23:03.040 it's like the way

00:23:03.920 people relate

00:23:05.280 to doctors

00:23:05.960 is a far less

00:23:07.960 straightforward

00:23:08.600 transaction

00:23:10.460 with respect to

00:23:11.760 the use of

00:23:12.840 another person's

00:23:13.500 expertise,

00:23:14.040 disease,

00:23:14.480 and

00:23:15.420 it's difficult

00:23:17.220 to navigate

00:23:17.840 for almost anyone

00:23:19.840 because,

00:23:20.440 in part,

00:23:20.740 it's the subject matter.

00:23:21.720 I mean,

00:23:21.820 you're dealing

00:23:22.200 in some,

00:23:23.160 in many cases,

00:23:24.340 either with life and death

00:23:25.440 questions

00:23:26.320 or

00:23:26.900 a concern,

00:23:28.500 a legitimate concern

00:23:29.220 about,

00:23:29.680 you know,

00:23:30.440 significant disability

00:23:32.000 or suffering

00:23:32.660 or risk,

00:23:34.300 and

00:23:35.000 I don't know.

00:23:36.200 We know so much

00:23:36.940 about how

00:23:37.860 impossible it is

00:23:40.040 for people

00:23:41.160 to navigate

00:23:43.300 their own

00:23:43.840 cognitive biases.

00:23:45.040 I mean,

00:23:45.160 we know that

00:23:45.740 physicians are

00:23:46.880 making diagnoses

00:23:48.900 based on

00:23:49.860 their clinical

00:23:50.760 experience

00:23:51.440 in ways

00:23:51.900 that really

00:23:52.620 distort the,

00:23:53.980 you know,

00:23:54.420 their sense

00:23:54.620 of probability

00:23:55.300 and the accuracy

00:23:56.100 of diagnosis

00:23:56.760 is way off.

00:23:58.460 I mean,

00:23:58.560 this is something

00:23:58.860 you touch

00:23:59.180 in your book

00:23:59.660 by reference

00:24:00.360 to Danny Kahneman

00:24:01.380 and Amos Tversky's

00:24:03.120 work.

00:24:03.860 There's something

00:24:04.340 about the culture

00:24:06.280 that,

00:24:07.280 again,

00:24:07.620 we haven't yet

00:24:08.220 introduced robots

00:24:09.380 into the equation

00:24:10.500 here,

00:24:10.820 but I mean,

00:24:11.640 can you say

00:24:11.920 anything about that?

00:24:12.680 I mean,

00:24:12.860 my impression

00:24:14.620 here is fairly

00:24:15.460 inchoate,

00:24:16.160 but I just realized

00:24:16.880 that there's,

00:24:17.820 I mean,

00:24:18.000 just the process

00:24:19.120 of,

00:24:19.540 you know,

00:24:19.820 getting second

00:24:20.420 opinions

00:24:20.940 is often weird

00:24:22.360 and what you do

00:24:23.580 with opinions

00:24:24.500 that can't be

00:24:25.200 reconciled

00:24:26.040 and how do you

00:24:27.960 see the effect

00:24:29.100 of putting on

00:24:29.720 a white lab coat

00:24:30.840 on,

00:24:31.380 you know,

00:24:32.700 the conversation

00:24:33.400 and the

00:24:35.060 relevant cognition?

00:24:36.860 Right.

00:24:37.140 Well,

00:24:37.760 you're touching on

00:24:39.380 this medical

00:24:40.020 paternalism,

00:24:41.540 which is

00:24:42.160 the sense

00:24:43.720 that,

00:24:44.160 you know,

00:24:44.400 doctor is

00:24:45.100 a know-all

00:24:46.100 entity

00:24:46.620 and that

00:24:48.260 wasn't as big

00:24:49.940 a problem

00:24:50.540 decades ago

00:24:51.700 when there was

00:24:52.940 a lot of trust,

00:24:54.300 there was presence,

00:24:55.160 there was a deep

00:24:55.720 relationship

00:24:56.540 and really

00:24:57.700 an intimacy,

00:24:59.140 an inner human bond.

00:25:00.840 But what's happened

00:25:01.560 over time

00:25:02.280 is that paternalism

00:25:03.820 has sustained

00:25:06.120 and at the same

00:25:07.860 time,

00:25:08.240 there's very

00:25:08.580 little time

00:25:09.180 with patients.

00:25:10.720 It's very

00:25:11.300 much a lack

00:25:12.860 of presence

00:25:13.380 because,

00:25:13.900 you know,

00:25:14.280 doctors are

00:25:14.980 looking at

00:25:16.240 keyboards

00:25:16.760 and they

00:25:18.200 really don't

00:25:18.720 have the time

00:25:19.560 to cultivate

00:25:21.240 a relationship.

00:25:22.400 So,

00:25:22.900 it's gotten

00:25:23.380 much worse.

00:25:24.860 It's the same 0.53

00:25:25.480 problem,

00:25:26.180 the basic

00:25:26.560 problem of

00:25:27.400 the kind of

00:25:28.380 authority,

00:25:29.180 control,

00:25:30.040 don't question

00:25:30.880 my opinion.

00:25:31.840 What do you mean

00:25:32.520 that you need

00:25:33.120 a second

00:25:33.520 opinion

00:25:33.980 when everyone

00:25:35.020 should be

00:25:36.000 entitled

00:25:36.400 and feel

00:25:37.080 very comfortable

00:25:37.780 to have

00:25:38.420 that second

00:25:38.880 opinion?

00:25:39.340 But this

00:25:40.160 doesn't

00:25:41.660 fit in

00:25:42.680 any longer

00:25:43.180 because

00:25:43.680 there's not

00:25:44.420 a relationship.

00:25:45.640 It's eroded

00:25:46.580 so seriously

00:25:47.420 over the last

00:25:48.760 three or four

00:25:49.440 decades.

00:25:51.620 It's interesting,

00:25:52.520 despite how much

00:25:53.920 we're spending

00:25:54.500 on medicine

00:25:55.140 each year,

00:25:56.660 and again,

00:25:57.080 the costs

00:25:58.060 are just going

00:25:58.620 up and up,

00:25:59.620 the field

00:26:00.200 is actually

00:26:00.920 very slow

00:26:02.240 to adopt

00:26:03.040 new technology.

00:26:04.680 And this is

00:26:05.320 something that

00:26:05.880 we've all

00:26:06.980 noticed the

00:26:07.760 transition to

00:26:08.520 electronic

00:26:09.520 health records,

00:26:11.040 which has

00:26:11.840 seemed somewhat

00:26:13.300 dysfunctional

00:26:14.100 and somewhat

00:26:15.420 haphazard.

00:26:16.920 I mean,

00:26:17.200 that just

00:26:18.680 feels like

00:26:19.140 as far as

00:26:20.160 this adoption

00:26:20.640 of tech

00:26:21.260 medicine is,

00:26:23.040 apart from

00:26:23.940 the introduction

00:26:25.240 of some

00:26:25.660 new scanner

00:26:26.500 from time

00:26:27.060 to time,

00:26:27.920 it seems

00:26:28.640 more like

00:26:29.260 the FAA

00:26:29.960 dealing with

00:26:31.000 old equipment

00:26:31.660 than it

00:26:33.380 looks like

00:26:34.280 Silicon Valley

00:26:34.960 dealing with

00:26:35.540 the latest

00:26:36.320 breakthrough

00:26:37.400 in consumer

00:26:38.580 tech.

00:26:39.120 How do you

00:26:39.920 view medicine

00:26:41.140 and tech

00:26:41.740 in general?

00:26:43.460 Yeah,

00:26:43.680 it's a pretty

00:26:44.140 sad story.

00:26:45.840 A lot of

00:26:46.220 people think

00:26:47.240 digital medicine

00:26:48.420 arrived with

00:26:49.240 the electronic

00:26:49.700 health record,

00:26:51.040 and that was

00:26:51.860 an abject

00:26:52.900 failure,

00:26:53.980 a disaster,

00:26:54.660 because when

00:26:55.860 those were

00:26:56.260 introduced,

00:26:57.600 they were set

00:26:58.520 up for

00:26:59.000 billing purposes

00:26:59.920 without any

00:27:01.320 consideration

00:27:01.880 of how

00:27:02.840 that would

00:27:03.160 affect either

00:27:04.100 patients or

00:27:04.820 doctors or

00:27:05.780 other clinicians.

00:27:07.180 So really,

00:27:07.820 that was actually

00:27:08.440 the motive?

00:27:09.020 It wasn't to

00:27:09.840 be able to

00:27:10.700 aggregate

00:27:11.500 information better?

00:27:13.720 No,

00:27:14.240 no,

00:27:14.500 it was just

00:27:14.820 to have

00:27:15.160 really good

00:27:15.680 billing,

00:27:16.100 to not miss

00:27:16.620 things.

00:27:17.640 It's amazing,

00:27:19.040 and it's not

00:27:19.960 really ever

00:27:20.500 improved.

00:27:21.060 It's the most

00:27:21.520 clunky, 1.00

00:27:22.760 pathetic software, 0.99

00:27:24.400 and across all 0.98

00:27:25.140 the different

00:27:25.480 companies that

00:27:26.460 are in this

00:27:27.560 business.

00:27:28.780 And that

00:27:29.740 had led to

00:27:30.860 doctors becoming

00:27:31.780 data clerks,

00:27:32.940 and has been

00:27:34.580 one of the

00:27:35.860 most important

00:27:36.620 aspects of why

00:27:37.580 there's such

00:27:38.340 profound burnout

00:27:39.340 in the medical

00:27:40.840 field,

00:27:41.700 with more than

00:27:42.260 half having

00:27:43.620 expressed that

00:27:45.020 they are

00:27:45.560 burnout,

00:27:46.020 but also over

00:27:46.740 20%,

00:27:47.480 even with

00:27:48.360 clinical depression

00:27:49.280 and the highest

00:27:50.020 numbers of

00:27:51.060 suicides ever

00:27:52.060 in the medical

00:27:52.900 profession.

00:27:54.800 And is there

00:27:55.540 anyone tracking

00:27:56.280 just the

00:27:56.740 actual use

00:27:58.040 of doctors'

00:27:58.940 time with

00:27:59.500 respect to

00:28:00.340 this new

00:28:01.020 technology?

00:28:01.960 Has the

00:28:02.500 experience of

00:28:03.360 being a

00:28:03.640 doctor been

00:28:04.620 more of

00:28:05.360 one dealing

00:28:06.400 with records

00:28:07.740 and insurance

00:28:08.420 and all the

00:28:09.620 rest,

00:28:10.000 and year by

00:28:10.840 year?

00:28:11.700 Exactly.

00:28:12.500 So what's

00:28:12.900 happened,

00:28:13.400 I mean,

00:28:13.620 the most

00:28:13.880 recent study

00:28:14.640 was that

00:28:15.760 80% of

00:28:17.180 the time

00:28:17.900 that medical

00:28:19.500 residents

00:28:20.180 were spending

00:28:22.600 without any

00:28:23.980 contact to

00:28:24.640 patients because

00:28:25.360 they were

00:28:25.580 working on

00:28:26.160 electronic health

00:28:27.220 records and

00:28:27.960 administrative

00:28:28.460 tasks.

00:28:29.500 And all the

00:28:29.940 recent time

00:28:30.600 studies that

00:28:31.320 have really

00:28:31.640 delved into

00:28:32.240 this show

00:28:32.740 a two-to-one

00:28:33.940 or greater

00:28:34.500 ratio of

00:28:35.520 time away

00:28:36.180 from patients.

00:28:37.780 So this

00:28:39.080 electronic health

00:28:39.900 record, which

00:28:40.540 is unfortunately

00:28:41.900 the precursor

00:28:43.020 of bringing

00:28:43.700 the digital

00:28:44.680 world into

00:28:45.480 the medical

00:28:46.560 profession,

00:28:47.880 has backfired.

00:28:49.080 It's really

00:28:49.760 been a

00:28:50.800 serious hit

00:28:51.660 to the

00:28:52.640 care of

00:28:54.020 patients.

00:28:55.900 And what

00:28:56.580 about other

00:28:57.200 technology like

00:28:58.820 diagnostic

00:29:00.080 imaging?

00:29:01.160 And I

00:29:02.120 remember,

00:29:02.800 you know,

00:29:03.900 I've had a

00:29:04.680 few adventures

00:29:05.520 in cardiology,

00:29:06.440 which is your

00:29:06.920 wheelhouse,

00:29:08.060 you know,

00:29:08.300 like a CT

00:29:09.520 scan, you

00:29:09.940 know, calcium

00:29:10.320 score scan,

00:29:11.560 and it's,

00:29:13.300 again, I

00:29:14.100 have found the

00:29:14.940 way in which

00:29:15.460 this imaging

00:29:16.040 has been

00:29:16.800 dispensed to

00:29:17.460 me.

00:29:17.660 I mean,

00:29:17.760 you know,

00:29:18.000 I've done it

00:29:19.280 and, you

00:29:20.340 know, happily,

00:29:21.200 I guess, you

00:29:22.020 know, I would

00:29:23.020 probably be

00:29:23.440 telling a

00:29:23.860 different story

00:29:24.440 if something

00:29:25.140 scary and

00:29:26.280 actionable were

00:29:26.960 found and I

00:29:27.680 had felt my

00:29:28.360 life was saved

00:29:29.140 by it.

00:29:29.620 But the way

00:29:30.920 this was

00:29:32.760 dispensed to

00:29:33.400 me was

00:29:34.780 cavalier enough

00:29:36.980 and it was

00:29:37.280 just like, we

00:29:37.640 now have this

00:29:38.180 new tool, let's

00:29:38.820 use it.

00:29:39.700 And there was

00:29:40.880 nothing, and I

00:29:41.700 got to the end

00:29:42.280 of the process

00:29:43.240 and it was

00:29:43.540 really, there

00:29:44.260 was just, it

00:29:45.260 was pretty clear

00:29:45.880 that it just

00:29:47.160 didn't make

00:29:47.480 sense in my

00:29:48.380 case.

00:29:49.280 to have done

00:29:50.080 this.

00:29:50.500 And so, how

00:29:51.700 do you view

00:29:52.160 just these

00:29:52.840 intrusions of

00:29:53.620 new machines

00:29:54.340 which could

00:29:55.260 be very

00:29:56.540 useful but

00:29:57.400 are either

00:29:58.600 used in

00:29:59.840 cases where

00:30:00.820 there's just

00:30:01.820 no reason

00:30:02.820 to use them

00:30:03.440 and I guess

00:30:04.440 we should also

00:30:04.920 talk about the

00:30:05.540 prospect of

00:30:06.260 type 1 errors

00:30:07.860 here where

00:30:08.260 people get

00:30:08.840 false positives

00:30:09.940 which then

00:30:10.620 they go chasing

00:30:11.440 with yet more

00:30:12.300 intrusive

00:30:13.260 procedures and

00:30:14.780 incur other

00:30:15.880 risks.

00:30:16.300 exactly for

00:30:18.160 that too.

00:30:18.980 The problem

00:30:19.820 here is we've

00:30:21.040 got a lot of

00:30:21.600 good technologies

00:30:22.680 but they're

00:30:24.080 misused, they're

00:30:25.240 overused.

00:30:26.280 So, the

00:30:26.820 example you

00:30:27.360 gave of a

00:30:29.200 calcium score

00:30:30.240 with a CT

00:30:31.280 scan to see

00:30:32.520 whether or not

00:30:33.020 you may have

00:30:33.680 coronary disease,

00:30:35.200 that test is

00:30:36.580 terribly overused.

00:30:37.880 I have never

00:30:38.680 ordered that test.

00:30:40.640 And mine was

00:30:41.120 worse, I had

00:30:41.560 an angiogram, I

00:30:42.400 didn't just have

00:30:42.880 the ordinary CT.

00:30:44.360 Yeah, so that

00:30:46.660 likely fits into

00:30:48.860 the so many

00:30:50.800 patients that I've

00:30:51.540 seen for second

00:30:52.260 opinions who

00:30:53.760 have become

00:30:54.760 disabled, who

00:30:56.740 have become

00:30:57.500 adversely affected

00:30:58.940 by the results

00:30:59.760 of their calcium

00:31:00.760 score even though

00:31:01.620 they have no

00:31:02.140 symptoms or others

00:31:03.880 that have been

00:31:04.260 told their lives

00:31:04.940 have been saved

00:31:05.580 because they are

00:31:06.200 whisked away from

00:31:07.220 the CAT scan to

00:31:08.500 then have an

00:31:08.980 angiogram and

00:31:09.760 stents or even

00:31:10.840 a bypass operation.

00:31:12.680 So, you know,

00:31:13.560 cardiac cripples 1.00

00:31:14.340 have been a result

00:31:15.820 of some of these

00:31:16.520 scans with patients

00:31:18.100 without any

00:31:18.820 symptoms and it's

00:31:19.920 really unsettling.

00:31:20.880 So, this is

00:31:22.020 an exemplar of

00:31:23.540 so many tests

00:31:24.680 that we have

00:31:25.160 today that they

00:31:26.040 can be helpful

00:31:26.660 in certain

00:31:27.260 individuals but

00:31:28.540 they can be

00:31:29.080 very harmful

00:31:30.300 as well.

00:31:32.080 And these

00:31:33.000 particular harms,

00:31:33.860 so I guess there's

00:31:34.460 two problems here.

00:31:35.380 We have the

00:31:36.260 underuse or lack

00:31:37.780 of availability

00:31:38.540 of medicine

00:31:39.860 to people who

00:31:40.660 really need it

00:31:41.480 and who have

00:31:41.840 substandard care

00:31:43.080 in a first world

00:31:44.520 society, our own,

00:31:46.380 that doesn't compare

00:31:47.220 favorably to the

00:31:48.680 rest of the

00:31:49.400 developed world.

00:31:50.860 But then here

00:31:51.680 we're talking about

00:31:52.560 the high class

00:31:54.140 problem of

00:31:55.160 having a more

00:31:57.380 consumer relationship

00:31:58.680 to advanced

00:32:00.400 medicine where

00:32:01.120 you have access

00:32:02.180 to what are

00:32:04.620 ostensibly the

00:32:05.240 best doctors,

00:32:06.120 the best hospitals,

00:32:07.000 the best

00:32:07.940 information,

00:32:08.900 the new

00:32:09.240 scanners,

00:32:10.540 and although

00:32:11.880 even there,

00:32:12.640 I mean,

00:32:12.760 just to give you

00:32:13.740 a reference

00:32:14.240 point for this

00:32:14.980 angiogram,

00:32:15.820 so I went to

00:32:16.860 a highly

00:32:18.260 regarded

00:32:18.760 cardiologist

00:32:19.760 on the

00:32:20.700 assumption that

00:32:21.420 whatever scanner

00:32:22.440 he would be

00:32:22.900 putting me in

00:32:23.500 would be the

00:32:24.880 latest and

00:32:25.660 lowest dose

00:32:26.440 of radiation

00:32:27.500 scanner.

00:32:28.720 And then I

00:32:29.080 get the scan

00:32:30.620 and I see

00:32:31.080 the amount

00:32:32.060 of radiation

00:32:32.540 delivered and

00:32:33.620 I just kind

00:32:34.180 of check this

00:32:34.760 with a friend

00:32:35.820 who's a

00:32:36.120 physician who

00:32:37.000 has access

00:32:38.100 to similar

00:32:39.300 doctors and

00:32:40.120 he said,

00:32:41.160 yeah,

00:32:41.360 if I had

00:32:42.340 ordered the

00:32:42.700 scan,

00:32:43.080 you would

00:32:43.440 have gotten

00:32:43.860 one-third

00:32:44.800 the amount

00:32:45.660 of dosage

00:32:47.380 there,

00:32:48.300 so it's like

00:32:48.640 I'm not quite

00:32:49.080 sure why

00:32:49.760 you got put

00:32:50.940 in that

00:32:51.200 scanner.

00:32:52.140 And just the

00:32:52.500 fact that

00:32:52.760 there's that

00:32:53.180 kind of

00:32:53.480 variance,

00:32:53.940 I'm not

00:32:55.040 especially

00:32:55.840 paranoid about

00:32:56.500 this,

00:32:56.800 I understand

00:32:57.440 that this

00:32:58.220 doesn't raise

00:32:58.700 my cancer

00:32:59.460 risk all

00:32:59.920 that much,

00:33:00.360 but the

00:33:00.980 fact that

00:33:01.620 in the

00:33:02.340 most

00:33:02.580 prestigious

00:33:03.220 networked

00:33:04.380 circles,

00:33:05.280 there could

00:33:05.600 be that

00:33:05.900 kind of

00:33:06.200 variance,

00:33:06.700 it's just

00:33:07.860 bizarre to

00:33:08.360 me.

00:33:09.400 Well,

00:33:09.780 you've just

00:33:10.360 touched on

00:33:10.940 something as

00:33:11.540 a pet peeve

00:33:12.180 of mine,

00:33:12.700 which is why

00:33:13.780 don't we tell

00:33:14.400 patients when

00:33:15.140 we order a

00:33:16.540 test or say

00:33:17.540 they should

00:33:17.880 have such a

00:33:18.500 test that

00:33:19.320 uses ionizing

00:33:20.280 radiation about

00:33:21.760 how much

00:33:22.700 radiation they

00:33:23.420 would be

00:33:23.620 exposed to.

00:33:24.340 That is,

00:33:24.920 we don't have

00:33:25.520 to use the

00:33:26.100 millisieverts

00:33:26.820 units,

00:33:27.980 we could say

00:33:28.740 it's equivalent

00:33:29.380 to how many

00:33:30.020 chest x-rays.

00:33:31.600 All right,

00:33:31.780 so this physician

00:33:33.160 who I will not

00:33:33.700 name,

00:33:34.400 but whose name

00:33:35.120 would be known

00:33:35.780 to you,

00:33:36.840 as part of

00:33:37.500 this pattern,

00:33:38.100 I asked the

00:33:39.020 perfunctory

00:33:39.980 skeptical questions

00:33:41.400 about whether

00:33:41.840 this scan was

00:33:42.720 necessary and

00:33:43.380 what my

00:33:44.820 dosage would

00:33:45.880 be,

00:33:46.480 and he said,

00:33:46.920 well,

00:33:47.080 it's analogous

00:33:47.940 to you taking

00:33:49.220 10 flights to

00:33:50.420 Hong Kong this

00:33:51.460 year.

00:33:52.300 Has someone told

00:33:53.480 you that you

00:33:54.100 shouldn't go to

00:33:54.920 Hong Kong 10

00:33:55.680 times this year?

00:33:57.060 And I said,

00:33:58.580 no, no,

00:33:59.220 that sounds fine.

00:34:00.120 I mean,

00:34:00.280 it's a lot of

00:34:01.000 Hong Kong,

00:34:01.540 but I can do

00:34:02.560 that.

00:34:02.800 But then when

00:34:03.460 I actually saw

00:34:04.920 my dosage and

00:34:05.780 did a little

00:34:06.400 arithmetic,

00:34:07.120 it was more

00:34:07.860 like 150 to

00:34:10.160 200 flights to

00:34:11.160 Hong Kong this

00:34:11.940 year.

00:34:12.420 Right.

00:34:12.660 Right.

00:34:12.920 So it's just,

00:34:14.520 again, I guess I

00:34:16.180 could be an

00:34:16.580 airline pilot this

00:34:17.420 year and it's

00:34:17.840 okay, but still

00:34:19.260 it's just to have

00:34:20.260 that wrong by

00:34:21.800 orders of

00:34:22.960 magnitude,

00:34:23.380 it's just

00:34:24.580 bizarre.

00:34:25.700 Well, and also

00:34:26.620 if you take it

00:34:28.480 by number of

00:34:29.880 chest x-rays,

00:34:30.500 when you tell a

00:34:31.100 patient that's

00:34:31.700 like 2,000

00:34:32.660 chest x-rays,

00:34:33.700 they say,

00:34:34.300 no, no,

00:34:34.760 I'm not doing

00:34:35.600 that.

00:34:36.240 Right.

00:34:36.440 So if we just

00:34:37.620 were real about,

00:34:39.580 and the other

00:34:40.060 thing you mentioned

00:34:41.020 I think has to be

00:34:42.220 underscored as well

00:34:43.400 is that there's so

00:34:44.640 much variability

00:34:45.440 in the exposure

00:34:46.880 of the radiation.

00:34:48.680 So we have,

00:34:50.480 again, this is out

00:34:51.220 of paternalism,

00:34:52.200 there's,

00:34:53.180 you're rare because

00:34:54.400 you actually ask

00:34:55.340 your doctor,

00:34:56.420 but most patients

00:34:57.440 just go and have

00:34:58.600 the scan.

00:34:59.720 Right.

00:35:00.480 And so this is

00:35:01.760 something that's

00:35:02.300 just not right

00:35:03.100 because this is

00:35:04.280 information that

00:35:05.180 everybody should be

00:35:06.080 entitled to and

00:35:07.140 they should be

00:35:07.780 part of the

00:35:08.480 decision of whether

00:35:09.300 they want to

00:35:09.960 accept that type

00:35:10.940 of exposure to

00:35:11.800 radiation.

00:35:12.900 Okay, so let's

00:35:13.860 bring in the

00:35:14.540 robots.

00:35:16.540 How did you get

00:35:17.940 interested in AI?

00:35:19.240 When do you date

00:35:20.300 your awareness of

00:35:21.940 it as a possibly

00:35:23.240 relevant technology?

00:35:24.400 Well, you know,

00:35:26.580 I had been working

00:35:27.360 in the prior

00:35:28.300 times on

00:35:29.560 digital medicine.

00:35:31.480 That was a

00:35:31.880 creative destruction

00:35:32.540 medicine.

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Making Sense - Sam Harris - July 03, 2019

#162 — Medical Intelligence

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