The Art of Manliness - #649： Thinking for Yourself in an Age of Outsourced Expertise

00:00:00.000 Brett McKay here and welcome to another edition of the Art of Manliness podcast. In an age

00:00:11.340 where endless streams of data, options and information are available, it can feel like

00:00:14.780 every choice from what TV show to watch to how to invest your money ought to be optimized.

00:00:18.980 And yet making any choice, much less an ideal one, can seem completely overwhelming. So

00:00:23.140 how do we figure out what to do? Well, much of the time we don't. Instead, we outsource

00:00:26.700 our thinking to technology, experts and set protocols. This, my guest today says, is

00:00:30.760 where some real problems start. His name is Dr. Vikram Mantramani, and he's a Harvard lecturer

00:00:35.220 who studies future trends and risk, as well as the author of Think for Yourself, Restoring

00:00:39.160 Common Sense in an Age of Experts and Artificial Intelligence. Today on the show, Vikram explains

00:00:43.400 how our increasingly complex lives have led us to increasingly rely on algorithms, specialists

00:00:47.680 and checklists to make decisions, even though experts are best suited to entangling complications

00:00:52.420 rather than complexities. We've talked about the difference between the two. We then discuss

00:00:55.840 the issues that can therefore arise and rely on expert advice, including the siloing of

00:00:59.640 information and the application of misdirected focus. Once we diagnose the problem, we then

00:01:04.280 turn to the solution and how we can harness the good that technology and experts can provide

00:01:08.160 without undermining our ability to still think for ourselves by doing things like asking experts

00:01:12.500 about their incentives, knowing our own goals, triangulating opinions and crossing silos.

00:01:17.260 And we enter a conversation with how the serendipitous discovery of perspectives that can come

00:01:20.740 from flipping through a paper magazine and browsing a bookstore can be part of restoring self-reliant

00:01:24.980 thinking in the 21st century. After the show's over, check out our show notes at awim.is

00:01:29.060 slash thinkforyourself.

00:01:40.780 Vikram Mantra-Romney, welcome to the show.

00:01:43.360 Thanks for having me, Brett. Grilled to be with you.

00:01:45.580 Well, you just came out with a new book called Think for Yourself, Restoring Common Sense in

00:01:49.620 an Age of Experts and Artificial Intelligence. And in this book, you're making the case in the past

00:01:54.040 few decades, lay people, like just regular folks, have been increasingly outsourcing their thinking

00:01:59.940 to experts and even technology. And I'm sure we'll dig into some examples deep, but just off the top,

00:02:06.660 sort of give us a big picture view. What are some examples that you've seen where you see people

00:02:11.120 just outsourcing their thinking to experts in technology?

00:02:14.800 Sure. So, well, Brett, I think it starts off with the idea that we're drowning in information

00:02:19.520 and data. And then the result has been more and more decisions are being put in front of us to be

00:02:26.500 made. And so we have too many choices. And we think because there are more choices, that there is a

00:02:32.620 perfect answer, that there's an optimal decision to be made. We also know we can't make that by

00:02:38.460 ourselves, that we don't have enough information to do so. Or frankly, we have too much information

00:02:42.540 and we need some help. So we turn to expertise. And expertise can be embodied in the form of

00:02:48.180 technology, human beings, i.e. experts, or even checklists and rules. And so just think about the

00:02:54.660 GPS device that many of us use when we navigate our way around town. A lot of us have stopped

00:02:59.560 thinking about maps. We don't actually know sometimes where we are, but we'll listen to this

00:03:04.740 little voice that tells us make a left up here in 300 yards, stay in the right lane, merge left,

00:03:10.480 etc. So that's a great example where we've stopped thinking about the dynamics of geography

00:03:16.100 and our path within it. And we've resulted in just outsourcing our thinking to the GPS device.

00:03:21.820 Well, another example of outsourcing our thinking to technology is algorithms, right? You go to Amazon

00:03:26.180 and instead of thinking, oh, do I really like this book? You just rely on the algorithms

00:03:30.580 that Amazon says, yeah, you're going to like this book. So shut up and buy the book. 0.98

00:03:35.520 That's right. Think about it. You used to go to a bookstore, at least I used to. I don't know how old 1.00

00:03:39.460 the listeners are, but I used to go to bookstores where I would browse the shelves. I went looking

00:03:44.480 for a topic, possibly a specific book, and I would find adjacent titles, other things. And it was this

00:03:50.880 somewhat unorganized, albeit fortuitous, search process that often was fortuitous.

00:03:57.180 Nowadays, you end up in these little echo chambers. You expressed interest in a book on

00:04:02.240 baseball strategy. Amazon's going to recommend a lot of baseball strategy books to you over time.

00:04:07.680 And they're going to get more and more specific because that's more and more likely based on

00:04:11.860 your revealed preference of having purchased that book or that topic. And so, yeah, I think that

00:04:17.280 those algorithms are conscientiously managing where we pay attention.

00:04:22.140 And what sorts of problems can pop up when we over rely on experts in technology?

00:04:26.840 Well, think about it this way. Experts in technologies live in silos. And we live in the real world where

00:04:33.600 there's a context outside of those silos. But when you rely only on the siloed information,

00:04:39.620 you're not seeing the big picture. You're not seeing the context. And so, what you get is

00:04:45.180 information that's optimized in a particular domain, but may not be optimized for you or your

00:04:51.240 overall context. So, I think the biggest problem is the silo effect, if you will.

00:04:56.580 And when did you start noticing this outsourcing of thinking was starting to cause problems?

00:05:00.960 Well, it really has to do with my first book. My first book was about financial bubbles.

00:05:07.800 What I realized was economists and those that were very narrow and focused, i.e. those who were deep

00:05:13.620 and specialized, sometimes missed what was deemed very obvious to the layperson. And what I realized

00:05:20.280 was actually a multi-lens, multidisciplinary view could help you identify dynamics that a single

00:05:27.340 perspective might miss. And so, what I realized was actually every perspective was limited,

00:05:33.400 biased, and incomplete. Combine that with the fact that we often outsource to people who have really

00:05:39.140 deep focus and expertise. And what you realize is you're outsourcing your thinking to incomplete

00:05:44.380 perspectives. So, why do that? Or if you're going to do that, maybe consult multiple perspectives.

00:05:51.000 So, you know, we can triangulate by discussing your insights with that of an insight from another

00:05:56.200 expert, with another expert, with another expert, and really triangulate to get some sense of what

00:06:01.240 the problem really is about. So, you mentioned earlier, one of the reasons why we started to rely

00:06:06.000 more on experts is that we're just flooded, inundated with information. There's so many choices.

00:06:12.040 But not only that, I think everyone's experienced information overload, which is why they go to Google

00:06:16.260 and they look for, you know, they Google like best whatever for my kid. We'll talk about optimization

00:06:21.180 here in a bit. But besides being flooded with information, things have gotten more complex. Like

00:06:27.340 the information we have to work with is much more complex. What does that look like? I mean, let's flesh

00:06:32.040 that out for us a little bit. Like, what does the increasing complexity look like? And how is it pushing

00:06:36.620 us towards the, you know, towards experts in technology?

00:06:40.520 Yeah. So, I think there's a little nuance here, Brett, that I'd love to make sure I clarify for the

00:06:45.320 listeners. And that has to do with the terminology. And so, let me first describe what I think are a

00:06:51.400 couple of different types of problems and environments that we may be facing. The first

00:06:56.260 is a simple environment or a simple problem. And that's one where there is a clear cause and effect.

00:07:02.420 This is a problem that could be solved with automation very quickly, software, a spreadsheet.

00:07:08.320 Think about how to calculate the interest on a credit card balance. There's a spreadsheet that says,

00:07:12.820 here's your average balance, here's the interest rate, there's your interest payment.

00:07:16.640 Alternatively, you can get to something that I would call complicated. Complicated environments

00:07:21.620 or problems are ones where there is, in fact, a clear cause and effect that it takes an expert to

00:07:28.900 help you identify that because it's layered in multiple different causes and different effects.

00:07:34.940 So, think about the fact that your car didn't start this morning. Maybe you were more,

00:07:39.040 you know, astute on this matter than I would be, but I would likely seek assistance, especially as

00:07:44.200 these cars have become more technologically sophisticated. Is it the starter? Is it the

00:07:47.760 alternator? Is it the ignition? Is it the battery? Is it there? What is the problem? I don't know.

00:07:52.240 There is a problem. It didn't start. It takes an expert mechanic, someone who understands and can

00:07:58.200 disentangle all those causes and effects to get to it. This is the domain, what I call complicated,

00:08:04.200 that experts really thrive within. The minute you cross the threshold from complicated into complex,

00:08:12.020 what we have are emergent phenomenon. This is where causes and effects are not clearly linked

00:08:17.940 or identifiable. And it's because there's just too many moving parts. This is the domain of social

00:08:24.080 dynamics, right? When you have lots of individuals thinking for lots of reasons, different thoughts,

00:08:28.680 and interacting to produce behaviors that emerge. So it's an emergent phenomenon. It's in this domain

00:08:35.520 that our instincts are to lead us towards experts who promise us salvation, who can solve these

00:08:41.680 problems. But these are not problems that are solvable. These are problems that are understandable

00:08:46.740 and that we can try to get our arms around, but there is no solutions. And so when you employ an expert

00:08:52.640 who's skilled at helping us navigate a complicated dynamic in a complex dynamic, what you find is

00:09:00.140 you've brought a man with a hammer to a situation where there may or may not be a nail, but he's

00:09:06.000 going to find that nail. And so that's the domain of complexity where I would suggest it really does

00:09:11.580 make sense to use multiple experts or multiple perspectives to really get your arms around the type

00:09:16.420 of problem you're facing. Well, the example of how an expert, even though they're an expert and

00:09:21.160 they're very knowledgeable about the area, they still can't solve the problem of complexity. I mean,

00:09:25.700 this is your domain, financial advisors. You talk about that, but basically the track record for

00:09:29.980 financial advisors isn't great. Yeah. Look, I think the financial advice community, it's hard to really

00:09:38.900 gauge whether it's great or not, right? Because even the assumption that financial advice has been

00:09:44.860 suboptimal usually is based against some optimization logic of, oh, we want to have the maximum blank.

00:09:53.060 Well, what if instead a true financial advisor understood what their client's needs were and

00:10:00.200 increased the probability of achieving those rather than trying to maximize just some theoretical

00:10:07.420 objective such as, oh, we just want to produce the max return. Well, the max return comes with some risk.

00:10:13.240 So what if instead the person said, I want to make sure I have enough money for my kid's tuition when

00:10:19.160 he goes to college in three years time and it's this much money? Great. Then we're going to increase

00:10:24.140 the probability of achieving that number rather than just objectively try to maximize in this ambiguous

00:10:31.360 way. So it's not clear to me that financial advisors are unproductive or useless. I think they're

00:10:37.500 probably very productive and very useful. The key is really taking the time for financial advisors to

00:10:42.780 step out of their own little silo of maximize returns, maximize returns, and understand client

00:10:49.120 needs. And you're also seeing, I'd say in the past 10 years, you've seen companies pop up promising

00:10:55.760 that they can use artificial intelligence to solve these complex problems. The idea is that you can get

00:11:01.420 these supercomputers thinking about things and they can see all the different possibilities in these

00:11:05.740 emergent properties. But what do you think? Is that actually going to do anything? Or is it just,

00:11:10.140 can that help us solve problems using technology?

00:11:14.420 Yeah, look, technology has forever, as far as I can tell, promised us the salvation into a utopia

00:11:21.780 where everything is knowable and everything is optimizable. The problem is technology, at least so

00:11:27.940 far, has been designed by humans that have limitations and biases and other issues. And those get embodied in

00:11:35.300 the very technologies that are produced by humans. So when you get to the domain of artificial intelligence

00:11:40.780 or machine learning, where they are trying to learn from themselves, the possibilities really could be

00:11:46.780 endless, but they're not anywhere near. The concept of artificial general intelligence, you know, a computer

00:11:53.540 or software that can actually think and understand common sense dynamics, doesn't seem anywhere imminent,

00:12:00.300 to me, at least. So that's one dynamic, I would say. But it also, if you think about even something

00:12:06.000 that's becoming increasingly popular as a topic, like autonomous driving, if a car is driving,

00:12:12.460 let's say the car is about to hit, this is a common problem in the discussion of fairness and some of the

00:12:18.340 decision-making literature. But if the car is going to hit either a person on the right side of the road

00:12:26.240 that has a baby in a carriage and is pushing it down the sidewalk, or two old people on the left

00:12:32.360 side of the road that are walking with their canes down the street, and that's it. It has to choose

00:12:37.460 one of those two. Which one should it hit? I mean, those types of ethical problems that emerge in the

00:12:44.280 software are things that humans have grappled with, but the software doesn't know how to grapple with

00:12:48.960 that. The software is going to deal with it, whatever it's been programmed to do. And so you have these

00:12:54.540 ethical considerations that emerge. I mean, the truth is software embodies values. Algorithms embody

00:13:01.840 the values of the people that design them. And so there you go. That's the problem.

00:13:06.040 That's the problem. All right. So besides increasing information, besides increasing complexity,

00:13:10.920 you said another reason that we're starting to turn more towards experts to help us solve our

00:13:15.420 problems is this desire to optimize everything. What does that look like? And why do you think we're

00:13:20.200 trying to be the best at everything? Yeah. Well, look, I mean, think about,

00:13:24.420 I'll give you a great example that I did mention in the book, which is my wife and I would sit down

00:13:28.700 after a long week and we'll plop ourselves down on the couch and we'll say, all right,

00:13:33.700 let's just watch something. And, you know, maybe she's had a week where she's in the mood at this

00:13:39.540 point for an action movie. Maybe I was thinking more, you know, it was really like a heavy week. I want a

00:13:45.300 comedy. We're convinced because there's, I don't know, a million movies on demand available between

00:13:52.240 Xfinity, Hulu, Netflix. I mean, you go down Apple TV, what have you, Amazon Prime. I mean,

00:13:59.800 there's got to be a movie that can thread that needle perfectly, right? There's got to be.

00:14:04.080 I think so.

00:14:04.580 There's so many movies. Why wouldn't there be? Of course there is. And our mood is perfectly

00:14:10.220 studed to that exact movie. And so, but finding it is a non-trivial task. And the truth is we

00:14:17.960 probably won't. And so what ends up happening is we think because there are so many choices

00:14:23.400 out there in the world that we get effectively paralyzed because we know that an optimum,

00:14:29.840 an optimal perfect decision probably exists, but we can't find it. How do we find that movie?

00:14:36.000 How do I know? I mean, oh my God, you would think I'd have to consult Rotten Tomato. I'd have to

00:14:40.460 consult different movie critics. I'd have to find this. I'd have to find the genres. Look,

00:14:45.100 the stakes are not high enough to do all that, but we're left with this low-grade anxiety.

00:14:49.920 And the result is we're probably going to be unsatisfied because of all that choice.

00:14:55.620 And so rather than sort of empowering us that having all this choice and we can find whatever we want,

00:15:00.740 we end up with this low-grade regret. Ah God, that movie wasn't perfect. There was probably

00:15:05.100 something better. It's this fear of missing out. Fear of missing out on the perfect choice.

00:15:11.440 So we often hear about this FOMO in a lot of walks of life, but the fear of missing out on the perfect

00:15:16.760 choice exists in many domains. And so the result is, well, let me go with the algorithm suggestion.

00:15:23.700 Netflix thinks based on my prior watching that I'll like this. Let me try it, right? Or based on these

00:15:30.140 decisions I've made in the past, the expert believes, my financial advisor thinks that I'm

00:15:34.400 very risk averse. They're not going to put me in Zoom stock because it's volatile, even though it

00:15:39.680 went up. Oh God, it was volatile. What have you. And so the fear of missing out on that perfect decision

00:15:45.880 that is elusively promised constantly by the explosion in choice and opportunities really leaves

00:15:53.660 us with this tendency to run headlong into the arms of experts and technologies.

00:15:59.080 Well, yeah, it seems like in the, it sounds like what you're saying, the technology actually

00:16:01.960 encourages us to think that way because technology, they want, there's data with everything. So you can

00:16:07.000 see popularity, but like the data could be immediately. I mean, I've had instances where I've

00:16:11.240 tried to get whatever I, whatever some company said was the best. Then I get it. I'm like, this wasn't

00:16:15.980 that great. This is the problem. This is FOMO invading all walks of life effectively, right? I mean,

00:16:22.300 think about this, but I went and I got to get a drink at Starbucks and, you know, it's kind of

00:16:26.860 feeling like a coconut milk latte, but they had this picture up there. It says real popular. The

00:16:31.440 app suggested that, you know, dollars off. If I get this other drink, this mocha, something

00:16:36.300 trying to manage my calories. I'm worried about fat. I'm trying to optimize, you know, the caffeine to,

00:16:42.300 I don't know, the caffeine to carb ratio, some weird thing that someone somewhere said is

00:16:46.760 important. And so I get it and yeah, it's okay. But there was a perfection,

00:16:52.300 promise at one point. And by the way, this goes right headlong in conflict with economic thinking.

00:16:59.300 Economic thinking has often said more choice is always better. It can't be worse, right?

00:17:07.000 I can ask you, Brett, do you like an apple or an orange? You say, I like an apple. I say, great.

00:17:10.740 Do you like an apple, an orange, or a pear? Well, now you either like the pear or you can still like

00:17:15.520 the apple, right? The orange is never going to be better. What we find with humans is, is it apple or

00:17:20.960 orange or pear? And then you introduce a banana and they say, I like the, I like the orange.

00:17:26.080 You say, wait, hold on a second. Why did you like the orange? Now you'd like the apple more than the

00:17:30.000 orange. The apple's still there. Now I introduce a banana and now you like the orange. What happened?

00:17:36.540 Well, it turns out choice is confusing and we drown in these sort of decisions. We get paralyzed. I mean,

00:17:42.540 you hear about analysis paralysis, this choice paralysis. There's been wonderful research that shows

00:17:48.280 after a certain point, more options actually paralyze rather than in power. And that's what

00:17:55.640 we're finding. Right. And so that's why we decide to go to Google, just Google, tell me what the best

00:17:59.640 thing is to buy or Netflix, tell me the best show to watch because I don't want to make the choice.

00:18:03.400 Yeah, it's easier. And by the way, in some walks of life, I would tell you,

00:18:07.080 you shouldn't think for yourself. You should just blindly follow what it's, right? When the stakes are low,

00:18:12.340 why do I need to try to optimize the movie I'm going to watch with my wife on a Friday evening or

00:18:17.060 Friday evening, right? Why should I do that? Why not just, it's an hour and a half to two hour

00:18:22.660 commitment. And in fact, if I didn't think of it as something to optimize, but something instead that

00:18:27.580 I tried to satisfy, I'd probably enjoy it better. Right. Okay. But then when the stakes are high,

00:18:33.820 you don't want to just rely on the expert or the technology. That's right. All right. No,

00:18:38.720 that's exactly right. You don't want to rely blindly when the stakes are high. Think of it this way.

00:18:42.620 If you had to worry about a medical decision where a procedure that was somewhat risky,

00:18:48.480 that maybe had some side effects, that balancing act is going to be a little more difficult than

00:18:53.780 one where I'd encourage you to think for yourself. Well, something that I thought was interesting

00:18:57.980 too, you argue in the book is that this information overload, this information complexity, this too

00:19:03.020 many choices is not only affecting lay people, but it's also causing problems for the experts in the

00:19:08.980 technology we rely on. How so? What's going on there? Well, think about the experts, right? They

00:19:14.540 live in silos and they may in fact, because they live in silos, not have an appreciation for where

00:19:21.800 their work is useful or not useful. And so I encourage the experts to also take a step back and see the big

00:19:29.140 picture. You know, one example I've used in the book and I often talk about is imagine if you went to

00:19:35.440 your cardiologist and she says to you, look, you're doing great. Your health is fabulous. However,

00:19:42.960 I'm noticing your cholesterol levels rise a little bit. It's a little concerning. What I really want to

00:19:48.780 do is put you on a statin to lower your cholesterol levels. By the way, don't worry about it. Statins are

00:19:55.360 completely safe and proven to work. I myself as a cardiologist take a statin. Most of my medical

00:20:02.380 school peers are on statins. In fact, every doctor in this practice is taking a statin.

00:20:09.720 We really recommend you take a statin. It works. And so you go ahead and take a statin. Later that

00:20:15.960 year, you come back, you get tested and lo and behold, your cholesterol levels have fallen.

00:20:20.320 Fabulous, right? She did her job. You can claim victory. And we know with good, you know, pretty serious,

00:20:27.120 good research that high levels of blood cholesterol are associated with higher risk of heart attack.

00:20:32.860 And she just lowered your blood level of cholesterol through a statin. Great. So that's a good thing.

00:20:38.600 However, now you walk down the hall and you go see a endocrinologist and he tells you, Brett,

00:20:45.680 you know what? You're doing great. Health is looking good. Except I'm seeing signs of prediabetes.

00:20:51.880 It looks like you're developing insulin resistance. And in fact, I think we're going to have to address

00:20:57.400 this because something's not right. There's a warning here and I'm worried because diabetes comes

00:21:02.840 with an elevated risk of heart attack. And so now we've crossed the silo away from the cardiologist

00:21:09.360 to the endocrinologist and we're seeing the exact opposite impact. Why is that? Because the way a statin

00:21:14.400 works is it interferes with enzymes that impact insulin production, et cetera. And so it interferes with the

00:21:20.820 system. The fact that lower cholesterol is good for you is true, all else equal, but all else wasn't

00:21:27.540 equal. You took a statin, a foreign object that interferes with other things. And so there's an

00:21:31.980 example where crossing silos may result in a different insight than living within a silo.

00:21:37.860 So, you know, I think it's useful for experts to look beyond their own silos as well.

00:21:42.400 We're going to take a quick break for a word from our sponsors.

00:21:44.140 And now back to the show.

00:21:49.960 Well, and besides experts in technology, you've mentioned something else that can cause us to

00:21:54.360 not really think for ourselves, and that's rules or procedures or, you know, sort of the bureaucracy.

00:21:58.960 Any examples of that causing us to be blind to different options?

00:22:03.200 Yeah. Look, I mean, sometimes checklists are useful. They've proven extraordinarily useful in reducing

00:22:07.940 surgical error. They've proven extraordinarily useful in aviation where, you know, pilots will go down a

00:22:14.000 checklist to double check everything, et cetera. It's a means to minimize sort of that complacency that

00:22:21.760 comes in with regular repeated actions. And the complacency sometimes increases the error rate. So

00:22:28.260 use the checklist and you reduce the error rate. However, what happens when we blindly rely on

00:22:35.940 checklists or protocols is we stop thinking. And that's a problem. There's a story in the book

00:22:41.860 where I talk about a checklist that was used to determine whether a patient should be removed off

00:22:46.580 of a blood thinner. And the checklist said, yes, he should be removed off the blood thinner. And so

00:22:52.020 this patient stopped taking blood thinner and later had a stroke. Well, it turns out one item that wasn't

00:22:57.700 in the checklist was family history of strokes wasn't part of the checklist. And so this doctor took

00:23:03.680 him off the blood thinner saying, oh, the checklist thought no reason to stay on the blood thinner.

00:23:08.980 However, this person, his father at that very age had a stroke that he was. And so, you know,

00:23:16.160 if you'd use a little common sense and not relied blindly on the checklist, you might've had a

00:23:21.500 different recommended course of action. So there's an example, again, sorry from the medical, we're

00:23:25.280 sticking with medical examples, but you know, it's also true even within aviation, you know,

00:23:29.500 Captain Sully Sullenberger, famous US air pilot who landed on the Hudson. You know, there was a

00:23:34.500 checklist in the plane for what to do when you lose thrust in both engines. There was a checklist for

00:23:42.400 that. However, that checklist was designed to be followed. If you were at 35,000 feet cruising at 600

00:23:49.380 miles an hour, he was at 3,000 or 4,000 feet, hadn't yet reached an ascent level that allowed him to glide

00:23:56.800 very far. And so he put the checklist aside and he thought for himself, the result was a good outcome.

00:24:03.800 Well, better than it would have been, I guess, is one way of thinking. So yeah, there's a couple

00:24:07.840 examples from checklists.

00:24:09.480 Well, so it sounds like what all these things, experts, technology, checklist, procedures, what

00:24:13.320 they all do, one of the things they do is they direct our focus to a specific area, causing us not to

00:24:20.260 focus on other stuff.

00:24:22.280 That's right. Yep. No, that's exactly right. It's about focus management. In fact, one of the things

00:24:26.780 I often suggest is that we need to be mindful about where we're focusing because the experts

00:24:33.420 in technologies are like spotlights and they're shining a spotlight for us in terms of where to

00:24:39.100 look or what to pay attention to. When in reality, the insight may exist in the shadows. You know, we

00:24:44.740 talked about the cardiologist and cholesterol, but I have to ask, like, why would you care about

00:24:48.660 cholesterol? I mean, do you care about cholesterol, Brett? No. I don't think you should care about

00:24:52.780 cholesterol. In fact, I don't know why I should care about cholesterol. You care about cholesterol

00:24:56.920 because it might impact your heart attack risk. Well, shouldn't you just care about heart attack

00:25:02.480 risk rather than cholesterol? Why are we focused on cholesterol?

00:25:06.800 Well, another example from the medical, because I guess that's an area where it's complex, a lot of

00:25:11.580 information that affects men is the prostate-specific antigen test. It's this idea you could detect

00:25:17.780 prostate cancer really early by taking this test and you think that's a good thing, but it actually

00:25:23.180 ended up causing a bunch of problems. Yeah. So that's a really, it's actually a tragic story,

00:25:28.560 I think, on many levels for lots of men. So Dr. Alblin designed this test. He was a University of

00:25:35.660 Arizona professor. And effectively what happened was this was a test to manage. Originally, I think the

00:25:42.220 intent was to manage people that had been, because of symptoms, identified as having prostate cancer.

00:25:49.100 And so you use the PSA test to see in their blood levels, perhaps how that cancer was progressing and

00:25:55.240 what to do. But the way you found out if a person had prostate cancer was they showed up with symptoms

00:26:02.180 or there was some identifiable physical means to say, okay, there's a problem here.

00:26:07.700 Well, what ends up happening is big business, big pharma, or not pharma, but big medicine,

00:26:13.740 if you will, takes over and they start using this test as a identifier of prostate cancer.

00:26:19.300 Well, it turns out most men will die with prostate cancer, but very few men will die because of prostate

00:26:29.020 cancer. And so it turns out that there's actually, you know, with age, there's a greater preponderance of

00:26:35.000 prostate cancer. So the PSA test gets hijacked. And so there's more people starting to rely on the

00:26:41.560 PSA test as a screening tool rather than a management tool. And so suddenly this becomes

00:26:46.680 the focus. Urologists around the country, around the world start saying, let's get a PSA test score

00:26:51.040 to see whether there's a tendency or an issue of potential prostate cancer. And then they end up

00:26:56.540 looking more. And then when they look more, they find more. And when they find more, they treat more.

00:27:01.960 And the result was at one point, Dr. Ablin, who designed the test, the scientist who came up with

00:27:07.900 it, ended up writing a New York Times op-ed. It was the most read New York Times op-ed that year

00:27:12.840 that said something that was called the great prostate mistake or something like that, where he

00:27:17.900 said, listen, I'm sorry. This test was not designed for use in this way. The result is millions of men

00:27:26.340 have undergone treatments for an issue that may never have bothered them, an issue that may never

00:27:33.520 have actually produced any identifiable impact on their life. And so, you know, there's, in fact,

00:27:40.640 he then had a book-length treatment called the great prostate hoax, where he talked about how,

00:27:46.680 and he starts it off with an apology to men saying, you know, there's been millions of men who are

00:27:51.260 probably incontinent or impotent because of procedures that might have been deemed unnecessary

00:27:56.860 because of over-reliance on this one indicator. Right. And so that's an example, again, like

00:28:02.100 misdirected focus. Like it, yeah, it just, it made you blind to the bigger picture and just

00:28:07.520 made you hyper-focused on one thing. That's right.

00:28:11.060 Well, another area that you talk about, and this is sort of your domain of business and finance,

00:28:15.460 where misdirected focus, where you're, you're siloed and you're just paying attention to specific

00:28:21.300 things can actually hurt businesses in the way they promote people. And this, uh, you talk about

00:28:28.140 the Peter principle. Oh, thanks for asking, Brett. This is one of, I think it's a genuinely comical

00:28:35.100 manifestation of this problem of misdirected focus. Well, it's like, so for those, yeah, for those

00:28:40.120 who aren't familiar, what is the Peter principle and how does misdirected focus lead to the Peter

00:28:43.480 principle? Yeah. So the Peter principle is, so there was this book in the 1960s, I think,

00:28:49.280 written by Lawrence Peters and there was somebody else, but anyway, it's called the Peter principle.

00:28:53.440 And what he found was he went around and was just frustrated by large organizations and bureaucracies.

00:29:00.560 And what he did was he said, well, why are people getting promoted? Why is this person in the job?

00:29:04.640 Why is this person staying in the job? And he did some research and looked into it.

00:29:08.280 And what he found is really at some level, I mean, it caused me to chuckle when I first read it.

00:29:13.480 And then when you think about it, it's quite profound. He said, well, it turns out people

00:29:17.880 get promoted by doing well in their current job. And the result is you keep getting promoted if you

00:29:26.100 do well. Seemingly logical, right? The next question he asks is, when do people stop getting

00:29:32.520 promoted? They stop getting promoted when they're doing poorly in their job. And he calls that,

00:29:38.720 that that person has reached their, quote, level of incompetence, quote. And so the result is

00:29:45.100 eventually over time, an organization is filled with people that reach their level of incompetence

00:29:52.300 and therefore nothing gets done. And so you can laugh about that because you're like, oh my God,

00:29:58.000 obviously if this person's really great at customer service, they're going to get promoted to run the

00:30:01.660 customer service team. Well, that's a different skill, managing people rather than managing customers.

00:30:06.580 And if that person's really good at managing that group of people, they get promoted to managing a

00:30:12.340 bigger, different operation, et cetera, and they'll get migrated up. And so the misdirected focus that I

00:30:18.940 highlight is the Peter Principle suggests that people get promoted by how they're doing in their

00:30:23.800 current job. When in fact, you should really look to promote them based on how they might do in their

00:30:29.920 next job, not the job they're in. You may find an underperformer in your business who's at a

00:30:36.120 particular level who once promoted may excel. Likewise, you can find someone who's doing really

00:30:42.140 well in their current position that if you promote them, they'll really struggle. And so the focus on how

00:30:47.900 someone's doing in their current job to determine whether they will do well in their next job really

00:30:53.660 doesn't actually make a lot of sense. I mean, it's a rewarding mechanism, but it's not a mechanism that

00:30:59.820 actually lines up people with the skills they need for the job they're being asked to do.

00:31:05.160 Gotcha. Okay. So in that case, if you're working in a corporation where you determine promotions,

00:31:10.060 you don't just look at how well they're performing at the job. Look at the bigger picture

00:31:12.920 of that person and see if they would do well where they're at right now or in a position higher.

00:31:18.380 Yeah. Look, yeah. Wayne Gretzky's, I don't actually know if it's Wayne Gretzky or Wayne

00:31:23.200 Gretzky's father. There's been debates on this, but there was a quote that came out of the Gretzky

00:31:27.780 family, which was one should skate to where the puck is going, not to where the puck is, right? So

00:31:35.200 evaluating people by how they're doing in their current role is looking at where the puck is. We want

00:31:41.800 to know where the puck is going. If I promote Brett to this other job, will he do well? That is

00:31:47.480 independent of how he's doing in his current job. All right. So we've talked about the problem.

00:31:51.840 We have all these experts, technology, rules and procedures that direct our attention and sometimes

00:31:56.580 to our detriment. Let's talk about how we can overcome that and be a little bit more self-reliant

00:32:01.740 in the 21st century. And let's talk about that managing focus. So it seems like the first step

00:32:05.860 is just resting control of your focus from experts, technology, and not just completely outsourcing

00:32:12.060 that thinking to them. But how do you do that when you have all these things, these algorithms,

00:32:17.060 these experts and books and TV telling you, here's what you need to do. How do you rest control

00:32:21.460 and start managing your attention for yourself? Yeah, it's hard to do. Let's be honest. So first

00:32:27.220 of all, it takes effort. But let me actually clarify one thing that I want to make sure comes across

00:32:31.720 here. I am by no means suggesting we shouldn't listen to experts. I am not bashing experts. What

00:32:39.040 I'm suggesting is we have for far too long bounced like a ping pong ball between complete deferral to

00:32:47.960 experts, which I think is problematic. That's where we don't think for ourselves and we blindly

00:32:51.920 outsource. But we've also bounced to the other extreme, which is complete dismissal of experts,

00:32:57.380 which I also think is wrong. What we need to do is keep experts in their spot, in their place.

00:33:03.180 We are the main actors. Experts are supporting actors. So we can take their insight. In fact,

00:33:10.360 in the book, I say, keep experts on tap, not on top. For that reason, I think there's a role for

00:33:16.920 experts and we want to rely on them and we want to tap into them and we want to get insight from them

00:33:22.200 and extract value from them without completely blindly outsourcing to them. Now, one exception,

00:33:28.460 in fact, again, in the book, I mention an example of a Stanford University professor, Baba Shiv,

00:33:34.220 who realized that he and his wife had a cancer diagnosis and they decided they were going to

00:33:39.800 take the backseat. They were going to do what the experts told them to do blindly. Now, they realized

00:33:45.760 that it was emotional and so they mindfully decided to give up control. So one, being mindful. And number

00:33:52.880 two, they then spent more time figuring out who they would give up the control to. So they were

00:33:58.020 mindful of who they outsourced to and they were mindful of the very outsourcing act. So I'm okay

00:34:03.380 with people outsourcing, you're thinking. I just want you to do it mindfully and intentionally

00:34:08.360 rather than subconsciously or just reflexively.

00:34:13.020 Gotcha. And so it sounds okay. If you make that decision to outsource your thinking and rely on

00:34:18.220 experts, which you should, I guess one of the things you do, maybe you start asking, what is this person

00:34:22.420 missing that because of their expertise, they might be missing because it's not even in their silo?

00:34:28.540 Bingo. That's exactly right. Ask questions of where the information is relevant and where it might not

00:34:33.540 be relevant or what the insight is based on. So, you know, I know it's hard to ask experts. You feel

00:34:40.320 like there's a status dynamic, et cetera. But when you're interfacing with an expert, I think it's

00:34:44.940 eminently reasonable to ask questions about how that expert came to the conclusion that they've come to,

00:34:51.440 why they're recommending it to you and how it applies to your specific context and your specific

00:34:58.760 problem or objective. So I think that's a very reasonable conversation to have. And an expert

00:35:03.900 should be willing to guide you to understand why they're coming to this conclusion.

00:35:08.960 Right. So that even involves like asking about their incentives. I mean, that could be uncomfortable.

00:35:12.840 It's like, well, do you make money if you tell me to do this thing?

00:35:16.220 Absolutely. You got to know that.

00:35:18.680 It's uncomfortable, but worth doing. You know, there's a quote in the book. I think it's from

00:35:24.280 Warren Buffett, but you know, don't ever ask a barber if you need a haircut.

00:35:28.140 Right.

00:35:28.260 It's sort of the logic. I think that captures it, right? That sort of gets at it.

00:35:33.560 Well, and besides, okay, just being more mindful of when you're ceding control and also being mindful

00:35:39.720 of the experts, their limitations or the technology's limitations. You also say another important thing

00:35:46.640 to be self-reliant in the 21st century is just actually knowing what you're trying to do,

00:35:49.800 like what your goals are.

00:35:51.180 Yeah.

00:35:51.660 And like, it seems like very basic, but how do you think people like,

00:35:54.360 do they just not think about that? Like, why don't you think people think about what their actual

00:35:57.660 goals are when they decide to cede control over to an expert or technology?

00:36:01.240 Well, it's not that you don't understand your goal. It's just that you let your goal be

00:36:04.580 subservient to the expert's objectives, right? So ultimately, you know, think of the cardiologist

00:36:10.220 example. The cardiologist is an expert in heart health. You are worried about your wellness,

00:36:15.480 your longevity, your risk of heart attack is part of that. Ultimately, we can even ask,

00:36:20.220 why do you care about a heart attack? If it doesn't kill you, I mean, yeah, you don't want to have it

00:36:23.440 because there's risks, complications, et cetera. But ultimately, you care about living a life

00:36:28.400 healthily. You want to stay well. And so, you know, your objective really should be driving

00:36:34.520 your interactions with experts. Again, think of yourself as an artist putting together a mosaic

00:36:40.900 and experts have the tiles. There's different tiles, there's different shapes, a different color,

00:36:45.940 different texture. You put them together based on your objectives. So, you know, again,

00:36:51.860 I think of it as the experts are pieces. You know where you want to go with this whole thing.

00:36:57.500 So take what you need from them. It also sounds like too, as you're working with an expert,

00:37:02.940 you have to look at results. And if the results, you're not getting the results you wanted or

00:37:07.240 desired, well, then you got to change course and maybe find another expert or do something else.

00:37:11.900 Yeah. Or interface with them. I mean, look, I'm not suggesting experts are bad. Maybe they don't

00:37:15.120 understand your objectives. Maybe there hasn't been a clarity of communication.

00:37:18.760 Right. That's a good point. A lot of people, he might be working on different assumptions than

00:37:22.640 you are. And so, another tactic you recommend is just, you mentioned this earlier, just triangulate.

00:37:27.920 Instead of just relying on one, you know, get a second or third, sometimes fourth opinion.

00:37:32.260 Yeah. And don't hesitate to cross silos in those opinions that you seek, right? So,

00:37:37.480 you know, I'll give you an example. Well, in fact, we talked about a cardiologist. So when you go

00:37:40.960 to your cardiologist, she tells you to take a statin. Why not ask your endocrinologist what they

00:37:45.200 think about you taking a statin? The obvious assumption is, well, that's not their domain.

00:37:49.880 That's not their silo. That's not their area of expertise. Why would I ask them? Well, because

00:37:53.900 it might interact with them in some way. They may have a unique insight or perspective on this.

00:37:59.680 Oh, actually, Brett, we've seen people who take statins. It turns out they have an elevated risk

00:38:03.140 of diabetes. Whoa, really? I don't want that. Okay. Let me re-engage with the cardiologist with this

00:38:09.580 insight. So part of the triangulation logic is an acceptance and admission that every perspective

00:38:17.180 is biased, limited, and incomplete. So don't just rely on one. And that's really what I mean when I

00:38:24.380 say triangulate, which is, you know, in the domain of financial bubbles where I've spent some time

00:38:28.400 thinking and writing, you know, an economic perspective leads you to one insight, but a

00:38:32.960 psychological perspective may lead you to another. And you add into it a political perspective,

00:38:37.720 a credit perspective, a herd behavior, or even, you know, what you find is that, oh,

00:38:43.460 cultural perspective, you get a different view than you would through any one particular lens.

00:38:50.700 And it reminds me of this, I don't know if it's a parable, but there's an often quoted story of the

00:38:55.320 six blind men that stumble upon a elephant, right? So the one man, you know, grabs the leg and he says,

00:39:01.800 oh, this is a tree trunk. It's definitely a tree that we've stumbled upon. Another one grabs the

00:39:07.100 tail and says, whoa, hold on a second. What we have here is a snake. And it's only through the

00:39:13.420 integration of multiple perspectives that the group would be able to determine that they are in fact

00:39:19.120 encountering an elephant. And it's the same way with a large portion of the uncertainty we face in

00:39:24.600 our lives, whether it's in medical, financial, or other domains, is that it really requires integration

00:39:30.800 of multiple perspectives to get our arms around what we're facing, the problems, and even the

00:39:35.480 potential solutions. Well, it sounds like too, besides getting a breadth of opinions from different

00:39:40.200 experts, you know, being self-reliant in the 21st century and knowing how to handle expert knowledge

00:39:44.680 requires the person, you know, you yourself to develop a breadth of knowledge. Like we read widely,

00:39:50.280 have multiple perspectives. Yeah, look, I think breadth is really important at the individual level

00:39:55.760 so that you can understand the limitations and boundaries of the silos in which experts and

00:40:01.660 specialists live. And so reading widely, yes, is important, but it's also just developing an

00:40:07.020 awareness. And these are simple things that can be done to give you that awareness. You know, let's

00:40:13.840 just talk about reading information and the news, for instance, right? I mean, a lot of people will

00:40:18.240 now, because of technology, tunnel in based on existing, you know, searches or filters or alerts.

00:40:27.420 They'll be told, oh, there's something you're in the, uh, I don't know, you're in the aerospace

00:40:31.260 industry. Great. Here's this 737 max problem. And so you get news on that, your alerts come in every

00:40:36.940 day and you get your, your industry newsletter and it comes to you and you read it. Whereas if you took

00:40:43.500 a physical newspaper or magazine and you flipped through it, you will be exposing yourself to different

00:40:51.020 ideas in different domains that may be adjacent, et cetera. And you'll just be more aware,

00:40:56.060 right? I mean, if you think about what's happening in business, reading the wall street journal,

00:41:00.640 physical edition, rather than the algorithmically influenced alert driven online version, you know,

00:41:08.460 I think there's some value in that and, and, and exposing you to breath. And I consistently will

00:41:13.260 read, for instance, the economist magazine cover to cover in physical form. And I do that because

00:41:19.280 just even flipping pages, even if it's not interesting or not a topic, I have real depth of

00:41:25.760 interest in, I may, I may get some value out of seeing the headline and even reading the first

00:41:31.420 paragraph of it. And it's very quick, but it gives me an awareness and a breadth of, uh, of exposure

00:41:37.100 that I wouldn't get if I just said, all right, I want to know about us China relations. Let me just

00:41:40.980 read about that. Well, Vikram, this has been a great conversation. Where can people go to learn

00:41:44.880 more about the book and your work? Sure. I think my website's probably the best spot,

00:41:49.080 which is just www.mansharmani.com and that's M-A-N-S-H-A-R-A-M-A-N-I or on, I'm on LinkedIn and

00:41:59.060 Twitter as well. And you can find me there. Fantastic. Well, Vikram, thanks so much time.

00:42:02.580 It's been a pleasure. Thanks, Brett. I've enjoyed the conversation. My guest here is Dr. Vikram

00:42:06.460 Mansharmani. He's the author of the book, Think for Yourself. It's available on amazon.com and bookstores

00:42:10.620 everywhere. Check out our show notes at aom.is slash think for yourself where you can find links to

00:42:14.360 resources. We delve deeper into this topic. Well, that wraps up another edition of the

00:42:25.160 AOM podcast. Check out our website at artofmanliness.com where you find our podcast

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The Art of Manliness - October 05, 2020

#649： Thinking for Yourself in an Age of Outsourced Expertise

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