Making Sense - Sam Harris - #155 — Mental Models

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00:04:16.860 by UCLA's Mindful Awareness Research Center.

00:04:21.060 And now for today's podcast.

00:04:23.480 Today I'm speaking with Shane Parrish.

00:04:26.440 Shane is a blogger and podcaster.

00:04:29.660 His website is farnamstreet at fs.blog, and his podcast is The Knowledge Project.

00:04:38.660 Many of you know him, I believe.

00:04:40.260 There was recently a profile in the New York Times about him that brought him into greater

00:04:44.740 prominence.

00:04:45.980 He has a background in computer science, and he worked for many years in the Canadian equivalent

00:04:53.120 of the NSA.

00:04:54.920 In fact, he briefly worked with the NSA as well.

00:04:58.400 But now he is a full-time digital media person, and he spent a lot of time thinking about thinking.

00:05:05.180 And we talk a lot about what he calls mental models.

00:05:08.340 This conversation has a lot in common with the conversation I had with Danny Kahneman about

00:05:13.200 reasoning under uncertainty.

00:05:15.020 But I think you'll find it very different as well.

00:05:17.720 Anyway, without further delay, I bring you Shane Parrish.

00:05:21.000 I'm here with Shane Parrish.

00:05:28.960 Shane, thanks for coming on the podcast.

00:05:30.380 Happy to be here.

00:05:31.360 So we're doing this in your hotel lobby, hence the ambient city vibe.

00:05:36.980 This is a non-studio sound, but it's an experiment.

00:05:39.900 If people can hear us, it has worked.

00:05:41.820 I think we probably share a significant audience, and many people will know who you are.

00:05:45.800 But you run the Farnham Street blog, and you have your own podcast, The Knowledge Project.

00:05:53.000 We've interviewed some of the same people, so we have many interests in common.

00:05:57.760 But there was a great New York Times profile on you, which I think brought you to the attention

00:06:02.000 of many people.

00:06:02.540 So let's just jump into a kind of potted history of your background, because you came into this

00:06:10.040 from an interesting angle.

00:06:13.220 You started in, was it cybersecurity specifically, is your background?

00:06:18.920 Is it computer science and cybersecurity?

00:06:21.020 Yeah.

00:06:21.340 So I started work August 28, 2001 for an intelligence agency.

00:06:27.520 And then September 11th happened two weeks later.

00:06:30.400 And I worked in, I guess you could say, cybersecurity in one way or another for, I guess, 15 years.

00:06:38.100 Is that something you can talk about, or are you bound by laws of Canadian espionage that

00:06:42.480 you will make that part of a very short conversation?

00:06:46.760 We can't talk about it too much in terms of specifics.

00:06:49.840 I think we can talk about general things around cybersecurity or maybe privacy issues.

00:06:55.080 But yeah, it's not something I think.

00:06:57.280 There's a lot of stuff out there now with Snowden and everything.

00:06:59.940 So I think people have a fairly good insight into what goes on inside intelligence agencies.

00:07:06.300 So you were in computer science and got into cybersecurity right like two weeks before September

00:07:13.480 11th.

00:07:14.000 So the landscape completely changed.

00:07:16.920 Oh, yeah.

00:07:17.460 Your job description completely changed.

00:07:19.200 Well, we didn't even have a sign on the building as of August 28th.

00:07:22.720 And by Christmas that year, we actually had a sign we existed.

00:07:25.500 But we've existed since the 40s.

00:07:27.300 So just to contextualize for people, I worked for the Canadian version of the NSA.

00:07:32.360 Right.

00:07:32.860 And it just it was a really amazing time to be working there.

00:07:37.000 I mean, it was unfortunate the events that sort of led to our increased visibility and

00:07:43.280 band-aids.

00:07:44.080 But with that said, it was we went from, I don't know, 500 people to 2000 or so when I

00:07:49.840 left.

00:07:50.460 Right.

00:07:50.680 A lot of growth, a lot of expectations.

00:07:53.300 You know, I ended up doing a job that I wasn't really hired to do, but I love doing.

00:07:57.660 And it was a good way to sort of give back to Canada and the country that I was born in.

00:08:02.840 My parents were in the military, so we live coast to coast.

00:08:05.620 I ended up working in the States for a little bit at NSA for a short time.

00:08:10.160 And then most of my other time has been in Ottawa.

00:08:12.960 Right.

00:08:14.120 So what's the connection to Wall Street?

00:08:18.080 Because this could have been an artifact of what the New York Times did to you, but

00:08:21.240 there seemed to be a real emphasis on how popular your blog and podcast are among the financial

00:08:26.880 types.

00:08:27.600 It's really strange.

00:08:29.160 We have three main audiences for our sort of blog and podcast, which is Wall Street,

00:08:34.500 Silicon Valley and professional sports.

00:08:36.540 And the way that it started was I took some time to go back to school, I think around 2008,

00:08:42.660 2009 to do an MBA and quickly realized that I wasn't going to learn what I was trying to

00:08:49.000 learn from my MBA.

00:08:49.920 I wanted to learn how to make better decisions because I was doing operations and I was making

00:08:54.740 decisions that impacted people and countries.

00:08:57.160 And I felt like there was an obligation on my part to get better at making decisions.

00:09:03.280 And it's not that there's no sort of like skill that is making decisions better.

00:09:08.300 It's a whole bunch of sub skills that you have to learn and apply.

00:09:12.700 So I went back to school to try to get better at some of that stuff and quickly realized that

00:09:17.080 the MBA wasn't going to teach me what I needed to know.

00:09:19.460 And so I started a website called 68131.blogger.com, I think.

00:09:25.140 And that's the zip code for Berkshire Hathaway.

00:09:27.140 And the reason that I did that was the site was an homage to Charlie Munger and Warren Buffett,

00:09:31.840 who were actually giving me things that I could think about and put into practice about

00:09:35.920 how to see the world differently, how to make better decisions.

00:09:39.820 And I started just journaling for me.

00:09:42.100 And the reason that we used 68131 was because I didn't think anybody would type it in at the

00:09:46.820 time.

00:09:47.100 It wasn't meant for anybody else's consumption.

00:09:49.140 It's more like a personal online notepad for my own edification and connecting ideas.

00:09:55.620 And then it just, I don't know, it took off from there.

00:09:58.020 It wasn't anything conscious, like it was not, we didn't try to reach Wall Street or

00:10:02.120 it was anonymous too.

00:10:03.780 It wasn't even like, it didn't have my name on it because I was working for an intelligence

00:10:06.440 agency and they wouldn't sort of let me put my name on it.

00:10:09.660 You took time off of doing intelligence to get an MBA with the intention of going back

00:10:15.180 to intelligence, being better equipped to make decisions, or were you getting out of intelligence

00:10:19.040 at that point?

00:10:19.520 I did full-time MBA studies and full-time work at the same time.

00:10:23.460 Oh, interesting.

00:10:23.900 So I switched jobs to take a less demanding job in the organization while I did that.

00:10:28.720 And the intent was always to go back and sort of like see what options were available.

00:10:33.820 I went back and went into management.

00:10:36.600 How do you view the current panic around online privacy and just what is happening to us based

00:10:43.600 on our integration with the internet?

00:10:44.960 I can imagine you have a few thoughts on what we are doing with our data, what's being done

00:10:50.000 with our data, how cavalier we are with these lives of transparency we're leading now.

00:10:55.360 I think it's something that we need to be aware of and make conscious choices around.

00:10:59.940 And I don't think there's a historical precedent where we can look back and sort of use that

00:11:05.200 as a guide because the environment's changing so quickly.

00:11:07.720 I think one of the big things that are going to dominate over the next 10 to 20 years is

00:11:13.120 online privacy and sort of the question about whether we're going to let foreign companies

00:11:20.000 control parts of our infrastructure.

00:11:22.320 And I think those questions are, they're not necessarily resolvable.

00:11:26.160 We have individual choices about what we do.

00:11:28.360 I mean, you don't want to use Google.

00:11:29.820 You can use DuckDuckGo or, but you also want these valuable services that are being provided.

00:11:36.000 I think we need to come to some sort of understanding about what that information

00:11:41.660 that we're giving away is in a transparent way.

00:11:46.240 I also think that there's an interesting, if you think about it, one of the questions that

00:11:53.460 I think is relevant is, do these companies get a cumulative advantage from having this

00:11:58.400 information that prevents competition?

00:12:00.180 And so is Google better at search because we use it?

00:12:04.660 And the more we use it, the better they get at search, which means that it's much harder

00:12:08.920 for competition to start.

00:12:10.640 Right.

00:12:11.060 As these algorithms get better and they're trained with more and more data, it becomes

00:12:15.740 harder and harder for the person in the garage to compete.

00:12:19.220 And then you end up having to compete with capital and not necessarily technology.

00:12:24.600 And I think that changes sort of the landscape of what we're seeing in the market today.

00:12:31.080 So I think maybe it's a case where history has always been the same, where big companies

00:12:36.400 and incumbents tend to get bigger.

00:12:39.540 But I think that it's a little bit different this time in the sense that these companies

00:12:43.920 make a lot of money.

00:12:44.920 They're not necessarily bound by employees.

00:12:47.160 They have a huge influence over regulatory frameworks.

00:12:51.520 The harder or more regulated they become, almost the more barriers to entry you'll get for

00:12:56.520 competitors as well.

00:12:58.400 Where do you come down on the question of having a foreign company build critical infrastructure?

00:13:06.580 I think that's a great question, right?

00:13:08.660 And I think one of the ways that you can think through that question is, if we were to go back

00:13:15.220 to World War II or something, to what extent would we want another country building our tanks?

00:13:19.900 To what extent do we want to be dependent on another?

00:13:23.440 Tanks that could be turned off remotely.

00:13:25.240 Right.

00:13:25.680 So to what extent do we want to be dependent on another country?

00:13:30.800 Even if we have good relations right now, I think one of the questions we ask is, are

00:13:34.800 we always going to have good relations with these countries?

00:13:39.080 What could go wrong?

00:13:40.860 Right?

00:13:41.120 And we can't, again, looking backwards, it's hard to find historical precedents where we can

00:13:46.380 clearly say what could happen, but I think that the variability in outcomes is high and

00:13:54.760 we're focused maybe on short-term optimization over long-term survival.

00:14:01.600 This is one of these places where it feels like the market fails us because it's just, in the

00:14:09.420 abstract, you can understand why you would want a free market for more or less everything,

00:14:15.560 but it's just so easy to see what could go wrong here.

00:14:18.660 If you have China or some quasi-hostile foreign power, or at least a foreign power that is probably 0.99

00:14:27.320 best viewed as a competitor, and it's very easy to see how we could be really in an open

00:14:33.500 state of war at some point in the future, there's no other way to look at it.

00:14:37.460 If they were going to put something malicious into the system, they would have the power to

00:14:41.700 turn the lights up.

00:14:42.780 And it doesn't have to be war in a physical sense.

00:14:44.800 It could be trade war, economic war.

00:14:46.820 I mean, there's lots of different sort of...

00:14:48.640 Stealing IP, which we know they do with abandons.

00:14:51.440 And so one of the ways that we think to address this, and I'm speaking of we as people, not

00:14:56.680 we as my intelligence background, is, okay, well, we'll set up a lab, and we'll review

00:15:01.460 your source code, and then we'll verify that it compiles in the checksums, and then we'll

00:15:07.240 deploy it into our infrastructure as a means to sort of reduce the risk.

00:15:11.900 And I think that there's problems inherent with that, one of which is logic errors and

00:15:16.240 computer code are extremely hard to pick up on.

00:15:19.060 But the one that stands out a little bit more to me would be, what if there was a zero

00:15:25.560 day found, and a zero day, for people who don't know, is a vulnerability that's not

00:15:29.320 patched, that becomes available, that's found in the code of this infrastructure.

00:15:35.120 So the phrase zero day means you have zero days to fix this.

00:15:38.820 It's already...

00:15:39.260 Right.

00:15:39.800 There's nothing you can really do other than unplug your system to prevent it.

00:15:44.260 And so they issue a patch, and does that patch go through this long process of code

00:15:48.620 review, or does it get deployed right away?

00:15:50.960 And you can quickly see circumstances where you would be forced into deploying something,

00:15:56.120 even under this regime of labs and stuff, where you would end up with stuff that you

00:16:02.120 would review it later.

00:16:03.260 And at that point, it might be too late.

00:16:05.140 And that's not to say that any nation would do that.

00:16:08.980 It's, do you want to be put in a position where you have to think about that?

00:16:11.860 Right.

00:16:12.660 Right.

00:16:13.840 So back to finance.

00:16:16.360 It sounds like you were inspired by Berkshire Hathaway, by Warren Buffett and Charlie Munger.

00:16:23.720 Do you have a connection to those guys?

00:16:25.180 Have you met those guys?

00:16:26.300 Or is it just, you're just a fan based on reading their stuff?

00:16:28.500 No, just a fan.

00:16:29.820 I mean, they're people who've influenced my thinking a lot.

00:16:34.180 The website, Farnham Street, is named after the street in Omaha where they have their headquarters

00:16:38.880 and Buffett has his house.

00:16:40.940 And I think it's just interesting to me when I was doing my MBA and I was sort of thinking

00:16:44.640 about this, it's, you sort of learn the, you had Daniel Kahneman on recently.

00:16:52.060 Yeah.

00:16:52.300 So you learn these cognitive biases that are great at explaining why we make mistakes.

00:16:58.100 And you have sort of Michael Porter and his five forces theory of business competition.

00:17:04.120 And I found it really interesting that these two guys in Omaha, Nebraska, or I guess one's

00:17:09.760 in Pasadena, Charlie Munger is in Pasadena, California, but these two guys took that work

00:17:14.760 and they made it practical and useful and used it to make better decisions in the real

00:17:20.380 world over a wide variety of companies and businesses.

00:17:24.560 And I thought it was really interesting.

00:17:26.080 And that's how I really got interested in them and their thinking.

00:17:29.500 Well, it was interesting that that conversation with Danny at one point, so for those who aren't

00:17:35.320 aware, Daniel Kahneman is one of the fathers of what has become behavioral economics, but

00:17:41.080 decision theory, prospect theory was part of that.

00:17:45.920 The work he did with Amos Tversky, for which Danny won the Nobel Prize in economics, revealed

00:17:53.260 how bad we are at reasoning through various decisions.

00:17:56.920 We have heuristics where we make certain decisions under uncertainty, and many of these heuristics

00:18:04.220 are bad ones.

00:18:05.640 They're not always bad, but they're often bad.

00:18:07.920 And one thing that surprised me in my conversation with Danny is, I mean, he's the godfather of

00:18:12.860 this way of debugging human reason.

00:18:16.820 And yet, when asked how much he's internalized this, how much better he is at not falling prey

00:18:23.340 to bad intuitions or making bad decisions or decisions that will, in hindsight, prove to

00:18:29.640 be bad.

00:18:30.640 He claimed more or less to be as bad at this as anyone else, or that all of his knowledge

00:18:36.540 hasn't really paid dividends in his practical reasoning.

00:18:41.400 But I get the sense that you're not quite in that same boat.

00:18:45.060 How do you view yourself as a decision-maker based on everything you've thought about and

00:18:49.320 studied?

00:18:49.980 I think it's really interesting that he said that, and I was going to bring that up, that

00:18:53.800 he basically said, I've studied this my whole life, and I feel like I'm no better at avoiding

00:18:58.600 these things.

00:18:59.820 And I think what that means is cognitive biases are really great retrospectively at explaining

00:19:05.540 how we go astray.

00:19:06.680 And they're not so great before in terms of avoiding maybe the pitfalls of those things.

00:19:13.400 And the way that we typically sort of, or the way that I deal with people and how they

00:19:19.520 try to address it is they create a checklist of, oh, I'm going to write down overconfident.

00:19:24.120 I'm going to write down, you know, sample size bias.

00:19:26.420 And then the problem with that is the more intelligent you are, the better the story you're going to

00:19:31.200 tell yourself about why that doesn't apply in this particular situation.

00:19:35.040 It's almost like you've made your decision and then you're rationalizing it, but you're

00:19:38.620 going through this checklist, so you're going to create overconfidence in terms of your decision

00:19:43.200 and the range of outcomes.

00:19:44.840 This is a point that Jonathan Haidt and Michael Shermer and other connoisseurs of faulty reasoning

00:19:51.620 have made.

00:19:52.700 Haidt puts it this way, that we reason rather often more like lawyers than like people who

00:19:58.980 are actually trying to get at the truth, where we're doing some internal PR, trying to convince

00:20:04.660 ourselves and others why our gut intuitions actually make sense.

00:20:09.340 And that's, and the problem is the smarter you are, the better you are at doing that.

00:20:14.200 And on some level, the better you are at fooling yourself.

00:20:17.560 Yeah.

00:20:17.800 It's egos over outcomes, right?

00:20:19.620 We're trying to protect our ego and it's not a conscious thing.

00:20:23.040 We're not sort of like meta thinking about protecting our ego.

00:20:26.100 We're just unconsciously trying to protect our view of the world and our interpretation of

00:20:31.200 the world is being correct.

00:20:33.080 And we're willing to take a less optimal outcome in part because we can excuse it away after.

00:20:39.400 Like who could have seen that happen?

00:20:41.320 And, you know, it becomes really interesting when you start thinking about what are the

00:20:45.260 things that I can do in foresight to make better decisions?

00:20:48.760 One of which we sort of alluded to this earlier, like there is no meta decision-making skill

00:20:54.280 that you just learn.

00:20:55.460 There's no class on decision-making.

00:20:57.580 There's a subset of skills that apply in a particular situation and tools.

00:21:01.960 And those are the things that we want to learn, right?

00:21:04.960 Just as there's no meta skill.

00:21:07.300 I think it was Herbert Simon who said there's no meta skill of sort of like problem solver.

00:21:12.160 And what there is, is there's people who bring particular skills that are relevant and then

00:21:17.020 they deploy that schema to a particular problem and they can see things and chunk things in

00:21:21.520 a way that other people can't see or chunk and make better decisions based on that.

00:21:26.800 And that's only relevant if the environment hasn't changed from where they've honed their

00:21:30.620 expertise or they've acquired that sort of like mental models, if you will, of like how

00:21:36.120 the world works and the variables that interact.

00:21:38.440 And I think one of the interesting things that my sort of study of Buffett and Munger has picked

00:21:44.200 up on is they've deployed this and they've made a lot of sort of money in the process.

00:21:48.820 But one of the things that they've done is they've stayed away from a lot of companies

00:21:52.480 that are highly variable.

00:21:53.920 They're more predictable.

00:21:55.360 And I think one of the reasons they do that is that gives them a better lens.

00:21:59.020 So my knowledge becomes cumulative instead of like having to reacquire it all the time.

00:22:03.220 If I'm trying to understand the technology behind Google, well, that's changing every day.

00:22:07.240 But if I'm trying to understand the technology behind a dry cleaner, the dry cleaner or Burlington

00:22:12.620 Northern Railway, it's changing a lot slower.

00:22:15.120 So my knowledge as I'm learning becomes additive and cumulative.

00:22:19.320 And so I think in those cases, your schema, your mental schema is more likely to be correct.

00:22:25.040 Right.

00:22:25.420 So what do you do differently in your personal life or in your professional life as a result

00:22:31.720 of all the, all the study you've done about decision-making?

00:22:35.260 Well, one thing that I do that I don't think a lot of people do is I rarely make a decision

00:22:42.080 on the spot.

00:22:43.200 I rarely feel the need to sort of like sit down and decide something to demonstrate to

00:22:47.540 other people that I'm in control or that I'm a decision maker.

00:22:52.060 I'll often take 20 minutes or 30 minutes and go for a walk and actually just try to think

00:22:57.280 through the problem and think around it.

00:22:59.280 And the way that I conceptualize this in my mind is like you have a problem or situation

00:23:03.840 and you just want to walk around it from a three-dimensional point of view.

00:23:07.260 What does that problem look like to you?

00:23:08.880 What does it look like through different lenses of the world?

00:23:11.080 And what does it look like to other people?

00:23:13.160 And how is it likely to impact them?

00:23:15.280 Can you think of an example of a decision where you would, this is one thing Danny Kahneman

00:23:20.560 said, is that if he's better at anything now, it's that he's more alert to the situations

00:23:26.540 where more care is needed.

00:23:29.720 He's more likely to make an error and perhaps can take a little more time.

00:23:34.780 Where have you applied this?

00:23:36.680 Well, we were talking about sort of allowing companies in your foreign infrastructure.

00:23:41.760 That would be an example of where you can think through the problem from different lenses,

00:23:45.980 right?

00:23:46.180 The immediate sort of response is, oh, it's cheaper.

00:23:50.300 They're good.

00:23:51.160 They're friendly with us.

00:23:52.240 And then you start, the longer you rag on that problem, the longer you work through it,

00:23:58.100 the more implications you can see as to the outside.

00:24:01.020 But you can also think about it in terms of, one of the ways that I think about this is

00:24:06.640 like, how do I want to live my life?

00:24:08.240 A lot of life is sort of optimized for financial maximization.

00:24:13.820 But I don't agree with that, right?

00:24:15.760 I think that it's actually good to have a lot of margin of safety in terms of your financial

00:24:20.600 position, because things can change.

00:24:22.600 Interest rates aren't always going to be there.

00:24:25.580 I mean, I don't know.

00:24:26.320 But historically, if you want to look out into the future, we could have a situation where

00:24:30.800 we have 10% or 20% interest rates again.

00:24:33.600 I don't want to go back to zero.

00:24:35.200 So when I'm making decisions on finances, it's not necessarily just optimizing the short

00:24:40.000 term.

00:24:40.560 It's optimizing over a wide variety of outcomes.

00:24:43.680 And I think when you start to take time to think about decisions, you don't necessarily

00:24:47.920 need to have more cognitive horsepower than other people to make better decisions.

00:24:52.640 You just have to think through a wider variety of situations and circumstances.

00:24:56.280 It's almost like you're doing a Monte Carlo simulation in your head, where you're just

00:25:00.040 thinking about what are the extent of the possible outcomes, where am I likely to end up on a

00:25:06.780 probabilistic basis, and are there outcomes that are unacceptable to me, in which case

00:25:11.420 I want to avoid those outcomes and invert the problem.

00:25:15.160 And then if you can avoid all the bad outcomes, you're likely to end up with good problems or

00:25:19.700 good outcomes.

00:25:20.280 So maybe we should just run through some of your mental models, because your blog, for

00:25:24.460 those who haven't seen it, is just an absolute arsenal of short essays on what you and others

00:25:35.100 have called mental models.

00:25:36.580 And these are both explicitly relevant to decision making of the sorts that Danny Kahneman has

00:25:43.200 spoken about, but also just ideas and memes that you think everyone should have in their

00:25:48.060 cognitive toolkit, whether they relate to biology or finance or probability or just many topics.

00:25:54.580 So I've listed a few here that we could touch.

00:25:57.660 The map is not the territory.

00:25:59.860 The best example of that is online dating, right?

00:26:03.040 So you get a profile of a person that is the map, and then you meet the person, and they're

00:26:09.220 often two completely different things.

00:26:12.480 And we use maps all the time, right?

00:26:14.360 We use maps in businesses like strategic plans.

00:26:17.160 We use balance sheets, income statements, or maps to what's happening in the business.

00:26:22.640 They're an abstraction of it, but they don't represent every nuance and detail in the business.

00:26:28.320 And we need maps to operate, because our brains can't handle that amount of details.

00:26:31.960 We have to have a map, and we can't have a map with perfect fidelity of the thing that

00:26:37.280 it's representing.

00:26:38.720 But territories change, and if the map becomes the goal in and of itself, you lose track of

00:26:44.220 what's actually going on in the territory.

00:26:46.160 So when I say online dating is the best way to conceptually, it's the quickest way to conceptually

00:26:50.600 recognize this, right?

00:26:51.780 Where you have a profile, a person is presenting a view of themselves.

00:26:55.320 It could be a tailored view.

00:26:56.960 It's definitely a curated view.

00:26:58.660 And then you go meet them, and you talk with them, and they're nothing like their profile.

00:27:01.960 Or their interests don't line up with their profile.

00:27:04.380 So you base your decision to meet them on a map, and then when you sort of met them,

00:27:08.180 you're dealing with the territory, and it's a different proposition.

00:27:11.200 And I think that we just need to be aware of when we're dealing with a map, and if you're

00:27:16.100 running a business or a team, you want to be touching the territory, right?

00:27:19.380 You want to have a feel for what's going on.

00:27:21.660 Are things changing?

00:27:23.260 How is the sort of morale of the team?

00:27:26.500 And Ron would be another example of sort of like a map territory problem before they

00:27:30.760 went bankrupt.

00:27:31.600 Everybody was reading the map, and the map was saying...

00:27:35.040 Well, they were lying about the map.

00:27:36.160 The map was lying to you.

00:27:37.300 But it is a map.

00:27:38.400 That's the thing, right?

00:27:39.260 So the maps can deceive you, and they can lie to you.

00:27:41.780 And your job, to the extent that you're an investor, is to sort of like understand the

00:27:46.960 territory and understand what's going on at a different level.

00:27:51.400 Yeah.

00:27:51.580 I ran into this recently with somebody was urging me to make a few business projections.

00:27:59.580 This is now a map of the future where, you know, like growth targets with respect to a

00:28:05.440 business, and maybe there's some context where this makes sense for people to do, but it just

00:28:11.760 seems so obviously just made up, right?

00:28:14.580 And I just was thinking of what are the consequences of making this up?

00:28:18.840 So you posit whatever it is, you know, 20% growth over some period of time, and that is

00:28:24.840 being put forward as some criterion of success, and yet you don't know, you don't in fact know

00:28:30.180 what's possible, right?

00:28:31.140 So it made no sense to me to be anchored to that number.

00:28:35.400 It made no sense to imagine that we should be happy with that number or depressed not

00:28:42.080 to have reached it, because it's just plucked out of thin air.

00:28:45.240 If you could have 10x something, why would you be happy with 5x?

00:28:49.920 And if 5xing something is in fact impossible, why would you be disappointed with 4x, right?

00:28:56.560 So it's like all of this is made, you're basically creating a psychological experiment for yourself

00:29:00.560 where you're either going to feel good or bad based on this confabulation that you did

00:29:05.920 some months prior.

00:29:07.540 Maybe there's more to it than I understand, but it just seemed like a crazy use of intelligence.

00:29:12.180 On a one-off basis, projections are sort of, as you said, they're dangerous, right?

00:29:17.180 So you can also start working towards the projection and not do the obvious best thing to do because

00:29:23.220 you want to hit your projection.

00:29:24.460 And then on a recurring basis where you work for an organization or a body or entity that

00:29:30.940 sort of like is consistently making projections, there's very few of those organizations go

00:29:36.440 back and calibrate the individuals making those projections.

00:29:40.180 I mean, we used to have people who would make projections in a very sort of rote fashion.

00:29:46.200 They knew which projections would get accepted and they also knew that there was no consequences 0.99

00:29:50.300 to sort of like pulling those projections out of their ass. 0.97

00:29:53.640 And so if there are no consequences and you're not sort of held to account for your projections, 0.98

00:29:57.980 you also have no way to calibrate the person making the projections.

00:30:02.020 Is this person more accurate than another person at these projections?

00:30:05.980 And then an interesting question would be, what makes them more accurate than other people?

00:30:10.220 And can we use that information to make better decisions?

00:30:12.920 And it's also, you're aiming at an arbitrary target, right?

00:30:17.380 So if the projection is 20% growth and that's what's going to satisfy you because you put

00:30:22.880 that target on the wall, my question is, why not just do the best things you should be

00:30:29.700 doing for, in this case, we're talking about a business, do those best things and see what

00:30:35.360 happens, right?

00:30:36.100 So like, why aim at an arbitrary target that doesn't take into account the higher level

00:30:42.400 thinking of just what are the best things you should be doing for this business?

00:30:45.600 We don't make projections on our happiness, right?

00:30:48.460 It's not going to be like, I'm going to be 15% more happy next year.

00:30:52.000 We do it with finances and numbers because it tends to be a little easier, but I think it

00:30:56.720 causes a lot more harm.

00:30:59.240 Okay.

00:30:59.540 Another mental model here.

00:31:01.380 First principles thinking.

00:31:02.500 Yeah, I mean, Elon Musk is sort of like the, the recent example of that, but it's breaking

00:31:09.660 things down.

00:31:10.300 And one of the things that the intelligence agency that we had to do a lot of was solve

00:31:14.280 problems that are sort of like ungoogleable where people haven't really solved them before

00:31:18.400 or dealt with that particular problem.

00:31:20.720 And you get constrained into thinking about things through your particular lens.

00:31:25.440 So your discipline, if you went through computer science or engineering or arts or HR, and we

00:31:31.160 were so fortunate to have a wide variety of people there, but one of the things that sort

00:31:35.600 of got us out of what we had been done, the other constraint is what you've done before,

00:31:40.600 right?

00:31:40.860 So you're, you're beholden to improve upon what already exists versus, I wouldn't say

00:31:46.800 reinvent the wheel, but rethink the problem.

00:31:49.660 Right.

00:31:49.780 It's like a legacy code for the mind.

00:31:52.080 Right.

00:31:52.320 So you bring all this baggage with you, but if you actually stop and pause a bit, the problem

00:31:56.880 for a second and think about, well, what are the actual physical constraints of the world?

00:32:01.620 What are the building blocks that I'm dealing with?

00:32:03.480 What are the limitations, like the actual limitations, not what exists today?

00:32:08.120 And then you can sort of rethink the problem in terms of how you want to solve it.

00:32:12.760 And you at least know what's possible.

00:32:14.760 It might be more expensive.

00:32:15.700 It might be cost prohibitive.

00:32:17.760 So the organization can't do it, but it sort of like gets you into this, out of this incremental

00:32:23.580 improvement state and more seeing the problem more fundamentally.

00:32:27.040 And I think that's where we see a lot of disruption in the world is, you know, I think it was Peter

00:32:31.400 Thiel who had the concept of zero to one.

00:32:34.120 And if you think of innovation as possibly having two types of different innovation, one being

00:32:39.260 incremental improvement and one being sort of like a fundamental change.

00:32:42.940 I think the fundamental change is coming when we tend to think through problems from a 0.99

00:32:47.680 first principle basis and take a different approach to them within the boundaries of what

00:32:52.800 is possible.

00:32:53.900 Whereas the incremental improvement is we look at something and we just move the widget

00:32:56.980 faster and they're both valuable and they're both valuable in an organization.

00:33:01.160 I think it's just a lot easier to do the incremental improvement.

00:33:04.720 And so if you think of optics and promotions and how sort of the internal dynamics of an organization

00:33:09.780 work, it becomes a lot less risky to do the incremental improvement than think about things

00:33:15.540 through a first principles basis and what's possible.

00:33:18.500 Yeah, I guess that's somewhat in tension with another mental model you have here, or at least

00:33:23.600 possibly so in doing no harm.

00:33:28.220 It's often the, well, first let's explore what that, what that means.

00:33:33.520 What do you, what do you mean by doing no harm?

00:33:35.120 On your blog, you call this the via negativa.

00:33:38.600 Yeah, so we're sort of like prone to demonstrate value in an organization, right?

00:33:46.140 We're, we're prone to having this bias towards action, this bias towards doing something and

00:33:52.080 being seen as doing something.

00:33:53.760 And often when we do that, we have a knee jerk reaction.

00:33:57.440 We solve the most visible problem that exists.

00:34:02.080 We don't necessarily solve the fundamental problem.

00:34:05.280 And a great example of this is sort of, if you think about software and you have a problem

00:34:10.700 with a software, hypothetically, you're using an HR software at work, you have a problem

00:34:15.580 with that software.

00:34:16.840 And that problem is, you know, people can't take vacation leave through that software.

00:34:22.120 They have to manage and track it through an Excel spreadsheet.

00:34:24.740 And so you're put in charge of solving this problem.

00:34:28.680 And while you go out in the world and you look for software that can solve this particular

00:34:35.020 problem where you can track vacation and you implement this new software, but you don't

00:34:40.020 realize that the software has created other problems.

00:34:43.760 You don't realize that like you've just changed one problem for another.

00:34:47.060 And the problems that you're getting now could be a lot worse than the ones that you're dealing

00:34:51.140 with.

00:34:51.460 The tension I saw there is that there's the Via Negativa model would counsel a kind of

00:34:58.180 conservatism, right, or an incrementalism, where it's like rather than tear up the whole

00:35:03.980 approach by the roots and reinvent it, you do just want to shave off inefficiencies or find

00:35:11.520 other ways of optimizing what has worked in the past rather than completely rethink it.

00:35:18.580 You mentioned Elon, you know, yesterday he successfully launched his Falcon Heavy rocket and landed

00:35:25.900 all the booster stages, right?

00:35:27.940 So this fundamental change of, you know, thinking of rocket launches as something that should

00:35:33.360 be totally reusable and you've got to figure out how to land these things, land the first

00:35:37.720 stage.

00:35:38.620 It's, you know, on its face, sounds like a crazy idea, but once you set that goal based

00:35:43.020 on rethinking the first principles of the whole enterprise, now we've discovered there's a

00:35:47.620 solution, but that requires such a vast use of resources to rethink something so fundamental

00:35:55.480 in an area that's so expensive already.

00:35:58.860 I mean, obviously this is a, the goal here is to cut the costs and to make it a bigger industry,

00:36:03.900 but it's easy to see that you could have gone down that path and for a very long time for

00:36:08.800 Elon, it looked like he was going down this path to a waiting cliff, right?

00:36:13.680 There was no guarantee of success.

00:36:15.920 What an amazing time to be alive.

00:36:17.540 Yeah.

00:36:17.740 I just want to say that, right?

00:36:19.220 Like watching rockets launch and sort of like re-land and then re-deploy is...

00:36:24.860 Well, that footage is so...

00:36:26.320 There are a few things which every time you see them, you don't really habituate to how

00:36:33.700 weird and futuristic they seem.

00:36:36.000 I mean, and this, this is footage that I'm sure at some point will become jaded enough

00:36:40.460 to say, well, that's, of course, that's the way that's supposed to work, but watching those

00:36:44.980 boosters land perfectly in unison, it just looks like a science fiction movie from the

00:36:51.820 eighties that, you know, was just preposterous.

00:36:54.180 And then when you, when you think you, you sort of alluded to why that happened, right?

00:36:57.640 When he's being interviewed, I remember him talking about it in the sense of, I just thought

00:37:02.480 about what was possible and I thought it was possible, it was physically possible to reuse

00:37:06.500 rockets.

00:37:07.880 And so he thought about the problem in a different way and he has a very great ability to attract

00:37:14.920 not only capital, but people to working on those problems and the result can be amazing.

00:37:20.980 But it's also important to note that not all of those results are amazing.

00:37:25.580 I mean, we see this sort of like SpaceX's of the world and we probably don't see the hundreds

00:37:30.940 or thousands of companies that rethink the problem as well and fail.

00:37:35.200 But I mean, that's how we make incremental progress as a society.

00:37:39.420 But that is, I guess that's probably another mental model you have written about.

00:37:44.100 There's a survivorship bias that we're constantly being advertised the evidence of only those success

00:37:52.020 stories and we're not given any true indication of the ocean of failures that is behind many of

00:38:00.120 those.

00:38:00.960 Maybe we should talk about that.

00:38:01.760 I mean, I guess this also connects to another model, which is just understanding base rates.

00:38:06.100 I mean, just how many new businesses succeed, for instance, or how it's like this is not

00:38:10.020 something that you necessarily understand when you calculate the probability that any new

00:38:17.260 venture is going to work out for you.

00:38:19.360 I mean, our view is based on ego, right?

00:38:21.160 So we think, you know, the restaurant we're opening or the podcast we're launching or the

00:38:26.840 app we're doing or sort of the new business that we're sort of endeavoring to undertake

00:38:32.160 is going to be successful because we're involved in it.

00:38:35.200 Right.

00:38:35.380 But everybody has that view and the success rates are, you know, abysmal, especially after

00:38:40.640 a five-year period.

00:38:41.520 Same as marriage, right? 0.98

00:38:42.420 If you ask people whether their marriage is going to be successful, if they're sort of like

00:38:46.420 on day one and embarking on that, they're of course going to say, like, we're not going

00:38:49.860 to fall victim to this 50% of marriage is dissolved sort of base rate.

00:38:54.820 But you don't have that.

00:38:55.740 You need to factor in that outside view in terms of making decisions.

00:38:59.700 And you don't need to do it all the time.

00:39:01.260 Maybe it's best not to do it in matters of love, right?

00:39:05.200 And maybe it's best to make a more emotional decision there, I think.

00:39:08.500 Well, in that having a positive bias or an optimism bias could actually be a self-fulfilling

00:39:18.320 prophecy to some degree in many endeavors.

00:39:21.600 I mean, it's just that the positive attitude has to count for something in various contexts.

00:39:26.100 I agree.

00:39:26.540 I think this desire to be purely rational all of the time in every decision that we make

00:39:32.500 might actually be a disservice because it would sort of take people like Elon and why

00:39:39.000 would I try to reuse a rocket?

00:39:40.420 It's never been done before.

00:39:42.340 And it would sort of dissuade us from doing that.

00:39:44.400 We need some sort of emotional component to our decision making.

00:39:47.680 It's just a matter of determining when it's serving us and when it's hurting us.

00:39:51.940 And I think that that would be the more accurate view of how you think about that.

00:39:55.760 So thought experiments, how do you think about thought experiments?

00:40:01.660 The phrase now for me is fairly charged because I am the victim of having used thought experiments

00:40:09.880 on controversial topics that did not get received like they were thought experiments.

00:40:16.480 Oh, which ones?

00:40:17.680 This is something that I got being a student of philosophy, where just to look for any kind

00:40:25.160 of ground truth, especially morally, you want to think of the corner cases.

00:40:30.320 You want to think of conditions where you've simplified a real world scenario so that you

00:40:37.060 can discover whether or not you actually have an argument against or for the thing you think

00:40:41.320 should be clear cut.

00:40:42.440 So probably the clearest case for me is thinking about the ethics of torture.

00:40:47.860 It's a fascinating and consequential argument to be had about whether torture is ever ethical.

00:40:56.160 And it's by no means straightforward when you line it up against the other things we accept

00:41:02.420 without blinking our eyes, which on paper seem worse than torture as you line them up.

00:41:09.640 And the example I used was collateral damage.

00:41:12.740 But in order to have that conversation, you talk about ticking bomb scenarios, right, which

00:41:17.900 in the real world don't happen very often.

00:41:22.620 And in the purest cases, they don't happen at all.

00:41:25.920 But the issue is if you actually want to get down to bedrock, if you want to understand whether

00:41:30.840 you can make an ethical argument against the use of torture in all cases, you need the clearest

00:41:36.640 case.

00:41:37.080 You need to say, OK, let's take out all the variables.

00:41:39.220 Let's take out the uncertainty, for instance, of a person's guilt, right?

00:41:42.860 So we know the person we have is guilty, right?

00:41:45.640 We know that, you know, we caught him with his heart.

00:41:49.520 He even claims to be guilty, right?

00:41:50.780 And we caught him with his computer.

00:41:52.020 And we can see, you know, the kinds of nefarious things he's been planning.

00:41:55.320 And, you know, we see the plans for the nuclear device that he claims is hidden in the middle

00:42:01.000 of a city, right?

00:42:01.760 And he won't give us the information.

00:42:03.360 So you need the purified case, not because that's the likely case.

00:42:08.920 But let's just figure out if we actually have an argument against the use of torture in all

00:42:14.520 cases, because that would be immensely clarifying.

00:42:17.020 Because if we solve that, then we know, OK, we're never tempted to make an exception to this

00:42:22.760 rule, right, because we've thought it through in the clearest case, where we know the person

00:42:26.760 is guilty.

00:42:27.600 We know they've got a nuclear bomb in the middle of a city.

00:42:30.100 We know we have a shortage of time.

00:42:32.140 There's no other methods we can use to get the intelligence.

00:42:35.280 You distill it down to the case where even good people would be the most tempted to resort

00:42:43.220 to torture, then see if you have an argument against it.

00:42:46.240 But what happens when you have conversations like that is that then people, rather than

00:42:52.740 receive them in the spirit of ethical inquiry for the purpose of charting a course in the

00:43:00.100 future politically, they put a journalistic or political lens on it from the start, right?

00:43:05.740 And so, I mean, even a clearer case, and this is a case I haven't actually used, but this

00:43:09.680 is the kind of thing that one would routinely do in a philosophy seminar.

00:43:13.660 You say, OK, well, why can't we eat babies, right?

00:43:16.120 So like babies, there are unwanted children in the world.

00:43:19.300 They're full of protein.

00:43:20.440 I mean, what's wrong with eating babies?

00:43:22.240 Now, it's not that the person who's raising that example has an interest in eating babies.

00:43:29.300 It's just, this is like a laser focus on moral bedrock, right?

00:43:34.140 To go that far to the edge case.

00:43:37.180 And it's instructive that some, you know, some people will find it difficult to even argue

00:43:43.480 that case, right?

00:43:44.400 I mean, some people will feel like they need to resort to a holy book revealed by an invisible

00:43:48.700 god in order to get you some bedrock where you can stand so as to not eat babies.

00:43:53.040 And so it is an engine of interesting and morally rich conversation.

00:43:59.700 Now, obviously, not all thought experiments deal with ethically fraught territory.

00:44:03.300 But I do find that the concept of a thought experiment has been stigmatized because it is synonymous

00:44:11.320 with or thought to be synonymous with not making contact with the real world.

00:44:17.100 You're basically creating the straw man case that you're then going to use to guide you

00:44:22.260 in the future with predictably bad results.

00:44:25.620 A couple of comments, just as you were talking there, one of the things that I found myself

00:44:33.400 thinking as you were talking is, how do we find out about what we think on an issue?

00:44:38.780 How do we find out where we land on a particular issue?

00:44:43.080 And so we're expected to have these fully formed opinions.

00:44:48.040 We're expected to have these fully thought out.

00:44:50.560 And we have really, I would argue, it's sort of increasingly difficult to have conversations

00:44:58.180 about these things.

00:45:00.480 And that in itself is a problem.

00:45:02.640 Like, can you imagine sort of like the outrage that would ensue about, you know, having this

00:45:08.300 debate on Twitter or just trying to figure out where you land?

00:45:12.360 So you put this out there and then the feedback would be like the media would be all over you.

00:45:17.600 People would be jumping on you.

00:45:19.600 I don't have to imagine it.

00:45:20.340 This is my life on Twitter.

00:45:21.700 But this is it, right?

00:45:22.580 This is why I'm tempted to delete my Twitter account on a monthly basis.

00:45:25.380 Aren't we better off having this safe space, like almost like a sandbox where we can play

00:45:31.340 with ideas, where we can explore things, where they don't have to infect us.

00:45:36.620 We don't have to believe it.

00:45:38.540 For me, this podcast has become that sandbox.

00:45:41.640 I have taken great pains to insulate it against the normal commercial pressures.

00:45:47.560 As you know, maybe we'll talk about that at some point.

00:45:49.340 But another example occurs to me that a guest brought up who I believe you've also had on

00:45:54.520 your podcast, Will McCaskill, the ethicist, who's just fantastic.

00:45:59.340 And he was talking about the ethics of, you know, running into a burning building to save

00:46:05.420 a child.

00:46:06.700 You could do that.

00:46:07.780 But if you run into that burning building and on your way to the child's bedroom, you

00:46:13.280 discover that there's a Picasso on the wall and you could also save that and, you know,

00:46:19.180 liquidate that.

00:46:20.140 And we use the, you know, the $75 million or whatever you get from that sale to save many

00:46:26.100 more children than one, right?

00:46:28.260 And if there were really a zero-sum contest between the money or the child, at minimum,

00:46:34.040 that's an interesting ethical, apparent ethical dilemma to sort through, right? 0.74

00:46:38.560 Now, it seems we have a very strong intuition that you would be a psychopath to grab a painting

00:46:44.140 rather than a child from a burning house.

00:46:46.700 But, of course, the choice is never really presented to us in that form.

00:46:51.920 But there are many analogous choices.

00:46:54.240 When you look at just the decision for a news organization to spend 24 hours covering a

00:47:02.020 story about a single suffering person as opposed to a genocide that is raging in some distant

00:47:08.500 country, it's just the way we marshal our resources, you know, the single compelling case

00:47:13.900 that causes the massive judgment as opposed to the statistics of vast human suffering that

00:47:22.560 doesn't move the needle at all.

00:47:24.440 This is how we can discover and correct for moral bugs that are actually of great consequence.

00:47:29.780 We need a mechanism to sort of have these conversations, and I think it's going away.

00:47:36.320 And as of right now, I mean, the only safe, guaranteed safe space you ever have is just inside your

00:47:41.740 own brain.

00:47:42.660 Right.

00:47:42.840 But in the future, we might even see that go away as technology increasingly sort of like

00:47:47.600 permeates us and maybe our skin.

00:47:50.300 And then what happens is like the minority report might become real, right? 0.99

00:47:54.000 Where you think of somebody cuts you off and you're like, I want to kill them.

00:47:58.360 And all of a sudden you're arrested because you had this thought.

00:48:01.740 And I think like we're at the very, we're in a very interesting time for thinking where

00:48:07.380 that sandbox doesn't exist.

00:48:08.980 Like you, you can't go out being Sam Harris and say something.

00:48:13.240 I mean, you can because you're you.

00:48:15.360 But I mean, a lot of people with such a public profile can't come out with a controversial

00:48:19.900 idea because the backlash on them is going to be so huge.

00:48:24.040 And I think as a society, we need a way to sort of maybe press it.

00:48:28.560 If you'd like to continue listening to this conversation, you'll need to subscribe at

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Making Sense - Sam Harris - April 29, 2019

#155 — Mental Models

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