Category: Notes

Notes from RenTec CEO Peter Brown on the GS Podcast

Podcast: Goldman Sachs Exchanges: Great Investors

Raj Mahajan, global head Systematic Client Franchise interviews  Renaissance Technologies CEO Peter Brown on July 27, 2023

I grabbed some excerpts from the transcript for future reference.

I include my own commentary here and there.

Newsflash: Money is a big factor in what people choose to do

Raj Mahajan: Seems that you were right at the vanguard of the machine learning movement in 1993. So, why did you leave an exciting career at IBM for a small financial company in Long Island that no one had ever
heard of?

Brown: …Three things happened. First, Bob had a second daughter accepted to Stanford. But he couldn’t afford to pay for her to go to Stanford on his IBM salary. So, she had to go to the agricultural school at Cornell, which offered scholarships to New York State residents. The second thing that happened is we had a daughter born. And a third thing was that Jim then offered to double my compensation. After that offer, I came home. I took one look at our newborn daughter and realized I had no choice in the matter. So, the decision to leave computational linguistics for a small hedge fund that no one had ever heard of was made purely for financial reasons.

Examples of Emotional IQ

[Kris: The EQ vs IQ thing is a false dichotomy. I suspect they are actually positively related but when we look at outliers on either dimension there is a major Berksons Paradox effect. RenTec has the reputation of being the true “smartest guys in the room” in the IQ/STEM sense of the word. And yet, multiple times in this interview I am struck at how people-savvy they have been. Which makes perfect sense to me. In a domain where the competition constantly learns and psychology plays an enormous role this is exactly what you expect. Only the naive who believe that investing is physics as opposed to biology cling to Spock-like caricatures of effective quants. Here are several excerpts demonstrating an deep understanding of human behavior]

Selling an approach to employees

Brown: At the end of 2002, Bob and I also took over the rest of the technical side of the firm, which included the trading of currencies, bonds, options, and futures. Now, our plan was to use the equities code that we and others had developed to trade these other instruments. But we recognized they would not be so great for morale to tell, say, one of the futures researchers, “You know all that code you spent the last decade of your life developing, guess what, we’re going to throw it out.” So, we had to spend quite a bit of time getting everyone to buy into our plan. To do this we used an approach that I learned from a biography I’d recently read of Abe Lincoln, which was to get them to come up with our plan themselves. Now, that took some time, but eventually it all worked out. 

Jim Simons weighing the input to manage a risk crisis

See below: 2007 — “Quant Quake”

Jim Simons reading a situation shrewdly

Brown:  In the fall of 2008, the whole financial system was stressed. So, we were concerned with the stability of our counterparties. So, we spent a lot of time with those counterparties and examined their CDS rates and so forth. I remember at one point, two senior executives from some firm we did business with came into our New York City office to meet with us. They assured us that the funds we had in our margin account were safe with them. And I was inclined to believe them. Why not? But after the meeting, Jim said, “Peter, they wouldn’t have come to our office. They wouldn’t have requested the meeting unless they were in real trouble. It’s time to get out.” So, we did. And Jim was right because shortly thereafter, that firm just disappeared. 

Examples of automation and innovation within RenTec

Brown: When we got control of the New York office, the first thing I did was to walk around that office, find out what everyone was doing. And what I found was that many people were doing jobs that could be automated. So, we set out on a massive campaign to automate our back-office operations. We moved from checks and wires to SWIFT and ACH. We replicated counterparties margin calculations. We built a large legal database that could be accessed by computers to fill out regulatory forms. We brought in AI systems to automatically read and pay invoices. We automated the treasury department so that cash and margin needs could be managed by computers instead of humans. My point of view was that Stony Brook produces a huge list of transactions and New York City produces monthly statements, K1s, and government filings. And I just didn’t see why humans need to be involved in the process of translating trades to monthly statements. Now, 13 years later, we’re not done yet. And I’m embarrassed to admit that we still even have a few people who use Excel. But we’re getting there. In fact, I was told recently that we’ve eliminated 97 percent of the spreadsheets that had originally been used in the company.

Stories about risk management

March 2000 — Dot Com

Brown: Let me start with March of 2000 when the dotcom bubble burst. We were doing extremely well back then. And we had large positions in the internet stocks. They were traded on NASDAQ. At one point the head of risk control came to me and said he was worried about the size of our NASDAQ positions. But I told him not to worry, the computer knew what it was doing. Then we took a big loss one day. So, I worked through the night trying to understand what was going on. The next day we took another big loss. And I, again, worked through that night. So, now it’s the third day and I hadn’t slept for, I don’t know, 48 or 50 hours. And I was sitting in a meeting with Jim and a few others when the head of production knocked on the door and asked to speak with me. I walked out of the meeting, and he told me we were down again by a large amount. So, I walked back in the meeting, and I must have turned white or something because Jim took one look at me and said, “It doesn’t look good.” Now, not having slept the previous two nights, I remember thinking I’m not sure I can get through this. But I really didn’t have much choice in the matter. And so, we got back to work and eventually we did get through it. A couple days later I went into Jim’s office and told him that I’d screwed up in not appreciating the risk we were taking and said that if he wanted me to resign, I would resign. But he responded, “Peter, quite the opposite. Now that you’ve been through such a stressful losing period, you’re far more valuable to me and to the firm than you were before.” Now, that response really tells you something about Jim Simons.

2007 — “Quant Quake”

Brown: When that happened, I was on vacation, and I was on a very long flight back to Newark Airport. And the moment the plane landed, my phone went nuts with all kinds of texts and missed phone calls. So, I called into work when it was going on and I got Kim, Jim’s assistant. And she said, “Jim wants you to get back here as soon as you’re physically able.” So, I raced out. I found a taxi, leaving my family to fend for themselves at Newark Airport. And pushed the driver to drive as fast as he could from Newark to Long Island. I ran into my office, and I found Jim, Bob, Paul Broder, who was head of risk control, all holed up. And the office was full of cigarette smoke. I could barely breathe. And then there was this, I remember seeing this, 16 oz cup full of Jim’s cigarette butts. And I’m thinking, like, why do they have to do this in my office? And they were all staring through the haze at the computer screens trying to figure out what was going on. And Jim was interpreting every little wiggle and various graphs. He was really scared. And he wanted to cut back and hard. Paul also wanted to cut back. Raj, I’m sure you know, the head of risk control always wants to cut back. Because he doesn’t get paid to make money. He gets paid to make sure you don’t lose money. 

And Bob, you know, Bob’s always very calm. But he wasn’t against cutting back. But I looked at the data and saw that the model had these enormous predictions, the likes of which I had never seen before. It was clear to me what was going on. People were dumping positions that were correlated with their own positions. And they were driving prices to ridiculous levels. I felt they had to come back. I argued that we should not cut back. That this was going to be the greatest moneymaking opportunity we’d ever seen. And if anything, we should increase our positions. But it was three against one. And so, we continued cutting back. But I succeeded somewhat because we cut back at a slower pace. And then at one point, miraculously, the whole thing came roaring back. And indeed, it was an incredible money-making opportunity. Now, what we learned from that was to always make sure we have enough on reserve to just hang on. Later, when Jim was about to retire, I reminded him of this period and asked if he was concerned that I was going to be so aggressive that I was going to blow the place up. But Jim responded that the only reason I was so aggressive was because I knew he was determined to reduce risk, another example of Jim’s insight into human nature. 

What RenTec does differently

Brown: I guess there are some firms that make it their business to learn how others make money and try to learn their secrets. That’s not our style. We just hire mathematicians, physicists, computer scientists with no background in finance and no connections with Wall Street. 

A few principles we follow:

  1. Science

    The company was founded by scientists. It’s owned by scientists. It’s run by scientists. We employ scientists. Guess what, we take a scientific approach to investing and treat the entire problem as a giant problem in mathematics.
    [Kris: In chatting with a friend who has proximity to RenTec, I learned of this a few years ago. I was intrigued by how they felt quite comfortable incubating highly promising individuals by offering a well-paying collegiate atmosphere that offered an alternative to traditional academia. It feels like just another instance of what I call risk absorption. RenTec is a highly efficient “bidder” for the risk of a scientist’s effort panning out. They can build a portfolio of talent in the form of a skunkworks knowing that they can scale important discoveries across their trading. Not unlike how a military R&D department might think of investments in scientists.

  2. Collaboration

    Science is best done through collaboration. If you go to a physics department, it would be absurd to imagine that the scientist in one office doesn’t speak to the scientist in the office next door about what he or she is working on. So, we strongly encourage collaboration between our scientists. For example, we encourage people to work in teams. We constantly change those teams up so that people get to know others within the firm. We pay everyone from the same pot instead of paying different groups in accordance with how much money they’ve made for us and so forth.

  3. Infrastructure

    We want our scientists to be as productive as possible. And that means providing them with the best infrastructure money can buy. I remember when I was at IBM, there was this attitude that programmers were like plumbers. If you need a big project done, just get more programmers. But I knew that some programmers were, like, ten times or more productive than others. I kept pushing IBM management to recognize this fact. But it did not. I remember being in an IBM managers meeting and some guy from corporate headquarters was explaining how they created something called their headlights program. The goal of which was to identify the best programmers in the company and pay them 20 percent more than the other programmers. Now, I figured this guy from corporate was making, like, $300,000 a year. So, I raised my hand and suggested they increase the pay of their best programmers to $400,000 a year. And he was stunned. He said, “What? More than me? You’ve got to be kidding me. Well, if the guy’s Bill Gates.” I said, “No, Bill Gates was making, like, 400 million per year. Not 400,000.” Anyway, they just didn’t get it. We don’t make that mistake. We pay our programmers a ton in accordance with the value we place on the infrastructure they produce.

  4. No interferenceWe don’t impose our own judgment on how the markets behave. Now, there’s a danger that comes along with success. To avoid this, we try to remember that we know how to build large mathematical models and that’s all we know. We don’t know any economics. We don’t have any insights in the markets. We just don’t interfere with our trading systems. Yes, of course there are a few occasions where something’s going on in the world and so we’ll cut back because we think the model doesn’t appropriately appreciate the risk of what’s going on. But those occasions are pretty rare.
  5. Time

    We’ve been doing this for a very long time. For me, this is my 30th year with the firm. And Jim and others were doing it for a decade before I arrived. This is really important because the markets are complicated and there are a lot of details one has to get straight in order to trade profitably. If you don’t get those details straight, the transaction costs will just eat you alive. So, time and experience really matters. 

A word on politics

[Kris: Peter Brown is liberal and co-CEO Bob Mercer is famously conservative. I can say that coming from the trading world, the liberal perspectives are in the minority amongst the traders but less so amongst the academics.]

Raj Mahajan: Is it true that while Bob Mercer and you have different politics, you worked closely for nearly 40 years at IBM and Renaissance? 

Peter Brown: Yes. It’s true. Bob and I began working together at IBM 40 years ago. And for most of the time, we’ve had offices right next to one another. So, we’ve done a lot together. And we’re still really close. In general, I find no better way of building friendships than through the collective creative process of building something together. And I see no reason why politics should interfere with friendship. 

Man vs machine stories

1) My understanding is that you had nothing to do with finance until age 38 and, instead, began your career working on automatic speech recognition. How did that happen?

Brown: So, at one point during high school I learned about the Fast Fourier transform. And I thought this was about the coolest thing I had ever seen. Probably because I went to an all-boys’ school and had nothing better to contemplate. Anyway, for some reason I got into my head that with the Fast Fourier transform it should be possible to recognize speech. You just take the speech data, transform it into the frequency domain. Match it up against patterns for words. And presto, magic, HAL would be born. And this idea always stuck around in the back of my mind. 

Then when I went to college I majored in math and physics. But in my senior year I had to fulfill a distribution requirement. So, I took a course in linguistics. And one day in the back of that course I heard a couple students talking about some guy whose name was Steve Mosher who started a company called Dialogue Systems that was doing speech recognition. And I thought, wow, great, I remembered this idea from back in high school. After class I raced over to the physics library. That’s because this was before the internet, so you had to go to the library. And I looked this guy up. And I found a paper he’d written. And I tracked him down. Applied for a job. And he hired me. And when I was there, I just fell in love with the idea that through mathematics it might be possible to build machines that do what humans do. I just loved the idea of exposing human intelligence to be nothing more than robotic computation.

2) I recently heard that in a talk you give at Harvard Business School you mentioned that you had a role in starting up the Deep Blue project at IBM. Can you tell us about that? 

Brown: Wow. Okay. I had been at IBM for a year or two. And I was standing in the men’s room one day when the vice president of computer science, a man named Abe Peled walked up next to me. I thought to myself, now’s my chance. I turned to him and said, “Dr. Peled, do you realize that for a million dollars we could build a chess machine that would defeat the world champion? Think of the advertising value to IBM.” He turned to me, looking kind of annoyed, and said, “What’s your name?” So, I told him. And then he said, “Could you please let me finish up here?” And so, I thought, wow, I had made a big mistake. So, I apologized, and I high tailed it out of there as fast as I could hoping he’d forget my name even faster.

But a half hour later, he called me in my office and told me that if I wanted to build a chess machine, he’d put up the million dollars. I told him that I was occupied with speech recognition. I have three friends from graduate school who could build it. He said, “Okay, hire them.” So, we did. They built the machine. I named it Deep Blue. In the first match, the IBM machine was a very weak machine. Weak physically. You know, I think only one special purpose chip in it. And we lost. The final match, however, was a different story. IBM had a much, much stronger machine with hundreds of special purpose chess chips. IBM won that match and IBM’s stock jumped $2 billion afterwards. Of course, it fell back down later. 

Now, a few years ago I was asked to speak at the Harvard Business School. And when I arrived, outside the auditorium, I could see all these protesters. And I thought, oh no, why are they protesting me? What have we done? Is there something I’m not aware of? I really didn’t want to do that. But as I got closer, I could see they were all holding signs about investing in Puerto Rico. And I thought, what is this all about? I was totally confused because I didn’t think we had anything to do with Puerto Rico. Then it turned out that the speaker before me was some guy named Seth Klarman from some firm named Baupost. Evidently, that firm had some investments in Puerto Rico and the protesters were protesting him. So, I went in to see Klarman’s talk, or at least the end of Klarman’s talk, to find out what all the hullabaloo was about. 

At the end of his talk, someone asked him his thoughts on quantitative investing. I suppose it was a set up for my talk. I don’t know. And I carefully noted his answer which was, “To do what I do takes a certain amount of creativity and finesse that a computer will never have.” And all those Harvard Business School MBAs seemed to really like that response. So, when it was my time to speak, right after him, I began by pointing out that after defeating Deep Blue in the first match, Kasparov was elated and gave a press conference at which he said, “To play chess at my level takes a certain amount of creativity and finesse that a computer will never have.”I then went on to point out that two years later we crushed him. Now, I’m not sure that’s how things will evolve. But whether it’s speech recognition, machine translation, or building large language models, or chess, or making investment decisions, I continue to love the process of showing that human intelligence, intuition, creativity, and finesse are nothing more than computation.

[Kris: In defense of Klarman, like the pod shops, I don’t think RenTec is investing so much as trading. Marc Rubinstein writes:

Dmitry Balyasny, founder of Balyasny Asset Management, attributes the model to a trading view of markets as distinct from an investing view.

“[Its] origins go back to my origins as a trader and thinking about how to build out business around trading… It makes sense to have lots of different types of risk-takers, because you have less correlation, you could attack different areas, the markets, and have specialists in different areas.”

I’ve beat that drum in Trading vs Investing and with great humility in How I Misapplied My Trader Mindest To Investing. 

Addressing Brown’s obsession with “exposing human intelligence to be nothing more than robotic computation.”

In The Introspection of Illusions, author David McRaney parses opacity of the intelligence and preferences buried in our subconscious:

Psychologically speaking, users found it easy to access the feelings that prompted them to give those films one star or five. Explaining why they made one feel that way would require the kind of guided metacognition that the Netflix interface simply couldn’t offer. Even when you stepped away from the code and the spreadsheets and asked people in person, they might not be able to tell you. They could make a guess. They could attempt to explain, justify, and rationalize their feelings, reactions, and star ratings, but without a conversational tool, a back and forth to get past all that to something honest and perhaps previously unexplored, you ran the risk of precipitating a psychological phenomenon known as the introspection illusion which would likely result in yet another phenomenon known as confabulation. There’s an entire literature of books and papers and lectures and courses devoted to this side of psychology. To put it very simply, we are unaware of how unaware we are, which makes us unreliable narrators in the stories of ourselves. You are, however, amazing at constructing stories as if you did know the antecedents of those things when explaining yourself to yourself and/or others.

There are parts of us we can’t access, sources of our emotional states we can’t divine, and I find some strange poetry in the fact that, like us, the algorithms can’t always articulate the why of what we do and do not like. Yet, through millions of A/B tests slowly zeroing in on more and more successful correlations, the Netflix Recommendation Engine can produce a glimpse of something a bit like the sort of profound, soul-exposing knowledge earned via an intense introspection that we could never achieve. Something a few fathoms deeper than “I don’t know, it just wasn’t for me.”

Speed Round

1) Is it true that at one point you went to IBM to suggest that the statistical methods you were using in speech recognition could be applied to finance, and asked to be given an opportunity to manage some fraction of IBM’s corporate cash?

Brown: Yes. I think that was in 1993. But IBM corporate had absolutely no interest. So, instead we went to Renaissance where we did the same thing we had in mind for IBM, but instead with money Jim Simons had raised.

2) Is it true that since you first joined Renaissance you have spent nearly 2,000 nights sleeping in your office? 

Brown: Yes. My wife works in Washington DC. And my experience has been that when a husband and a wife work in two different towns, the husband commutes. Psychologically, if I’m going to be away from my family, I have to work. I sleep in my office when I’m in Long Island. 

For me, productivity-wise it’s really fantastic being able to spend nearly 80 straight hours each week with no interruptions except sleep thinking about work before spending three more normal days at home. Of course, I really miss my family. But the freedom to concentrate nonstop on work while surrounded by my colleagues is hugely valuable. And the job is so demanding, I really don’t see how I could do it otherwise.

[Adds this]  I’m just one of those types who can’t sleep. Not by choice. I just can’t sleep. So, I often am on the computer by around 2 am. And it’s true, I tend to send a lot of emails out in the middle of the night.

3) Is it true that you almost exclusively hire people with zero background and finance? 

Brown: Yes. We find it much easier to teach mathematicians about the markets than it is to teach mathematics and programming to people who know about the markets. Also, everything we do we figure out for ourselves. And I really like it that way. So, unlike some of our competitors, we try to avoid hiring people who have been at other financial firms. 

[Kris: The prop trading firms think similarly. My friend Joel talks about how Brown’s claim that it “is is easier to teach markets to mathematicians than it is to teach math to market experts, may seem dismissive to market-centric people but in reality is more of a statement about what “math” is at Renaissance.” He goes on to distinguish about levels of math but I latched on to this a more general observation:

Markets person isn’t a thing. Markets thinking is systems thinking and anyone from any discipline can learn that. From there go on Investopedia and learn how a zero coupon bond or share of stock works. start with a good, teachable mind then label the variables.

Math/STEM skills are legible markers of computational/rigorous thinking. Someone trained in the nitty gritty of assumptions, what follows, and so on. Making abstractions concrete.

If I’m generous it took a month of professional training for non-finance STEM grads at SIG to know everything finance grads would have brought to the table. But you can’t teach math and computer science in a month. 

Ultimately this is only part of the story of getting a great start in finance. There’s a Berksons Paradox once you are in the pool of high level finance employment where the math skills don’t correlate as much with talent. You get older and realize the dichotomy of being a math person vs a verbal person that you carried as an identity when you were young is bullshit. Skills in either are likely highly correlated. But maybe the right door or guidance wasn’t there to help you see that.]

4) What do you actually look for in applicants? 

Brown: Math ability. Programming ability. A love for data. A work ethic. And most importantly, the ability and desire to work will in a collegial environment.

5) How do you actually assess those qualities?

Brown: I think probably the same way other firms do. First, we get resumes. Those that look promising we give them phone interviews and we ask them for references. If those pan out, then we invite the promising applicants to give research talks. Talks like if you’re applying for a job at a university or something like that. And then we put them through a grueling day of solving problems in math, physics, statistics, computer science, and so forth at a blackboard.

6) Is it also true that your staff had to install mirrors in the corners of the office to prevent you from flying into people as you rode a unicycle around the office? 

Brown: Where did you get all these questions from? Yes, it’s true. Although, I don’t ride a unicycle anymore because at one point I crashed and the unicycle broke. 

David McRaney on EconTalk

Episode description:

To the Founding Fathers it was free libraries. To the 19th century rationalist philosophers it was a system of public schools. Today it’s access to the internet. Since its beginnings, Americans have believed that if facts and information were available to all, a democratic utopia would prevail. But missing from these well-intentioned efforts, says author and journalist David McRaney, is the awareness that people’s opinions are unrelated to their knowledge and intelligence. In fact, he explains, the better educated we become, the better we are at rationalizing what we already believe. Listen as the author of How Minds Change speaks with EconTalk host Russ Roberts about why it’s so hard to change someone’s mind, the best way to make it happen (if you absolutely must), and why teens are hard-wired not to take good advice from older people even if they are actually wiser.

Link: https://www.econtalk.org/david-mcraney-on-how-minds-change/

I think the best teaser for the interview occurred during the interview when McRaney says:

The incepting point of this book was someone in a lecture came up to me and asked about their father who had slipped into a conspiracy theory and they said, ‘What can I do about that?’

And, I told them, ‘Nothing.’ They said, ‘How do I change his mind?’ I said, ‘You can’t.’ And, I really felt, the second I said it, that: I don’t know enough about this to say something like that. I don’t even know if I believe what I just said, but I know one thing I don’t like this attitude I have about this issue. I should at least learn more about it.

And, if I was in that same situation today, I would actually be able to say, ‘Oh, here’s what you should do. Here’s what you should say.’ I no longer believe anyone is unreachable. I no longer believe anyone is unpersuadable.

In conversations that don’t work out the way we think,  we blame the other side. We say, ‘They’re dumb. They’re mean. They’re evil. They’re ignorant. They are unreachable, unchangeable, stuck in their ways.’ These are all things that we are using to forgive ourselves for failing.

My selected excerpts:

Motivated reasoning for social acceptance

Reasoning, psychologically speaking is just coming up with reasons for what you think, feel, and believe. And, those reasons are motivated by a desire to–a drive–to be considered trustworthy to your peers.

So, not only are you driven to come up with reasons for what you think you’re going to believe, you want them to be plausible. And, plausible, in this sense is: ‘What would your most trusted peers, your social network think?’ ‘Oh, yeah. That’s a reasonable way to see that.’

[Kris: For example, a quant might not respect reasoning that comes from intuition which they might see as excessively prone to bias whereas someone with a lot of experience might night trust the numbers for some unconscious pattern-matching reasons. The irony is both people recognize the intuitive approach is just pattern-matching but the quant thinks this is untrustworthy and the discretionary trader thinks it is.

I’d add another observation — the criteria for sense-making might be entirely context-dependent. Maybe the quant gets acupuncture when they go home. Our standards for epistemology vary depending on our expertise. The religious doctor doesn’t just pray for their patient.]

The process of radicalization

You feel something happens in the world that gives you this a negative emotion. Some anxiety starts to come up. It could be for really good reasons, but it could also be because you have some sort of prejudice or some sort of political bias.

So, then you do that thing. You go, ‘Hmm. Let me search for evidence that justifies the anxiety that I’m feeling.’ 

And, when you do that, online, you absolutely will find something that suggests your anxiety was justified.

And, you also might find people talking about that. And, you might end up wanting to talk with them about that. You might end up spending a lot of time talking with them.

And slowly you can radicalize yourself. You can cultivate yourself–cultivize yourself–and by, you start snipping your connections away from people who don’t share the attitudes being expressed in that community and you start strengthening the connections you do have with those.

And, now all of a sudden, you’re in a group. You’re in a community. And, the great sociologist Brooke Harrington told me that, if there was an E=mc2 [energy equals mass times the square of the speed of light, Einstein’s Equation] of Social Science, it would be: the fear of social death is greater than the fear of physical death. And, if your reputation is on the line, if the ship is going down, you’ll put your reputation in the lifeboat and you’ll let your body go to the bottom of the ocean.

We saw that with a lot of reactions to COVID [coronavirus disease]. As soon as the issue became politicized, as soon as it became a signal–a badge of loyalty or a mark of shame to wear a mask or to get vaccinated–as soon as it became an issue of ‘Will my trusted peers think poorly if I do this thing or think this thing or express this feeling or attitude or belief,’ people were willing to go to their deathbed over something that was previously just neutral.

Reactance

[Kris: calling all reflexive contrarians!]

This is a concept that has been studied extensively in the context of clinical therapy.

They would come to the therapist and the therapist would say, ‘Well, you know what’s your real problem is. You should be doing this.’ Or, ‘I don’t know if you’ve noticed, but you don’t do this very much. You should do this.’..All that feels pretty good. They now call that in psychology the “writing reflex”. And, we’ve all felt that whereas someone is saying something and you’re like, ‘Oh, I have the advice for them. I know what to tell that person.’

But, you also have also experienced this other thing that happens, and this seems to be something that’s universal to human beings across all cultures. It’s just something that the brain that we’re issued at birth, it’s something that’s a feature of human thinking, rationality, psychology. Human brains do this. It’s called reactance. In the psychological parlance, they’ll say something along the lines of, you feel motivationally aroused to remove the influence of the attitude object, which just means: ‘You made me feel a feeling I don’t like and I want it to go away. So, I’m going to push you away,’ or ‘I’m going to disengage.’

What is the feeling that’s causing the motivational arousal? It’s the sense that your agency is under threat–your autonomy is under threat. It’s the ‘Unhand me, you fools,’ feeling. You’ve all felt this. If you’ve ever been a teenager or you’ve ever spoken to a teenager, you know what I’m talking about…”You shouldn’t do this. You should study more.”‘ This is good advice that the person when they’re 35 will go, ‘Man, my parents were right about that.’

But, in that moment it’s just the fact that you’re saying, ‘I have a thing in my head that should be in your head and I want it to be in your head.’

And, oddly enough, it’s the want that creates the reactance. The person’s feeling that you have approached them in some way and said, ‘I want you to think, feel, or believe, or act in a certain way that you’re not doing right now,’ and it feels coercive. It feels like they’d come at you and they’re threatening you. They’ve got a knife in their hand, and they’re saying, ‘Walk this way.’ That’s what it feels like.

We just, at a visceral level, will react by saying ‘no thanks’ to that, and we’ll push against it.

Basically, what you’re saying is ‘I have a goal and I’m not even concerned with what your goal is. This is the goal that I want you to go toward.’ Then they say, ‘Oh yeah, well, no. How about I don’t do that? I want you to stop talking to me that way.’ Well, now you feel reactance, because you’re like, ‘Oh, you’re telling me how to talk to you? How about I double down?’

And, then you enter into a horrible feedback loop.

This happened so often in therapeutic frameworks that they’re like, ‘We should really develop a way to stop doing that.’ Because what started happening was people would come in wanting to extinguish a behavior and then they would leave therapy more likely to engage in the behavior than if they had never seen a therapist because something along the lines of: they had these arguments for and arguments against. So, they were at a state of ambivalence when they arrived, but they wanted a little bit more in energy on the side of ‘Let’s not do the thing anymore.’ But, because of that, they counter-argued with the therapist. They generated counter-arguments inside of them that put more weight on the side of continuing to do the thing. So, they walked away with more arguments for than against than when they walked in.

This is also what happens when we have a conversation with someone where we disagree on an issue. Very often, if we create that feedback loop, they will walk away with more arguments in their mind than they had coming in to continue believing or feeling in the way they had before we had the conversation.

What I want to emphasize here is you can be very much correct. The facts can be on your side. You can be really trying to reduce actual harm in this world. You can have the moral high ground, and you can be dealing with a person whose intent, they’re, like, their action and behavior, their political stance harms you. They may even hate you.

So, what I’m saying is you can be on the right side of all of this, however you want to define the word right–you can be on the correct side of all those things. And yet, if you generate reactance from the other person to what we’re talking about, you will not be able to change their mind. You lose out.

And, it’s a very difficult thing to offer a person the space and give them the respect that would avoid reactance when you are dealing with a person that you feel like doesn’t deserve that treatment from you.

Shaming will cause the same defenses to kick in

If you say something that is interpreted–you may not mean to come across this way, but if it can be interpreted as, ‘You should be ashamed for what you believe. You should be ashamed for what you feel. You should be ashamed for that value or that intent to behave,’ even if I’m putting my hand at the side of my mouth. Even if they should be ashamed. If you communicate it that way, then you’re going to activate the person’s fear of ostracism. And there’s nothing more–like we said, there’s nothing more fearful for a social crime made than the suggestion that they may be ostracized. So, if you tell them they ought to be ashamed for feeling that way, it’s going to cause them to feel very viscerally upset and angry, and they’re going to push away from the conversation.

Unblocking the discussion

 All you have to do is get out of the debate frame with the other person. Don’t make this feel like, ‘I need to win and you need to lose. I am and you are wrong.’ Just get out of that frame.

And, the easiest way to get out of that frame is to, first of all, say something along the lines of–instead of saying, ‘I want to show you what you ought to think, feel, and believe,’ you say, ‘Hmmm. You seem to know a lot about this issue and you seem to care about it a lot. You seem to see that these problems are problems. I’m wondering, given what you know, I wonder how it is that–because I look at a lot of this stuff, too. I wonder why we disagree on this issue? It’s really curious to me. I would love to talk to you a little bit more about that. I wonder if we could look at this issue and see what is it we disagree on here?’

What you want to do in that frame is give the other person a chance to feel like, instead of being face to face, you’re going to go shoulder to shoulder, and we’re going to–instead of looking at each other as obstacles, we’re going to turn and face in the same direction and look at the problem at hand, the goal at hand, the issue at hand. And, we’re going to collaborate now. We’re going to work together and say: Well, you’ve got your side of things, and your views, and your experiences, I’ve got mine. I bet if we joined forces, we could get to an even deeper truth on this or higher truth or a solution that works well for both of us.

You don’t even have to put it in those words. That’s another thing we have an innate inclination for which is, ‘Oh wow, we get to snap together and work together on a problem.’ You can frame things that way with just a slight change in approach and language and you will escape the debate frame that leads to reactance; and it’s much more fruitful.

Specific approaches that work

The thing that was most surprising in all that was discovering that there were all these different organizations that had said, ‘Okay. Well, what do we do about this?’ And, they started A/B testing conversation techniques. I found deep canvasing, and street epistemology, and smart politics, and then all the therapeutic models that I mentioned–motivational interviewing and cognitive behavioral therapy. And, on and on and on. There’s so many.

And, the thing that was most surprising was: Most of them had never heard of each other, never seen each other’s work. Many of them, the majority of them weren’t aware of the–if they weren’t in therapeutic domains–they weren’t aware of the science that would support what they were up to. Yet, independently, they all came up with pretty much the exact same technique. And, if you put it in a step-by-step order, it’s almost in the exact same order every time, too.

That seems to me like something almost in the world of physics or chemistry, and that if you were to build an airplane–the first person to build an airplane, it was always going to look like an airplane. It doesn’t matter where they built it. It doesn’t matter what culture they were from. It doesn’t matter how old they were, what they looked like, what they knew about anything. Airplanes have to look like airplanes because physics works like physics on the planet Earth.

Conversational techniques that actually shift attitudes and open people up to different perspectives, that get past resistance, all pretty much work the same way because brains resist for universal reasons and brains work in a very particular way.

Diving into street epistemology

Origin

Street epistemology came out of the world of the angry atheists and the militant agnostics who were having their own reaction to getting online and meeting each other. And, they’ve gone through several phases of growth and evolution themselves where they have schismed off. And, there’s some who are still very angry and there are some who are much more humanistic and empathetic.

And, within all of that, there was this movement that came about where they wanted to know, like, ‘How do we talk to people in a way that could avoid the angry pushback that we so often get when we speak with people who are not in our subculture or do not see or have our same theistic or atheistic views?’

And, they did the same thing that people did in deep canvasing. They went out. They had conversations with people. They recorded those conversations. They shared them with other people in the group. And, when something seemed to work well or get them closer to having a good conversation, they kept it. Anything that made it go the other way, they threw it away. And, through thousands of A/B-tested conversations, they started to zero in on something that worked.

And, now they’ve expanded it to: this can be applied to anything. You don’t have to be in their sub-community or have their theistic views to use it.

In the book, I talk about how there are techniques that work well on politics, techniques that work well on attitudes and values. And, then this one specifically works best with fact-based claims, things like, ‘Is the earth flat?’

How it works

It’s a stepwise method for having the conversation that we all should be having on any issue. Without going through an hour of trying to go through all the steps, I’ll give you sort of the quick version of that, which is: You open with a lot of the stuff we’ve talked about before–you open by establishing rapport. That’s that assuring the other person you’re not out to shame them. Assuring the other person, you’re not even there to change their mind. What you are there is to explore their reasoning. You ask them, ‘I would love to have a conversation with you in which we explore your reasoning on a topic and see what your views are and understand it better.’ Maybe: ‘You might shift, but you will have a deeper understanding of what we’re talking about.’ However, you want to frame it. Use your own language. You’re telling a person you’re going listen. And, most people will take you up on that offer.

I’m doing it right now. You asked if I would talk about something; you said you would listen; and I’m doing that right now. The podcast world depends on the fact that we’re all very willing to tell people what we think and feel about things.

So, give people that opportunity. You open the space for it. In this method, you ask for a claim. You ask for a very specific claim. It could be: Is the earth round or flat? And, then the person tells you–and then you repeat back the claim in the other person’s words. You make sure that you’re always using the other person’s words, because the big lesson in all of these techniques is that you are in their head, not yours.

You stay on their side. And, your job is to hold space for the other person to non-judgmentally listen and give them a chance to have a safety net, to metacognate and introspect.

And so you repeat the claim back to them. If they have definitions for terms, you ask for them; and you use their definitions, not yours. Like, if they say ‘the government,’ don’t assume that they’re talking about something from a civics textbook the way you look at it. They might be thinking of a group of reptiles in a round room talking about how they’re going to divide the country up to play golf. They have a different view of it. Let them–use their definitions.

And, then this is the big moment–and this is true across all of the conversation techniques. They all open in a pretty similar way with this space-creating moment. And, then they move to this thing that is magic.

It is asking the other person on a scale from zero to 10, or one to 100. The scale is a great way to get out of the debate frame and to assure the other person that this is not going to be a binary, right/wrong, black-and-white view of things. And, it even will work with the movie example you gave earlier, which is like, ‘Hey, Top Gun Maverick, what did you think of it?’ A person will say, ‘I loved it.’ That’s a very, like, black, white binary abstract. ‘Oh yeah? What would you give it on a scale from zero to 10?’

There is a moment when you ask a person a question like that, where they’ll go, ‘Oh, well,–that moment is, when they pop into that metacognating frame; and it could be like, ‘What did you think of this talk?’ ‘Loved it.’ ‘What would you give it on a scale of one to 10?’ ‘Oh, well–.’ That moment is what you’re looking for on any conversation topic.

[Kris: this is similar to asking someone to bet on their claim or handicap an outcome — the thinking switches from emotional to deliberate]

And you ask them, ‘What would you put it on a scale from one to 10, or zero to 10, or one to 100?’ Whatever they tell you, ask, ‘Why does that number feel right to you?’

This will encourage the other person to engage in reasoning–motivated reasoning most often. And, you let them do it. Let them do it the way they could do it. They’re going to come up with reasons that seem plausible for that position. But, what’s likely is that they’ve never done this. Not in this sort of like, ‘Please, present your reasoning to me’ kind of way.

It’s marvelous to witness a person saying–well, if they’re talking about Top Gun Maverick, they’ll have to start thinking, ‘Why do I have this emotion? Why was that so quick–why was it just like–it popped right in my head. What caused that to happen?’ And, they start coming up with reasons why that could be. Most of these are exploratory and they’re definitely going to be justifications and rationalizations.

Then, if you are actively hoping to get the person to see things closer to your perspective, if you’ve already done this for yourself and you know where you’re at on the number scale, ask the person how come they’re not in the other direction that you–appropriate to the issue. So, if I feel like–if a person says–if I say, ‘Is the earth flat?’ And, they say, ‘Absolutely.’ And, I say, ‘How certain are you of that from a scale from zero to 10?’ They say, ‘I’m probably a seven.’

Well, what you would ask is–first, you’d ask, ‘Why a seven?’ The next thing you’d ask–and this comes from motivational interviewing–is, ‘How come you didn’t say eight? How come you didn’t say nine?’ Because you’re asking how come they didn’t go all the way to 100% confidence. And, they must, on their own at that moment, generate their own counter-arguments against their position. But, you didn’t do that. No reactance. You’re not telling them what to think, feel. You’re not giving them your counter-arguments. It’s not your reasoning. They have to generate reasoning that counter-argues their position that will be new, that will be fresh, and that’ll be added to the collection of counterarguments in their mind. And, it will affect how they see things going forward.

With street epistemology, it’s more about just getting the person to examine: are they using a good epistemology to vet what they think and feel? So, after you have done all of these things with the number scales, you’d ask them what method that they used to judge the quality of those reasons that they presented. And, then you just stay in that space for the rest of the conversation as long as they’re willing to do it, and continue to listen and summarize and repeat and wish them well. And, try to make it so that you can have more than one conversation.

People do experience 180s in these moments sometimes. But, usually what happens is it’s by degrees, by increments. And, at the end of the day, the street epistemology people, they’ll tell you, ‘We’re not interested in changing people’s minds. We want people to just be critical thinkers. We want them to have more robust epistemologies.’ Which is sort of an even deeper way of changing a person’s mind. Getting a person to change their epistemological approach to the world is even more powerful than getting them to change just one belief, or attitude, or value.

Cognitive Empathy

This is a huge complex idea, but I think it all kind of plays into what we’ve been talking about previously, which is that sense of naive realism, where you just think that: ‘All people have to do is see the things that I’ve seen and they’ll naturally agree with the things that I think,’ if you don’t believe.

And it just takes–what it shows is a complete lack of cognitive empathy that other people come from completely different priors and experiences and social influences that affect the way they see–the way they form their beliefs–but also the way they interpret evidence.

An example of empathy failure:

I’ve seen this recently with a lot of these political ads that I’m seeing come across social media for places that I don’t live where they keep making these–I saw one today where someone was, like–they were in, like, the Midwest and they had these two people trying to survive in the desert. And, one of them is doing everything right because they’re a cowboy and they understand how to survive in the wilderness. And, the other one is a Senator who has no idea how to survive in the wilderness. But, the cowboy dies on Day 2 from a heart attack, because he doesn’t have good healthcare; and the Senator lives, because he’s got great healthcare, the Senator.

And the whole idea of the ad is: See. Senators have the healthcare that you don’t get to have. And, even though you’re a good, rugged individual who lives out there in the wilderness, who can survive in the wilderness, they’ll out-survive you because they’re taking away the healthcare you need.

That seems like a great political ad because it focuses on the identity of the individual that you’re approaching. But, that is an awful political ad based off of everything that I’ve learned in this domain, because it only feels like a great political ad to people on the Left–to liberals. It feels like a great ad for people who already have the values to which that makes you angry about that. It’s the inability to see that you can’t make an argument from your moral framework to a person who is in a different moral framework and expect it to land. You have to actually couch the argument in that person’s moral framework and their values. [ie “Moral Reframing”]

Lessons from Game Designer Raph Koster

I am going to be reading game designer Raph Koster’s book Theory of Fun pretty soon. For a preview, I listened to an old interview on the Think Like A Game Designer podcast with Justin Gary.

Link: https://www.thinklikeagamedesigner.com/podcast/2018/10/25/think-like-a-game-designer-5-raph-koster

Raph’s 25-year-old blog is a monument to design knowledge — it includes his writing, talks, and links to projects.

Raph is a creative force of nature. And this interview gets behind the madness. As always with my recaps, this is just what I wanted to write down for my own future reference but so much more is covered (there’s an especially great section about the use of simulations)

The Studio | London Art Classes

Ideating from scratch

When designing a game Raph will have a starting point. On one end of the spectrum might be a particular loop or mechanic the game hinges on. At the other end of the spectrum, he might start with the type of experience he’s looking to design. His approach to tabletop games tends to start with the mechanics and for video games from the experience. I excerpted the following because he decomposes the act of swimming into game mechanics off the top of his head in the interview. It was a neat example of how native this thinking clearly has become for him:

In my board game work, I find myself biased towards the mechanical. It’s unusual for me to start from the other end of the board games. But in video games, I often start from the experiential end. My goal is to establish what I know at one end and then use it to jump to the other end to draw conclusions. For example, if I start from the experiential end and I want to make a game about swimming, I think about the experience of swimming for me. There are different strokes. There’s the fear of drowning when you start to learn. Rhythm is crucial to swimming, as is breath management. The concept of a breath might be a resource. It could be something consumed periodically, but there might also be an exhaustion meter that decreases over time, limiting your breath. Different strokes might have different breath expenditures. If I decide to create a tabletop game, I think mechanically. I could set up a board with a race structure appropriate for swimming, perhaps with themes like sharks chasing or diving challenges. I’d play a game of resource management to get the necessary strokes, maybe using cards or tokens. If I were designing a digital game, I’d focus on rhythm, possibly incorporating a timing aspect and still manage resources of breadth and endurance. Different strokes would offer varied trade-offs. My aim is to establish two foundational ideas and move inward, paying attention to both. Ideally, they meet in the middle. If I have an abstract idea, like a deck of cards that “moves” me, I might not end up with a swimming game. It could fit another context but remain mathematically sound. It could be rules for moving cavalry in a supply chain. It’s crucial to consider both ends because it helps generate ideas that lead to a cohesive design.

Having a wide array of influences and skills

I’m always fascinated by and strive to understand the universal principles that apply to the creative process. It doesn’t matter whether you’re making games, poetry, art, or a movie, I believe there are common threads in how you approach creative work. You have such a polymath background, maybe you can speak to that.

My education and background is eclectic, with a consistent focus on the arts. I took studio art classes beyond the college level and I’m a musician. I play multiple instruments and studied music theory and composition in college. Interestingly, the one thing I do but never formally studied is programming. I have a Master of Fine Arts in Creative Writing and draw on all of these disciplines regularly. It’s challenging for me to imagine not being a jack of all trades or how I’d approach games if I weren’t integrating all these skills. I also frequently use Excel. A primary reason I enjoy game design is because it allows me to utilize various skills in one project.

Getting better — what does it mean to practice?

What’s the equivalent of “practicing scales” for other creative work?

I consider the practice of all those things I do as being very similar. I use the same habits for all of them. I made a list of them once in a blog post, which I think was called “practicing the creativity habit“. First was, whatever the activity is, do it regularly and make it a habit. So part of that is having the tools near you at all times. In the room I work out of, there are about 20 musical instruments within five feet, a complete art studio, a recording studio, and a game design reference shelf. Not actual games, but books about games, economics, interface design, and other topics related to games. For board games, I have a prototype kit with hundreds of dice, wooden bits of different shapes, and about 30 or 40 different decks of cards. The first thing is to make it a habit. Second, have the tools close at hand always.Third, give yourself constraints. I try to do that regularly. If it’s guitar, I might find five jazz chords and learn them, then write a song using those chords until I understand them. I picked up this habit from studying art and poetry. There are traditional poetic forms like sonnets, Villanelles, and haikus. In a writing workshop, we set ourselves the challenge of writing a poem using every single traditional form. In game design, it would be trying different game types. I haven’t succeeded at it for games, but that’s not the point. It’s about understanding design patterns. This approach applies to everything I work with, be it music composition, writing, or drawing. It’s a common underlying principle. It’s like working out — you need to rotate through the different muscle groups. 

Intuition is pattern-matching against experience subconsciously

This is illustrated by an example from one of the cognitive science books on my shelf: the firefighter intuitively knows a structure is going to collapse. If you ask them why, they often have trouble explaining. I believe the process of conducting formal analysis of numerous games or seeking NP hard problem categories or compiling a pattern library and trying to internalize it helps strengthen our intuition. The exercise of building games around patterns serves as practice for honing this intuition. I may not always explain why I opt out of a conflict early, but I just intuitively sense it won’t work. The key is recognizing this earlier. I still believe 90% of ideas are shit but now, I discard them even before jotting them down, often when they’re just scribbles.

Nuance about the role of games in education

The changes over the years have involved the “chocolate covered broccoli” concept, where something fun is wrapped around an academic task. It’s clear this approach wasn’t effective. We’ve come to understand that games teach in specific ways that are well-suited for certain subjects but not for others. Games motivate players best through intrinsic motivation. Players choose to learn and take on tasks because they want to, with the game guiding their objective. For instance, instead of making a game to directly teach math, you create a game where players have a goal they wish to achieve. This might lead them to discover that understanding a certain type of math is the solution. They then learn it out of their own motivation. This is a realization that educational game design has recognized over time. As for games with broader themes, they can reflect social structures, human interactions, economics, politics, and other vast topics. While there’s an abundance of narrative-driven or viewpoint-based games out there, game systems can be informative as well. For instance, Sim City faced criticism for presenting an overly optimistic view of public transit and its associated challenges.

You can bias your game systems to convey specific lessons. It’s important to recognize that your game systems inherently teach lessons, intended or not.

Game-playing trains your “systems thinking”

Finding real world systems and abstracting them or boiling them down to their essence isn’t actually a very common skill. Games can teach people how to do this. The idea involves setting constraints, modeling real systems, and allowing people to experience them within a game context to understand them deeply. It provides an opportunity for individuals to experiment with these systems, unlike in real life where, for example, you only get one shot at lifetime earnings. Playing a game that emulates this system offers lessons. This is applicable to various scenarios, such as political engagement. There should be games that allow players to experiment with political engagement methods, helping them discern more effective strategies. This principle holds true in many areas.

Kris here…yea, I’ve made this point repeatedly over the years.

In Let Your Kids Play Boardgames I said this of the game Quacks of Quedlinburg:

Quacks is a bit like a deck builder. It’s known as a bag builder but with a don’t-bust-press-your-luck mechanic. To most of you, that means nothing but for the remaining, you should know this an outstanding game. It’s fun, and while seasoned gamers won’t like this necessarily, it has enough luck to allow a first grader to compete with an adult. I found myself thinking quite a bit about the value of the “options” (they’re actually chips representing ingredients in a potion recipe) in the game and their respective costs. The concepts of theta, volatility, and vega would be visible to someone with a finance background if they looked past the game skin.  An engineer would see this game as a very pure simulation (most likely AI) based problem especially since the game has no trading interactions.

In Practice Second Gear Thinking I write:

We must identify second-order effects. In the options world, the “greeks” are sensitivities. Delta is the option’s sensitivity to the underlying. Gamma is a second-order sensitivity that describes how an option’s delta changes with respect to the underlying.

But this topic is everywhere. If a company sells more widgets it makes more profit. But second-order effects mean attracting more competition or saturating a market. Every satisfied customer is one less customer that needs satisfying. So if I build a model of profitability based on units sold, when does the function inflect? When does opportunity fade into unsold inventory?

A fun way to think about second-order sensitivities is playing “engine builder” boardgames like Dominion or Wingspan where synergies between your cards lower the marginal costs of later actions2. In essence, the cards have gamma based on how you stack them. Every time I use a card it might increase my odds of winning by X. That’s the delta or “benefit per use”. But the delta itself increases with synergy, so as the game progresses, you get more delta or benefit/use ratio, from the same card

In Greeks Are Everywhere I write:

One of the reasons I like boardgames is they are filled with greeks. There are underlying economic or mathematical sensitivities that are obscured by a theme. Chess has a thin veneer of a war theme stretched over its abstraction. Other games like Settlers of Catan or Bohnanza (a trading game hiding under a bean farming theme) have more pronounced stories but as with any game, when you sit down you are trying to reduce the game to its hidden abstractions and mechanics.

The objective is to use the least resources (whether those are turns/actions, physical resources, money, etc) to maximize the value of your decisions. Mapping those values to a strategy to satisfy the win conditions is similar to investing or building a successful business as an entrepreneur. You allocate constrained resources to generate the highest return, best-risk adjusted return, smallest loss…whatever your objective is.

Games have mine a variety of mechanics (awesome list here) just as there are many types of business models. Both game mechanics and business models ebb and flow in popularity. With games, it’s often just chasing the fashion of a recent hit that has captivated the nerds. With businesses, the popularity of models will oscillate (or be born) in the context of new technology or legal environments.

In both business and games, you are constructing mental accounting frameworks to understand how a dollar or point flows through the system. On the surface, Monopoly is about real estate, but un-skinned it’s a dice game with expected values that derive from probabilities of landing on certain spaces times the payoffs associated with the spaces. The highest value properties in this accounting system are the orange properties (ie Tennessee Ave) and red properties (ie Kentucky). Why? Because the jail space is a sink in an “attractor landscape” while the rents are high enough to kneecap opponents. Throw in cards like “advance to nearest utility”, “advance to St. Charles Place”, and “Illinois Ave” and the chance to land on those spaces over the course of a game more than offsets the Boardwalk haymaker even with the Boardwalk card in the deck.

In deck-building games like Dominion, you are reducing the problem to “create a high-velocity deck of synergistic combos”. Until you recognize this, the opponent who burns their single coin cards looks like a kamikaze pilot. But as the game progresses, the compounding effects of the short, efficient deck creates runaway value. You will give up before the game is over, eager to start again with X-ray vision to see through the theme and into the underlying greeks.

[If the link between games and business raises an antenna, you have to listen to Reid Hoffman explain it to Tyler Cowen!]

Advice for aspiring game designers [Kris: I think much of this applies to anyone whose job is to communicate — which is basically everyone]

The first piece of advice is to make games. I understand many are familiar with this advice, but it’s valid: make a multitude of games and practice consistently. The second piece of advice, especially for aspiring game designers, is to become intellectually curious. I haven’t met any outstanding game designers who aren’t. Be a voracious reader and be open to exploring different fields. Be genuinely curious. These two traits alone can take you a long way in the game design world.

Well, ok. But, given Raph’s background, it seems incomplete for me to not quote uber-successful game designer Sadie Green’s character in the novel Tomorrow, Tomorrow, and Tomorrow responding to a rando who asks her “How did you get into making video games?”

Sadie hated answering this question, especially after a person had told her that he hadn’t heard of Ichigo. “Well, I learned to program computers in middle school. I got an eight hundred on my math SAT, won a Westinghouse and a Leipzig. And then I went to MIT, which by the way is highly competitive, even for a lowly female like myself, and studied computer science. At MIT, I learned four or five more programming languages and studied psychology, with an emphasis on Judic techniques and persuasive designs, and English, including narrative structures, the classics, and the history of interactive storytelling. Got myself a great mentor. Regrettably made him my boyfriend. Suffice it to say, I was young. And then I dropped out of school for a time to make a game because my best frenemy wanted me to. That game became the game you never heard of but yeah, it sold around two and a half million copies, just in the US, soooo…”. Instead, she said, “I like to play games a lot, so I thought I’d see if I could make them”.

Specific content recommendations

Jerry Seinfeld Chats With Tim Ferris

This Seinfeld/Ferris interview is great:

Jerry Seinfeld — A Comedy Legend’s Systems, Routines, and Methods for Success (#485)

There are good notes here and I’ll list my favorite lessons despite the feeling that you should really take the whole thing in bc the delivery is as good as the lessons.

  1. He writes every day like a job. Jack White (another artist I’m a big fan of has a similar view). Inspiration comes from perspiration kinda thing. It’s not “eureka” moments. Writing sessions should not be open-ended, that’s torture. You should have an end time to reward yourself.

  2. The key to writing is learning to switch between these two states: When you are writing, treat yourself as a baby in need of care and love. Acknowledge that creating/writing is the most difficult thing in the world. The day after, you become a ruthless critic It’s 95% re-write.
  3. Writing sessions feel very hard, but he knew he had to do it anyway (and realized this at a young age). Jerry attributes his success to his ability to stick with it. Today he’s so used to the frustration he doesn’t even notice it.
  4. For Jerry, there can be no failure in going up on stage. Even if for him it’s a 4 out of 10 show, he still counts it as a win. This is part of nurturing and rewarding yourself as a creative.
  5. “Never talk to anyone about what you wrote that day. You have to wait 24 hours to ever say anything, because you never want to take away that wonderful, happy feeling that you did that very difficult thing that you tried to do, that you sat down and wrote…Have you ever heard you never tell people the name that you’re going to give the baby — until it’s born? Bc they’re going to react, and the reaction is going to have a color. And if you’ve decided that’s going to be the baby’s name, you don’t want to know what they think”
  6. Mind and body are intertwined deeply. Exercise is the closest thing we have to a panacea. The stress from weight training makes your nervous system more resilient. We need to be properly exerted. “a tired dog is a happy dog”
  7. Weight-training builds your constitution. “You’re deteriorating. You’re just trying to bend that curve a little bit. I’m 66. I shouldn’t be performing at this level at 66. I should be over. So you have to cheat the biology.”
  8. Repetition & systems “It’s like you’ve got to treat your brain like a dog you just got. The mind is infinite in wisdom. The brain is a stupid, little dog that is easily trained. Do not confuse the mind with the brain. The brain is easy to master. You just have to confine it.” Systemization is needed to harness talent:Image
  9. He measures and gamifies to direct his progress. But not on the creation process:Image
  10. Jerry is confrontational so he doesn’t let things fester. “I feel like if you break the human struggle down to one word, it’s confront. And so, I kind of approach everything that way.”

  11. Survival is success. And if he could have a billboard it was say: Just Work

    Image

  12. If Jerry could pass along something to his kids it would be ethics and boldness

A Few Excerpts from Dan Carlin on Lex Friedman

I recently listened to my first episode of Dan Carlin’s Hardcore History — a tour of the transatlantic slave trade entitled: Human Resources. Dan’s story-telling and research shine in this nearly 6-hour episode. He deserves all the accolades he gets. The style, quality and nuance of his work is well-advertised, I’m just late to the party. He immediately jumped into my favorite creators.

As a fan of the Founder’s podcast I found an interview with its host David Senra to be as compelling if not more than the books he highlights (a high bar), so I decided to hunt down interviews with Carlin. The first one I clicked on with Lex Friedman did not disappoint. I include 4 excerpts that stood out to me but most of the interview was enlightening and wide-ranging so I wouldn’t stop at these excerpts.

3+ hour interview (Lex Friedman on YouTube)

I used GPT-4 to clean up sections of this transcript: https://www.happyscribe.com/public/lex-fridman-podcast-artificial-intelligence-ai/136-dan-carlin-hardcore-history

An example of how propaganda can scramble your beliefs in a way that creates collective distortions that are hard to see

[Carlin is a war historian and while he admits to his bias towards individualistic ideals “I’m famously one of those people who buys in to the ideas of traditional Americanism”, his characteristic nuance is well-displayed in his deep skepticm of the “military industrial complex” and how its inclination towards self-preservation as an institution often exerts undue influence in when America looks at its menu of choices]

“Many people living today seem to think that patriotism requires a belief in a strong military and all the features we have in the present. However, this is a departure from traditional Americanism, which viewed such elements with suspicion during the first hundred years of the republic. They saw them as foes to the very values that Americans celebrated. The question arises, how could freedom, liberty, and individualistic expression thrive with an overarching military always engaged in warfare?

The founders of this country examined examples such as Europe and concluded that standing militaries or armies were the enemy of liberty. Today, we have a standing army deeply woven into our society. If one could go back in time and converse with John Quincy Adams, an early president of the United States, and reveal our current situation, he would likely find it terrible and dreadful.

Somewhere in our history, Americans seemed to have strayed from their path and forgotten their founding principles. We have successfully combined the modern military-industrial complex with the traditional benefits of the American system and ideology, so much so that they have become entangled in our thought process. Just one hundred and fifty years ago, they were seen as polar opposites and a threat to each other. When discussions arise about the love of the nation, I harbor suspicion towards such sentiments.

I am wary of government and strive hard not to fall prey to manipulation. I perceive a substantial part of what they do as manipulation and propaganda. Therefore, I believe a healthy skepticism of the nation-state aligns perfectly with traditional Americanism.”

The problem with dictators or strongmen even if they are wise and benevolent

“The challenge in a system such as a strongman system is the question of succession. When you have someone who can control and navigate the ship during a violent storm, if you’re not establishing a system that can function without you, then the severe instability and the dreadful future that you justify the strongman for is only postponed. Unless he’s actively building the system that will survive him and allow successors to carry on his work, you’ve merely created temporary stability. It’s the same problem that occurs in a monarchy.

In a monarchy, you have a king who might be good or perceived as good, but he will eventually hand over his duties to someone else. However, the system doesn’t guarantee a smooth transition because no one has really worked on it. For instance, you would need to inform me if Putin is establishing a system that can survive him and that will maintain the stability that the Russian people appreciate him for, even after he’s no longer in power.

If the oligarchs simply assume control afterward, one could argue that there were 20 good years of stability. However, if we consider the metaphor of a ship of state, the person steering the ship, from the Russian perspective, may have done an excellent job, but the challenges still exist and he won’t be in command indefinitely.

Therefore, it seems logical to assume that his responsibility is to ensure there’s a successor who can continue to steer the ship for the Russian people after he’s no longer there.”

Lex asks how we will “destroy ourselves”. Carlin gives a framework for handicapping what calamity will undo us.

Lex: If you were to wager on the method in which human civilization collapses, rendering the result unrecognizable as progress, what would be your prediction? Nuclear weapons? A societal breakdown through traditional war? Engineered pandemics, nanotechnology, artificial intelligence, or something we haven’t anticipated? Do you perceive a way humans might self-destruct or might we endure indefinitely?

My perspective is primarily influenced by our ability to unite and focus collectively. This informs my estimates of the likelihood of one outcome versus another.

Consider the ’62 Cuban missile crisis. We faced the potential of nuclear war head-on. That, in my view, is a hopeful moment. It was one of the few instances in our history where nuclear war seemed almost certain. Now, I’m no ardent Kennedy admirer, despite growing up during a time when he was almost revered, especially among Democrats. However, I believe John F. Kennedy, acting alone, likely made decisions that spared the lives of over a hundred million people, countering those around him who preferred the path leading to disaster.

Reviewing that now, a betting person would have predicted otherwise. This rarity underpins our discussions about the world’s end. The power to prevent catastrophe was in the hands of a single individual, rather than a collective.

I trust people at an individual level, but when we unite, we often resemble a herd, degrading to the lowest common denominator. This situation allowed the high ethical principles of one human to dictate the course of events.

When we must act collectively, I become more pessimistic. Consider our treatment of the planet. Our discussions predominantly center around climate change, which I believe is too narrow a focus. I become frustrated when we debate whether it’s occurring and if humans are responsible. Just consider the trash. Disregard climate for a moment; we’re harming the planet simply through neglect. Making the necessary changes to rectify this would necessitate collective sacrifice, requiring a significant consensus. If we need around eighty-five percent agreement worldwide, the task becomes daunting. It’s no longer about one person like John F. Kennedy making a single decisive move. Therefore, from a betting perspective, this seems the most likely scenario for our downfall as it demands a massive collective action.

Current systems may not even be in place to manage this. We would need the cooperation of intergovernmental bodies, now largely discredited, and the national interests of individual countries would need to be overridden. The myriad elements that need to align in a short span of time, where we don’t have centuries to devise solutions, make this scenario the most probable simply because the measures we would need to undertake to avoid it appear the least likely.”

[a later thread that rounds out his thinking on this]

“Returning to our primitive instincts, we are conditioned to address immediate and overwhelming threats. I hold a considerable amount of faith in humanity’s response to imminent danger. If we were facing a cataclysmic event such as a planet-threatening explosion, I believe humanity could muster the necessary strength, empower the right individuals, and make the required sacrifices. However, it’s environmental pollution and climate change that pose a different challenge.

What makes these threats particularly insidious is their slow development. They defy our innate fight or flight mechanisms and contradict our ability to confront immediate dangers. Addressing these problems requires a level of foresight. While some individuals can handle this, the majority are more concerned, understandably so, about immediate threats rather than those looming for the next generation.

Could we engage in a nuclear war? Absolutely. However, there’s sufficient inertia against this due to people’s instinctive understanding. If I, as India, decide to launch an attack against China, it’s clear that we will have 50 million casualties tomorrow. If we suggest that the entire planet’s population could be extinguished in three generations if we don’t act now, the evolutionary trajectory of our species might hinder our response.”

Will the US tear itself apart in a second civil war?

Lex: What’s the way out of this, is there some hope to avoid something, and I hate to use the terminology, but something that looks like a civil war? Not necessarily a war of force, but a division to a level where doesn’t any longer feel like a United States of America with the emphasis on “United”. Is there a way out?

I read a book a while back. George Friedman, the Stratfor guy, wrote it. It was called “The Next Hundred Years”. I remember thinking I didn’t agree with any of it. One of the things he might’ve said in the book was that the United States was going to break up. Something stuck in my memory about that.

Some of the arguments were connected to the differences we had and the fact that those differences are being exploited. We talked about media earlier and the lack of truth. We have a media climate that is incentivized to take the wedges in our society and make them wider. And there’s no countervailing force to help.

There was a memo from a group called Project for a New American Century, and they took it down. But the Wayback Machine online still has it. It happened before 9/11 and spawned many conspiracy theories because it suggested that the United States needs another Pearl Harbor type event. Such events galvanize a country that, without them, is naturally geared towards pulling itself apart. These events act as the countervailing force that otherwise is not there. If that’s true, then we are inclined towards pulling ourselves apart.

The media environment profits from widening those divisions. I was in talk radio, and there were those who used to be upset with me for not playing into this. We would have intense discussions after broadcasts, with program directors emphasizing heat. They wanted heat not for political reasons, but to attract listeners and engagement. Because of the format’s constraints, you don’t have a lot of time. They once told me the audience needs to know your stance on every issue within five minutes of turning on your show. This system is designed to pull us apart for profit.

That’s one example of many in our society that function in that manner. The Project for a New American Century document suggests we’re naturally inclined towards disunity. I think that’s what George Friedman’s book was suggesting, which I disagreed with at the time.

In answer to your question about civil wars, it’s different now. We don’t have a clear geographical division like before. Now, we’re divided within communities, families, and voting districts. So you can’t disengage. We’re stuck with each other.

If there’s a civil war now, it might resemble the late 1960s and early 1970s with bombings and domestic terrorism. You don’t even need a large chunk of the country pulling apart 10 percent of people who think it’s it’s the end times can do the damage, just like we talked about terrorism before and a can of gas and a big lighter. 

Terrorism doesn’t need a particular origin or agenda. It could be someone upset about election results. If we’re looking at probabilities, everyone has to behave for society to work. Only a few need to act out for things to go sideways. For every action, there is a reaction, all they have to do is start the retribution cycle. And there’s an escalation. It creates a momentum of its own, which leads fundamentally, if you follow the chain of events down there to some form of dictatorial government as the only way to create stability. You want to destroy the republic and have a dictator? That’s how you do it. And there are parallels to Nazi Germany, the burning of the Reichstag, etc.

Allison Bishop On The Growth From Failure Podcast

My wife Yinh’s podcast Growth From Failure is in its 5th year. Her guests are extremely wide-ranging and rarely found on “the circuit”. Many of you know her and would agree — her multi-standard deviation superpower is a genuine interest in people’s individual stories. It’s a power that is not simply recognized by people she meets — it’s felt. You feel like she’s listening to you because she listens with her whole self. Some may wish for an invisibility cloak or a crystal ball. I’d take her ability to listen (and for every keto dude working on his abs — I’d be willing to bet that this listening skill is the OP aphrodisiac — the problem is it’s rarer than a six-pack.)

She doesn’t need me promoting her pod but yea you should check it out if you want to break out of your normal pod routine especially if you get the awkward sense that you’ve slotted too many quarters into the same dudes-who-use-business-idioms-like-open-the-kimono merry-go-round.

That said, if I promoted every episode I’d dilute my recommendations. I restrain unless the interview is:

☑️ too compelling to not share. Examples: Elizabeth Shaughnessy, founder of the Berkley Chess School (one of my favorite humans) or T-Vu, engineer and rapper (maybe my favorite GFF episode).

☑️if they intersect with quant finance. Past in this category include interviews with my former colleagues Kelly Brennan, partner at CitSec, and options trader Tina Lindstrom or power trader Noha Sidhom.

Today, I’m boosting her latest episode because it checks both boxes.

🎙️ALLISON BISHOP – COMPUTER SCIENTIST, WRITER, COMEDIAN. PRESIDENT AND CO-FOUNDER, PROOF TRADING (Growth From Failure)

Yinh’s intro:

This is the story of Allison Bishop, president and co-founder of Proof Trading, an institutional equities execution platform. In this episode, we cover Alison’s journey from aspirations in creative writing, which had a rejection and led her down a path that was much more quantitatively oriented than she thought. That led her to Masters and PhDs, in math, computer science, and cryptology.

I learned so much from her like the branch of math called combinatorics, which I’ve never heard before. And also the practical applications of cryptology and computer science and for the first time, finally, understanding how those were actually used.

But more importantly, I learned about controlling how you set people’s expectations and reclaiming that power, either emotionally or physically. Allison literally changed the way she moved in the world.

Select excerpts:

On her transition into math after being rejected from the hallowed Princeton Creative Writing path, her entire reason for choosing Princeton in the first place:

I was devastated, it was the entire point that I was here. And at the time, I was also supposed to be just getting rid of my general distribution requirements. One of those was to take a math course. And I refused to take calc, which was what most people are taking. I’d taken calc AB in high school, and I find it kind of boring. And so they’re like, you could just take Calc II.

Meh, what else you got?

I ended up taking number theory because I thought it was the “physics for poets” of math. It is not. It’s a foundational course in cryptography. And it was a course math majors were taking and it set me on this very different path of learning that I liked math and that math could be creative. But it happened because of this simultaneous confluence of events that I got rejected from Creative Writing, and I refused to take calculus.

I also did take the “physics for poets” version at Princeton. I thought it was great. It was really philosophical and insightful, and I quite enjoyed it. But yeah, the math class was not at all that. It was a serious math class and I also had no conception of what Princeton math is. What the Department was or what that meant. And I’m really glad I didn’t know because I think I would have found it very intimidating. I got pretty deep into this process as a math major before people started, like telling me, you do know, this is one of the best math programs in the world. Oh, no, I didn’t know that. You know, the guy teaching linear algebra is a Fields medalist. What’s the Fields Medal? And it was just very perplexing to the people around me how I got there because there are usually about 60 to 100 people every year applying to Princeton for math and in my year, only 15 graduated with that major. I ended up being like this wild card person who did not know what was going on, but was in for the ride.

What she found creative in math

It was the first time I actually got to write proofs. This concept of using math not as a vehicle to just calculate something, but as a way of reasoning about the world. That was new to me because I feel we lose so many opportunities in the way we teach math at the elementary, middle school and high school level. Here’s the procedure and you do it. If we’re lucky — “here’s what that means”.

But there’s not “here’s how people came up with it. Here’s the history of it, or here’s the question from first principles, and have you come up with the procedure?” So the first time having these open-ended questions be asked, and then having to reason about it myself, assemble proofs out of the building blocks that we’ve seen in the class.

The one that I think fascinated me at first, which is actually a relatively simple one that you can teach at the middle school level, is a proof that there are infinitely many prime numbers. The fact that you could prove there are infinitely many of something as complicated as prime numbers. What’s fascinating to me, and the creativity that goes into this, okay, how do I reason about this? How do I create a procedure to always produce a new prime outside of the set of primes that I produced so far? That constructive building process was very appealing to me.

But when you’re writing a proof and realize how creative it is, but then you’re going through it again and it’s still the same answer does it then feel black and white, and then QED?

Not really. And I think this is something that mathematicians are at varying degrees of denial about, because there is this process of peer review that happens when we prove new theorems and people put them out. And it’s highly nontrivial to go through and check someone else’s proof and make sure everything makes sense. And in some sense, when we can reduce each little step to this logic axioms, then you can check that we mostly gain confidence. But the process of putting those things together really shapes the theorems that you’re proving. So it’s not really that there’s this a universe of facts. And then there’s these proofs that get attached to the facts. And then as long as we have a proof attached to the fact that we can check we can move on. There’s so many different things that we could reason about, or relationships between objects that we could try to prove theorems about so much more of the interesting stuff goes into the human process of what do we find worth studying? What questions do we ask?…I think mathematicians are a little bit reticent to admit how subjective the process of curating what’s important and what things we study is, because the process of checking a proof is already nontrivial, but is solvable in some sense. But the process of deciding which proofs are worth doing, and which questions are worth investigating is where most of the fun stuff happens.

From math to computer science

Math separates into two sub-fields. For me, at least the way I think about it, some of them have very complicated objects, and then you prove relatively simple theorems about them. So all the complication goes into the objects themselves. And so there’s things like topology, which is about shapes in the world, and things like that. And algebraic geometry. And combinatorics is more like the objects are pretty simple. Graphs, you’ve got dots, and you’ve got lines connecting the dots are things but then the theorems and the patterns that you study on them are complicated, which is much more aligned with computer science.

I ended up wandering from math to computer science. So as an early PhD student at Austin, I would go around to the different mathematicians in the department and try to learn about their research, I would always ask them, “What is the application of this in the world?” And I got a range of answers from there aren’t any applications of this in the world to tons of applications to other areas of math. And so I was pretty underwhelmed by the potential impact of the things that were being studied. And there’s a lot of fundamental research that happens. And we don’t know yet how it’s gonna get applied. And it eventually gets applied. And I think this stuff is really cool. But from the perspective of I have one life, and I like being very people-facing and doing things that impact people directly, it wasn’t really compelling enough to me. So I started wandering over to the computer science department.

It’s always a joke I make with mathematicians, “what are you guys doing over here?” It’s all the same stuff. But it’s got much better research grants in computer science, and it’s much more potentially impactful and relevant, pretty directly. So I ended up switching halfway through my PhD to be in the computer science department, which meant doing all of their requirements, again from scratch. So I basically did two PhDs and left with one of them. Totally the wrong way to do it. But I ended up in a good place sort of finishing my PhD with an emphasis in cryptography in the computer science department.

[Skipping over a discussion of the 2 major branches of cryptography which solve the same problems with different tools but remain silo’d for complex reasons as well as her human interest in the field]

While I’ll also skip how she started working with IEX before starting Proof Trading I found the transition story useful:

Cryptography and finance are similar fields — they both try to scare people away with enough acronyms. So I was somewhat comfortable at that point, being the person who just asked everyone questions all the time. And so my strategy on the trading floor was just sitting in the middle of all these people and whenever they their take their headphones off, I would ask them a question. “Hey, I’m wondering what this graph means. Can you come over here?” I was just shameless about asking questions. But I think also just having that prior experience of learning a jargon-heavy field, knowing that the fact that I didn’t know what the things were, didn’t mean I was stupid. And it didn’t mean it was going to be hard. It just meant that I had to ask, although I do think finance makes it unusually tough.

I’ve also been documenting some of my process. Proof has put out a market structure primer, which is basically my writing down the things that I didn’t know, and therefore asked and putting that into a form that hopefully helps other people. Because we do think that, unlike cryptography, where there are textbooks and there are public facing things and surveys that are helpful, in finance, you’re piecing this together from different people’s memories. I’m in the middle of the trading floor asking “What does this four-letter code mean on this trade flag?” There are no public references for so much of this. So I do think as a field, we need to do a better job of giving people friendlier entry points, but the people on the trading floor at IEX, around me were great at just having the patience to answer a million questions.

What problem is Proof Trading trying to solve?

The biggest surprise to me learning about the stock trading system was that the entire purpose of stock trading is to provide public information about prices. That’s the whole reason for being of the stock market. And yet, absolutely, every structure around that is completely opaque, which I just think is ludicrous. I will make the same argument with people about pay transparency, we need better insight into where these prices are coming from, for exactly the same reasons that we need public price discovery for stocks, but taking it specifically to the broker layers.

What we saw from our seat at IEX, was that we were trying to build tools that would ultimately help long-term investors on the buy side, but we didn’t have direct access, because that’s not who IEX is — its customers are brokers. And every time we’d ask a question, well, why are brokers doing this? Or why are brokers acting this way? There’s no insight available into that because brokers are this black box.

Thinking about this coming from cryptography, cryptography is all about keeping secrets, but they are much less secretive than this. Because fundamentally, whenever somebody comes to the cryptography community and says, I have a cool new way of encrypting data but I can’t tell you how it works, we laugh at that person, then we break their system immediately. Usually, “I can’t tell you how it works” means it’s not going to stand up to scrutiny. And the reason we believe in the encryption algorithms that we have is that they’ve been exposed to decades of people trying to break them and improving them and all these things. So it seemed crazy to me that the science of electronic trading algorithms of how to round certain ways or how to build or design a schedule, or how to optimize to certain goals for order performance, that that was all individualized inside these black boxes, instead of benefiting from an open science culture. It seemed completely handicapped to me as a scientific field and completely unnecessary.

There are things that need to be protected and confidential, like, what stock are you trading and when are you trading it. But if I’m claiming to you that I have a way of taking big trades and breaking them up into pieces in the market, so that they blend in with the noise, if they really blend in, then I should be able to tell you my mechanism, and it should still work. And if I’m forced to expose that mechanism, it should open up all of the surface for public science and collaboration that should help us get much better outcomes. So I’m a big believer in making science public, whenever there’s not a great reason to do otherwise, rather than secrecy being the default.

So one of the main things we wanted to solve for as a broker was to make as much of our decision-making process public as we could. So to make us more accountable, to open that up as a surface for collaboration with our clients that if we tell them what we’re doing, they can say, Oh, well, that’s not aligned with our goals in this case. And that’s a much more rich surface for communication and improvement than just saying, Here’s the box, you can use it or not. So it’s kind of our hope that bringing a scientific process into the open in this area would really jumpstart progress toward better solutions.

[Skipping a balanced discussion of the challenges they face as a remote-first company]

Can you give me an example of what Proof Trading does for a client? (I highlighted the refreshingly honest part of the answer)

Once a client has decided they want to buy a large amount of stock or sell a large amount of stock, our job is to figure out how to split it over time and space into pieces, so that the market doesn’t disproportionately react. How do we make their total activity blend in with the random activity of the market in such a way that we can get done what they want to get done without the price going up, because they’re buying or going down, because they’re selling so it’s reducing impact relative to getting the trade that you want? That is the value that we’re looking to add.

One thing that’s very tricky about this process is that the market is very noisy. So there’s a lot of noise in the data performance. And it’s very hard to compare two algorithms, apples to apples, because they get different kinds of orders and different market conditions, huge sample sizes. So it’s a very tough sales position. I can’t point to a single order. “Look, this is the amount of money we saved you.” And people seem to expect that, which seems super weird. When we go into the sales call it’s “explain to me how many basis points your algorithm is going to save me versus my competitors.” One, your competitors won’t tell me anything about their performance. So how would I know that? And two, I can’t even measure my own performance cleanly, because it’s a function of all this noise. And so I get a lot of befuddled expressions on the other side, it’s like, well, then what are you selling?

We think we’re better. We just also think this is really hard to show and I’m not going to show you some half-baked thing.

Addressing her recovery from a deeply personal trauma:

As a growth moment, it was pretty significant because I was having symptoms of depression and PTSD as a young faculty member. And what was strange to me about it was that my ability to function and do my job was the last thing to go. I was not sleeping, I was not eating well, everything was off. And yet, I was still publishing papers and teaching classes on paper, everything looked fine. And I had to convince myself that it was bad enough to heal, just give myself permission to heal.

And I think one of the things that surprised me about that process was it was less of the growth — it was more, almost shedding a limb, just completely resetting. And that was actually the time a lot of people have asked me about. I started dyeing my hair, blue and purple, and I started getting tattoos that were meaningful to me and changing my appearance. I felt like I was walking through the world looking like this person that I wasn’t able to be anymore. And having people react to her the same way they used to react to her was stopping me from healing, people would expect things in me and I would do them because that’s what I’d always done. And so I needed to find a way to change what people expected of me. And so I think one of the biggest things was reclaiming my physical presentation and space. That was also when I started learning, boxing, and just changing the way I move in the world.

So for me, I think the biggest growth moment was realizing that sometimes you need to reset, and you need to reclaim some of the things that are in the way of that progress and giving myself permission — also to quit, as a faculty member and not say it is a failure. I think a lot of academics think of leaving academia is always intrinsically a failure. It was a continuation of my journey, the willingness to be seen as a failure. And that sense, I think was really important.

And I loved this part:

Realize that we have more control over setting people’s expectations for us. And I think it takes a certain amount of separation from people’s reaction to you just realize that that lever is there to some extent. And for me, it really came out of a place of necessity. And from feeling it in myself, I had to wake up in the morning and look in the mirror and see this person that I didn’t feel existed anymore. And that was this weird, disconnecting feeling.

This was always the biggest thing I tell people thinking about public speaking or comedy, is that if you make yourself laugh, it’s contagious. If you’re getting on stage, and you want to convey an emotion, or you’re pitching your startup or whatever, if you feel it, the audience will feel it. And so it’s getting to the point where you feel good about what you’re doing, or you feel excited about what you’re doing is 90% of it. And the rest is just icing on the cake.

Check out the full episode to hear about how Allison defines success, what she learned from her blunder as an 18-year-old intern working on the Mars Rover with the JPL (Jet Propulsion Lab), her boxing and comedy outlets and how her professor Jordan Ellenberg (my notes on his book) inspired her to embrace her varied interests and her recent acceptance to a creative writing MFA program!

Allison also founded a conference called CFAIL: Failed Approaches and Insightful Losses in Cryptology.

It’s an annual event where we give people a platform to talk about research that didn’t ultimately succeed in whatever they were trying to do. So it’s whether they tried to prove something and they couldn’t, or they tried to build something, and it was broken. And that has been, I think, just one of the funnest and most energizing research conferences that I’ve been a part of people embracing talking about failure.

I’ll leave you with this skit Allison created:

“The MMWF Award” — a fictional award for Men Who Support Men Who Support Women in Finance.

Venkatesh Rao On Infinite Loops

Introduction by Infinite Loops host Jim O’Shaughnessy:

Venkatesh Rao is a writer, consultant, and author. He has been writing about indie consulting for years and has recently published The Art of Gig, Volumes 1 & 2, which together take an in-depth look at the gig economy.

Venkatesh joins the show to discuss tragic luck, becoming slightly nonsensical, the advantages of mediocrity, and a whole lot more!

My intro:

Venkat is one of my favorite writers. I pulled a number of ideas out of this interview for posterity. This is not a summary, just things I want to keepsake.

Episode link

[All bold is mine]

  • I had an equal number of people calling me a communist and a capitalist. – Venkat

I loved this line for the same reason I love this quote by Niels Bohr:

“How wonderful that we have met with a paradox. Now we have some hope of making progress.”

  • On Arthur C. Clarke’s distinction between a failure of imagination vs a failure of nerve: Arthur C. Clark has this wonderful essay called Failures of Prophecy, I believe, and he talks about two kinds of failure in thinking about the future, failure of imagination and failure of nerve, and he makes the very interesting claim that the failure of nerve is, by far, the more important. A lot of
    people are extremely imaginative, they can take in the vast amount of confusing information in the world now and come up with very imaginative sort of interpretations and sense-making constructs. But very few people can look the confusing or mess of reality in the face and say, “This is actually the nervy, courageous thing to do,” And go against their instincts. And it’s easy to, I don’t know, spend as much time as you like on the fun imaginative stuff and never do a courageous thing in your life, whereas the nervy thing is kind of the hard thing to do. So that’s where that particular phrase came from.
  • “Paycheck people” The Paycheck People connection is, I guess, the industrial economy over a century, has created this gamified environment relating to work where it is easy to get through life never making a hard decision ever. So long as you’re smart and imaginative, you will always be valued, you’ll have a job, somebody will give you interesting problems to work on. If you have the right kind of imagination, maybe you’ll come up with good answers, but your courage is not routinely tested. And this, I think, was probably the case in most sectors in the, at least, developed industrialized world, and the paycheck economy in particular, until, I would say, the mid to late nineties when things started wobbling and the old certainties were really starting to unravel and it became clear that you could not go through life only being smart and imaginative and playing the game that was laid out in front of you because at some point, you had to make courageous decisions, and the paycheck world is not really set up to allow you to make courageous decisions.In fact, in the paycheck world, I would argue, courageous decisions are, generally, decisions that kind of break the gamification model of the world itself…. In the brief time I was paycheck employed for several years at Xerox, I dropped a few bombs, I made few bold decisions, but what was shocking was not that a few senior executives kind of spotted me and chose to sponsor me and back my decisions and help me take, I don’t know, risky decisions and risky projects, but the complete lack of reaction in the rest of the corporation, and this, I think, is generally true. It’s like it’s outside their frame of reference to understand risk at all. It’s like, all right, you make this narrow band of maybe very intelligent and imaginative decisions, but within an extremely narrow band of acceptable risk. And beyond that, risk-taking is for senior executives, weird people in the investing world, artists and creative types who live hand-to-mouth and are starving. Risk is not within the frame of reference for how to navigate the world. And I think that’s kind of why I relate the paycheck economy to kind of a structural failure of nerve, it sort of trains you to not have nerve, it trains you to survive without it, and I think there’s a cost to that over a long term.
  • The false sense of security in the paycheck world

    A lot of the sense of security in the paycheck world is a completely false sense of security. That security does not actually exist. It’s as risky as being a gig economy independent, it’s just that they manifest and structure themselves differently. And if you refuse to take risks for year after year, quarter after quarter, for years on end, you’re going to end up with lots of risks. So yeah, it blows up in your face.[Kris: this feels like another one of those failures of mental accounting. We have a “first order effect” myopia where we are sedated by a steady paycheck while the wild world evolves and the sociopathic forces that govern corporate life conspire at least subconsciously against you — unless you are also all-in on the corporate Hunger Games. The person who is not playing the game ruthlessly is the one quietly accumulating all the risk when they thought they were playing it safe] 

  • Is there a character type or archetype that tends to be more open to risk?

    This is a very interesting and complex question, and I think there are layers to it that are truly worth unwrapping…

    1. On privilege
      Some of the basic criticisms of risk-taking, especially from the liberal corner, it’s like, yeah, the people who look like they’re bold risk-takers, if you look at their background, you’ll often find that they come from privilege and the risk, subjectively, for them, is not actually that big. The marginal cost of a hundred thousand dollar risk is not the same if you sort of grew up in poverty and made that first hundred thousand dollars with painstaking hustle versus if that hundred thousand is just 1% of a very large trust fund you inherited.

    2. Psychological conditioning that leads you to have different perspectives

      Another interesting layer, and this comes up in the famous two marshmallow test, for example, which has been kind of discredited, but it’s interesting how it’s been discredited, where the original research claims that kids who were willing to wait for the researcher to come back so they could have two marshmallows instead of having just one marshmallow right now, they did better in life and future. And poking at that, some more recent research looked at the backgrounds of children who made the two kinds of different decisions, and it turned out that the kids who picked one marshmallow now, versus two marshmallows later, tended to come from less privileged backgrounds where the short-term environment was relatively stable, but the medium and long-term environments were so unstable that it was actually rational for them to say, the future is so uncertain, I’d rather take the one marshmallow now than risk this.And if you poke deeper, there was this research done, I think by Phil Zimbardo, he’s another person who’s gotten canceled for questionable research. But one of the interesting things he did were these tests to study time perspectives, was asking children to tell autobiographical
      stories, and it’s very telling. People who grew up in deprived environments tend to tell stories that span a day. People who grew up in more privileged environments tend to tell stories that span a lifetime. So a poor kid who grew up in the slum might say something like, I got up in the morning and went to the market and found, I don’t know, a sandwich or something. It’s a day-long story. And a rich kid might tell a story about how I’m going to go to college and study law and become president and everybody will love me and I’ll be famous.

    3. The subjective perception of the quality of the risk

      Let’s say you were bullied as a kid and developed an extremely strong fighting instinct. And in a particular situation where somebody might be very combative and another person might be very conciliatory, you take what looks to other people like a very risky decision to escalate a conflict and blow things up. And maybe that traces back to some, I don’t know, early childhood memories of fighting back against bullies
      or something like that. So to you, in that situation, psychologically, it could be the case that, even though there are lots of explicit risks, like saying something objectionable and potentially losing your job, the sort of utility of that outcome or disutility of that outcome is actually less than the disutility of challenging, say, very deeply repressed traumas and learned behaviors for dealing with those traumas.

      So I think the narrative people tell themselves of what the risk they’re taking actually means to them, is actually very different from what you might assume just watching a drama unfold from out there. So my point here is, the risk looks very different to the person taking it then it might to different spectators, and this is part of the other mind’s problem. Like, I’m in a meeting, somebody else is saying something very risky that might get them fired and I’m like, “I would never say that because if I put myself in their place, I would see the risks and utilities very differently.” But part of that is… There’s the seen part, which is explicit incentives which affect everybody like money, losing positions, jobs, and investments, but there are also internal psychological risks. Maybe I don’t have the traumas that could be badly exposed and brutalized if I did certain things that another person does.

Venkat reveals his system for dealing with the complexity:

I’ve gotten, I think, both more empathetic and more judgmental about this stuff…The way I like to phrase this is, I like to keep my psychology complex, but my moral judgment’s simple. It’s like, I can never quite put myself in your shoes and unpack the complex psychology of why you’re taking the decisions you are, but I am going to draw some hard lines in the sand and say, “All right, murder is wrong.” I don’t care how traumatized and messed up you were in your childhood or how murdering someone seemed to you, the less risky thing, as opposed to facing the consequences of some actions and drawing a line in the sand at murder is wrong, you’re infringing another person’s life. So I think that’s kind of the layers of how I think about this stuff.

So to your original question of how should we think about the distribution of risk and is there a genetic predisposition to risk-taking, I think the answer is probably yes. There are probably people who are fundamentally more, I don’t know, risk-positive, and more likely to just blow things up to see what happens. So there’s probably some genetic predisposition, but there are these layers of trauma management, behavioral conditioning, and circumstantial assets that create so much more context that, I would say, the genetic component, at least in modern conditions, is probably
almost a rounding error.

I don’t take extreme risks and I’m like somewhere in the middle. But I probably present as somebody who takes a lot more risks than I actually do, because, from my subjective perspective, the actions I take are not actually as risky as they appear. So I think that’s a big theme in a lot of my writing. I’ve written about it in a few places, but the risk that I think I’m taking is not the risk you think I’m taking.

  • Rationality as nihilism

    There’s a philosophical notion that rationality is actually an extremely nihilistic mode of cognition. An extremely rational approach to say scientific discovery and experimentation, science is a fundamentally nihilistic process. If you let it, it’ll tear apart any sense of meaning you have in the world from any source whatsoever. And this is true of any approach to thinking and decision-making that sort of draws inspiration from more scientific and rational approaches to decision-making. Which is, you define your terms of reference, you define the variables in play, you sort of make up mental models of how those things relate to each other, hopefully in a scientific spirit. So you kind of make sense of the world and understand how the world works. Then you kind of decide what you value and say, “I value this much, I value that that much.” There are constraints. And so you end up solving an optimization problem that there’s a natural progression from thinking of the world in rationalistic modes and being sort of rational and building your models of reality, to moving to synthesis and normative considerations through optimization problems. And what that leads to is seeing sort of life itself as an optimization problem where you are like, “All right, what’s my utility function? What are the weights on the different factors? How am I going to solve this cost function? If I have constraints in the picture, are they hard or soft constraints?So you kind of almost turn yourself into an automaton that’s trying to solve an optimization problem. And there’s a long story about why this happens, but this is basically a doomed process. It will lead nihilism. By the time you’re done solving your perfectly rationally formulated and pose the problem, and you maximize your utility function and say, “Hey, this is the most utility maximizing outcome and decision I could hope for, and I’m going to do X, Y, and Z, and I’ll live the optimal life,” you will find that what you’ve solved for is a completely meaningless life.

    It’s sort of this conundrum of complete rationality and optimization as an approach to decision making leads to completely valueless, but technically correct, utility maximizing outcomes. So it’s the whole economics idea of knowing the price of everything and the value of nothing. This is the manifestation of that.

  • How fixed point futurism allows you to break out of this nihilistic process of optimization

    The answer is, you actually have to start not from rationality, but from complete arbitrariness. It’s like, “I’m going to pick something utterly arbitrary. I’m not going to attempt to justify it.” You want arbitrariness in a completely… How do I put it? Artistic sense. It’s like, “I’m just going to declare that blue is my favorite color.” So that’s the kind of thing I mean by arbitrariness. And it’s amazing how often committing to this kind of arbitrariness actually kills nihilism inherent in otherwise rational postulates. And then you can be as rational as you want about everything else so long as you hold faster that one arbitrary commitment you’ve made, which is what I mean by fixed point futurism. And an example that’s on my mind right now, my wife and I, we are shopping around to buy a house for the first time. And it’s like that’s a classic rational optimization decision-making problem. You can make up a spreadsheet about buying houses with all sorts of attributes about property values, income taxes, property taxes, blah blah, blah. And you can lose yourself in this optimization problem of a million variables, and sort of get everlastingly trapped in this hell of trying to decide what your utility function is.But on the other hand, you can pick something arbitrary that is going to break you out of that. So for example, my wife is arbitrarily attached to the idea that she must have beautiful view, where either of the ocean or mountains or something like that. And that can be an optimization variable where you can talk about, “All right, how much view am I willing to give up for lower taxes or whatever.” But it can also be arbitrary. You can say, “I want a view of Mount Rainier,” and that’s an extremely arbitrary thing that can lock you in.

    It’s a little philosophical sleight-of-hand trick of turning a nihilistic process into a meaning-making process. It’s like now you’ve decided no matter what happens to the rest of the world and whether we are all doomed to die in a zombie apocalypse, you are going to make one thing true about the future.

    You’re going to be wearing blue shirts, you’re going to be staring up at the sky with a telescope, even if it means zombies are coming at you and you’re like killing them with the machete, right? That’s what I mean by fixed-point futurism.

  • If you’re mired in the “paycheck economy”, you may be in such a routine that more existential questions about meaning are ignored or not given space. How does Venkat think about this?

    Meaning I think is extremely strongly related to the first topic we were talking about, nerve versus imagination. I think meaning-making begins when you first take your first courageous decision in your life and then realize just how much agency you have. To what extent you are operating in a condition of learned helplessness in institutionalized environments. And the first time you sort of make a reach for a truly autonomous decision, despite the risks, you realize how much more opportunity there is to do so. And for me, the first time that happened was actually long before my leap into the gig economy, when I was unhappy with my first PhD advisor. And I made the decision that even if it’ll costs me my financial aid and I’m sort of adrift for a while, I’m going to break up with my PhD advisor and sort of go off in the wild for a while and find another advisor and new funding.And that is what I did. It was very sort of a tough decision. I quit that advisor, I lost my funding, I had to go off and work at a startup for a year. Then I came back, worked with another advisor I got along with better. But I think that flipped a switch in me where after that, solving for meaning became so easy and so much second nature because it’s not an intellectual problem. You don’t have to be smart to solve for meaning-making, you just have to be courageous. You have to do the tough and hard thing as opposed to the maybe intellectually complex but easy thing. So I think I’m a reasonably smart guy, but I think what unlocked meaning-making for me was that first choice to make a tough decision. And after that, it was brain-dead obvious to me. Anytime I came to a fork in the road, it’s like, “Yeah, this is obviously the more meaningful thing to do, so I’m going to do it.”

  • How the world obscures this

    I would say that today the world is set up in a way where it’s actually hard to learn this meaning-making trick except by accident. And one of the things that I think this growing conversation around the gig economy is doing, is sort of reinforcing the intense practicality of looking for meaning. A lot of people don’t get this.If you look at conversations about meaning-making in the abstract, the way talking heads talk about them and talking about lost voice, listening to podcasters and getting radicalized, that level of conversation about the meaning crisis, it seems like a philosophical spiritual problem that should be addressed with religion and philosophy, ideas and so forth. It’s not. It’s really as simple as meaning-making is unlocked when you first learn to take courageous decisions and keep doing that, so it becomes a habit. And after that, you kind of unlock this idea of fixed point futures and all these other little tricks become sort of self-evident. 

    Learning to make meaning is the most intensely practical thing you can do. It’s not a matter of spiritual retreats and going on soul-searching journeys and having shamans take you on Ayahuasca retreats and things like that. It’s not about that at all. It’s the first time you come to a hard decision in your career or life, make the hard decision, see how good you are at making tough calls, and then keep doing that and meaning-making will take care of itself.

    And I think that’s a lesson that the emerging conversation in the gig economy is driving home for a lot of people. And a lot of people who stay in the paycheck economy, stay in an environment that makes this way too hard, that tells them, “You have to go on spiritual retreats and read Zen philosophy and take drugs to learn meaning-making.” And it’s not that hard.

  • The “tragically lucky”

    At age 23, it’s very tempting to conflate agency and determinism in scripts. You think you control your future, you think you can make a very specific future happen. You think “I’m a smart guy, I have these resources at hand and I can solve the problem and solve the equation of how to turn my talents and resources into the outcomes I want.” And then of course, life hits you in the face. You realize it’s much more complex.Then you ask, “What happens next?” Do you then refactor your sense of agency as in “I still have agency, it just doesn’t work the way I thought it did, so I’d better get about understanding how the world actually works and understanding how agency actually operates.” That’s one path.

    The other path is of course the world sort of mashed my plans to bits and pieces and I’m going to be helpless from here on out, and that happens to people too.

    So I think a naive sense of youthful agency does not survive first contact with the enemy…but for some people it does. And of course, there are also people who just get lucky in a very naive sense in the sense that they plan a particular future and actually it unfolds because they never get hit in the face with conflicting reality. So there are people I know who are these spirits who go through life everything having gone exactly as they planned.

    But there’s a certain tragedy there, which is, they think they’re super agenty then things go out exactly as planned and they become president or whatever, and then they’re like 60, 70 or these old people and they come across as children. I talk to them and they’re like, there’s a sense of a lost child about them. It’s like they were never really tested by life, so they’d never really actually learned what was going on. It’s like they’re 60 or 70 and they act like children or 23-year olds maybe. And part of the reason is they were on the surface, they were super lucky that things bent as they planned, but at the deeper sort of philosophical level, they’re the most intensely tragic figures in the world because things went exactly as they planned. The most interesting thing that can happen to you in your life is things don’t go as you plan. And because that forces you to come to terms with what’s the actual nature of the world, what’s the actual nature of agency.

    [Kris: I think most people’s desire or goal in life is to become tragically lucky. Ignorance is bliss and all that. Hard to think of anything more boring.]

  • Finding a healthy sense of agency

    2 versions of the problem

    a) There are people who were so battered down by early life traumas that they never make those naively optimistic 23-year old statements at all.

The first challenge is to get them to that place of naive optimism in the first place. So I think of that as a much more basic challenge of humane treatment of young people, which is if they’ve been battered, just create kind environments for them where they can develop some confidence and say, “Hey agencies, actually I think that exists”, even if it’s at a very toy level. So often when I’m thrown into position of trying to mentor younger people, which I try to avoid, I’m not a mentor type person, but when I am thrown in the situation, my tendency is to ask “how burned are you? How much are you a devastated landscape of bad parenting and bad childhood conditioning that we have to get you to the starting line of being a naive optimistic age 20?” And this requires kindness and nurturing, and I’m not very good at that, other people are better.

b) But let’s assume some people are already at that starting line of naive optimism

How do you ensure that you when throw them into reality a) they don’t get tragically lucky. Let’s hope they don’t get tragically lucky. Throw them in something that actually challenges their assumptions about the world and breaks them in some way. But then how do you ensure that if they’re broken, they’re actually not going to react with complete helplessness, but then sort of pick themselves up and say, “No, the world works differently and I’m going to rethink what agency means.”

And I think yes, that is a learnable, teachable skill, but it’s one that the industrial environment with schooling and the paycheck world is actually anti-optimized for. It’s designed to teach you exactly the opposite of that. It’s designed to take you from an naive starting point and keep you tragically lucky for the rest of your life. And if they fail at it, you’re tossed by the wayside. That’s what the industrial world is set up to do, make you tragically lucky or throw you into the garbage heap.

In the developing world, more people are thrown by the wayside, and in places the US more people enjoy the tragically, enjoy is the wrong word, but suffer the tragically lucky outcome.

We don’t want either of those outcomes. We want you to be thrown into the world, into a test environment where you’re
actually tested and then you kind of learn the skills through trial and error of acquired realistic agency

  • The self-defeating fear of technology

    Go back as far back as you like in tech history. And you will always find that it’s the case that whenever tech sort of automates or disrupts a category of labor, it creates 10 times more new kinds of labor, right? So we feed the entire planet with maybe 4% of modern populations in agriculture. It used to be 80 plus percent a couple of centuries back, but we produced more food and feed everybody. And it’s not that all those farmers banished. Future generations just weren’t farmers anymore. There was no need for them to be farmers. So in one sense, it’s true. If you’re attached to your idea of yourself being a farmer or a creative writer who’s going to get disrupted by LLMs and you’re attached to that idea, you are going to go obsolete. So your expectation is, in fact, tragically correct. You are going to be extinct. But the question is, “Why are you choosing that path of extinction?” I think the reason is that these people like the character in Office Space who says, “I’m a people person,” they’re actually the most degenerate sort of lesser subhumans in our world, because it’s kind of weirdly dumb to live as part of a species that’s been a technological species for 6,000 years and reject this hugely important aspect of our environment that’s been growing for 6,000 years, right? Saying, “I’m a people person,” and sort of distancing yourself from the world of technology that you’re completely entangled with is like I translate it as saying, “I choose to be a 10th of what a human being actually is.” So yes, the thing is it’s not the technologies or tools or that we are sort of masters of our technology, that we use technology as tools, but that we co-evolve with them. The medium is the message, and we are inextricably entangled with our tools… what tools you sort of came of age with… I’m as much a product of my human conditioning environment, my parents and my friends and so forth, as I am a product of computers and various other technological artifacts through which my brain became what it is today, and that process kind of continues.

  • The key to playing infinite games: mediocrity

    I would say, my least popular idea ever, and therefore, my absolute favorite idea ever, which is this call for mediocrity. I have a whole series on my blog about mediocrity and how I love mediocrity and how I solve for mediocrity and I hate excellence. And finally, it’s just me being a troll and a contrarian in this culture of excellence and trying to win and 4.0s and being excellent and Six Sigma and optimizing and all that whole world of being Paycheck People. This is why the term Paycheck People evokes a whole world of stuff. They are people who play finite games. They do all these things. But yeah, how do you get away from that? Be mediocre. I think I got onto this line of thinking starting with David Allen, the author of Getting Things Done. I got friendly with him in 2005 or 2006. I met him a couple of times. Lovely guy. In his workshops on Getting Things Done, he starts off with a very good joke, which is, “How do you get things done? I’m going to give you an absolutely perfect hack. Lower your standards.” I love that. And he doesn’t mean it flippantly. A lot of people assume he’s just making a joke, and the rest of the workshop is about, “All right, how not to lower your standards and how to actually maintain high standards and do it.” No, David means it. He means fricking lower your standards.This, I think, is an unbelievably important key to unlocking infinite game attitudes, because the conceptual connection is optimizing in a finite game and trying to win by particular standards and maximizing according to those standards means you’re operating in a closed universe of sort of contextual information and you’re ignoring everything outside of that. And the infinite game is fundamentally about recognizing the fact that there is an infinite universe out there beyond the little scope of a little game you’ve set yourself to play, and there is no such thing as ultimately winning or losing in that little fake game you’ve made up. All that happens is that you either win or you don’t. And then you sit back and say, “All right, life hit me in the face or made me tragically lucky.” So I think winning in a finite game is tragic luck, losing in a finite game is life hitting you in the face.

    But then what happens next? You’ll sit back, let that boundary dissolve, expand your horizons and say, “All right, what else is out there in the universe? What else is out there beyond the scope of this game that I was just in, that I can pay attention to a,” I don’t know, “new fixed point that I can sort of latch onto and create a whole new game around?” That’s how you continue the game, right?The way to do this is to let go standards. The way to do this is to appreciate that mediocrity is the key, which is when you’re in any given finite game, you don’t go all out. You reserve a part of sort of your human potential for just paying attention to peripheral vision, the world outside the little particular game you happen to be playing. Of course you play it sincerely. And ironically, you do right by commitments you’ve made to other people. If you say you’re going to do a job and other people are depending on you to do that, you do that. So I’m not saying cut your standards in the sense of being unethical or unreliable or anything like that. I’m saying maintain a reserve of who you are, your thinking, and devote it to the infinite universe beyond the particular game you happen to be playing. That looks, from the context of the game, kind of like mediocrity. It kind of looks like you’re not willing to go 110% and hustle and go all out and stuff like that. It looks like, at some level, a part of you is philosophically checked out because it’s curious about the rest of the universe. It’s not checked out because you’re lazy or lack courage or insufficiently committed. You’re checked out because you’re bigger than the particular thing you happen to be doing right now. You’re a larger being that has a bigger faith in your life, and you want to reserve a part of your attention to that. And there’s a strong evolutionary logic to that.[Kris: the logic is basically how slack or redundancy in nature gives the randomness embedded in evolution to be expressed.]

    This is why success can be so tragic for people who’ve been overcommitted to it. It’s like you’ve actually won and you’re acting devastated and destroyed, like the meaning of your life has been rugged from you. The rug has been pulled out from under your feet. That’s because you overcommitted. You had too high of a standard.

  • Divergentism

    As people grow and age, they fundamentally diverge from each other in thought space, and that’s okay. It’s okay to not be understood, because that’s what happens when you diverge from other people. It’s like people don’t understand you as well, and you don’t understand them as well. So I would say the compact form of the thought is it’s okay to not be understood and to not understand other people.

    [Kris: I’ve had a similar thought. When people are surprised by others my response is always…”there are 8b people in the world”]

Gabriel Leydon’s “Purple Pills” From His Invest Like The Best Interview

Video game designer Gabriele Leydon went on Invest Like The Best and dropped deeply provocative bits about what I might describe as design and gamification as a response to a future that has thus far proved disappointing or alienating. I don’t know how much of it I agree with it though I’ll admit I have had similar thoughts (and a few essays sitting in my drafts on the topic) with respect to financialization. I’d describe listening to this as Patrick interviewing the Ben Hunt of video games. If there’s something I’d probably disagree with most it’s the pastoral sense that the frontier seemed somehow more accessible to the common man 100 years ago beckoning people to go West for opportunity. There are frontiers, and they are always crushing by the standards of their time. I think a lot about the stories of cab-driving immigrants and have a sense that they are deeply courageous and today’s modern day pioneers, leaving all that is familiar behind (and probably why the success of immigrants in the US shouldn’t be surprising. They are built different). The definition of frontier is context-dependent. Still, I really enjoyed listening to this interview and any disagreement I’d have is well worth the brain food Gabriele serves. Patrick does a great job as usual asking questions.

episode link

These notes are just pulled from the transcript and a (lightly edited) snippet of what I wanted to refer back to. It’s not a summary. All emphasis is mine.

A Dark Interpretation of Our Obsession With Stories and Design

Patrick: I know you’re going to restrain yourself, but we’ll do our best. The first red pill of the discussion is around the topic of design. There’s a huge emphasis on design right now, and I think you’ve got an interesting take on what an emphasis on design means about where we are in capitalism. What are your thoughts on the importance of design or what it might mean?

Gabriel: There’s this pattern where when things are innovative, nobody really cares what they look like. If I made up a teleport machine and it was the size of an arena and it was covered in slime and smelled really bad or something nobody would care. There’d be a line around the block. Everybody would just jump in and they would think it’s the greatest thing ever. But over time we kind of would make it smaller, and then the artists would come in and try to make it look nicer and feel better. And once you kind of get to that design phase, where Silicon Valley’s been for about 10 years, there’s only so much you can do to make something look better.

If you remember 5 years ago, everybody was talking about delighting their users, and delighting is “We don’t have any more ideas. So we’re just going to feel a little bit better because we’re out of ideas. So now we’re going to just delight you.” The game design stuff is, “we don’t know how to make this look better, so now we’re just going to tap into your human condition of biology and psychology to make our products better. Because we don’t know how to make them more innovative, we don’t know how to make them better looking, but we can add levels and achievements.”

How that presents itself is all of a sudden you’re getting achievements for buying erectile dysfunction pills from Hims. You buy extra orders of minoxidil to max out your Hims account. That’s what we’re seeing…You see this kind of talk about everything becoming a video game, but I actually see it as a bad sign. We’re basically running out of new ideas. The economy is just becoming more and more psychological and it’s less about innovation and more about understanding your condition as a person and then building a product around biological and psychological reflexes rather than a teleport machine that can move you around the world.

Patrick: It reminds me of that Neil Postman book, Amusing Ourselves to Death [Kris: I’m coincidentally about to start this book], that Huxley’s version of the future was more accurate than Orwell’s.

Gabriel: I think it’s because when people think about capitalism, they think about the early 1900s. They think about cars and radios and TVs and microwaves and it almost never ends. And I think it peaks in the ’60s and the ’70s with all that futurism. The futuristic art, flying cars, and skyscrapers. And that’s the same time we go off the gold standard and there was this infinite optimism around money printing and innovation basically. And we could just print as much as we want because we’re going to be immortal space beings, zapping around the galaxy. So who cares?

That didn’t happen. So when the innovation growth didn’t really match the expectation, it’s just like things just start getting designed, they start moving towards the design phase, and then eventually a gamification phase, like what you’re seeing in the financial markets and software and pretty much everything.

I’m not a big person on late-stage capitalism. Capitalism is just a human condition. What does that even mean? I think it’s more like we just don’t know what to do anymore. So we’re just going to add levels to the stuff that we already know how to do. And there’s a lot of margin in it too. So it’d be, it’s like a big gravity well where it’s like, “Well, we can just take the existing stuff and add achievements to it and we’ll sell more pills.”

There’s also another part of it in Silicon Valley where … And you’re a VC, so has anybody ever tried to pitch you a video game? Do you understand it at all?

Patrick: What did you learn about the reasons why people will pay? Famously in free to play there’s this crazy power law of who pays and how much. And the 0.1% of the players, I don’t know what it is. Some crazy high percentage of the revenue. So maybe a better way of asking the question is like, what have you learned about what characterizes that willingness to spend?

Gabriel: We’re tribal people by nature. And when I say tribe, I don’t just mean your culture. I also mean the size. Tribes tend to be pretty small. If you look at early America and people say, go West and land of opportunities. What does land of opportunity mean? It means if I’m a blacksmith and I’m the only blacksmith around for 100 miles, it doesn’t matter if I’m the world’s best at making horseshoes or not. I’m the only one around. So, that’s my land of opportunity. I could just keep going West essentially, and there’ll be less and less people, and I’ll have more and more of an opportunity to become important to the community that I’m in.

And we’re in this age of hyper-competition. We have these social networks, forums, and chat rooms, clubhouses, whatever, where we have essentially this real-time leaderboard of who matters and who doesn’t. So when you say that 1% of spenders, that group is even smaller with who matters online.

So the answer is that the world has become so soul-crushingly competitive. Being good at something doesn’t matter anymore — you have to be the best. If you make horseshoes, doesn’t matter if you’re good at it, I’ll just order it for someone else and it’ll arrive in two days. And you better be cheap, because if not I’ll wait a week and get it from China.

So we’re in this hyper state of competition, that makes people feel like they don’t matter. Because they don’t. They actually really don’t, and everybody knows it. That’s the honest truth. So you end up with these online communities with a seductive and simple way to belong to something, where these things actually reward time spent, rather than skill. So if I just spend more time, I’ll be more important. You see that a lot on social networking, they’re all designed that way. Spend more time, you’ll matter more. You see so much like online activism, for example. Online activism that you would never see in person because all I got to do is post something, or whatever. And they matter because they’ll get lots of likes, they’ll get lots of retweets.

You get the culture and then the counterculture. And they’re both essentially the same thing, like one side saying thing because that’s the thing to say. The other side is saying the opposite because that’s the opposite to say. And both sides get a lot of likes. Video games give more structure to that than Twitter does. A lot more structure. They could have levels, and Kings, and Queens, and weapons, and kingdoms, and whatever you want, you just make it up. So you get more structure. And the video games become a place to get lost in because they have so much structure. That’s what I did. And I loved it. And for me it was really important to me, because before that I was just like, what’s the point? I don’t even know what the point of my life was basically. It’s like, you’re working at Target, and Dave & Buster’s, and whatever, and you’re not going to college, what else do you have? That’s what I had. And I think that’s what made me understand it. There’s just too much competition, and people need environments to excel in. This whole hyper-globalization thing just crushes souls because they can’t excel. And they know it. Everybody’s like, robots are going to replace you. And AI is going to replace you, and you got to go eat bugs and go live in a box. It’s so funny, I talk to these AI guys in Silicon Valley. They’re all trying to make God versions of themselves. They always say to the game developers “We need you.” Because what are people going to do when my God AI thing works?

It’s so sick. It really is sick, like they know what they’re doing. They know exactly what is going to happen. And they’re looking at the game designers like, well maybe you’ll distract everybody. Maybe everybody will just be distracted as the whole world collapses around them. Like every person in AI, every single person in AI, every single one. They’re all, “We’re going to need VR.”

I wish they would be more honest in public about it. Because they all say it. I think this game design worldwide takeover is partly because the innovators think that’s what should happen. And also because they don’t know what else to do.

Patrick: Give me one more thing at least. One more what I would call purple pill. Something not too inflammatory. Something you think that is true about the world that people wouldn’t like to hear.

Gabriel: I think we need AI more than we think. I think that we’re at an IQ limit and the reason why innovation feels like it’s slowing down is because we can’t do it. We just literally, physically can’t do it. And there may be an exit ramp through AI, but it’s not exactly clear that we can do that either.

I really think that the 60s and 70s futurism is the reason why we’re suffering so much today. Because there was no reason to not print money, to not full-on inflationary mindset and everything because we were going to live in paradise. We were going to be on the moon. We’ll be able to pay all this back, there’s no problem. And then financialization happened, and gamification of financialization happened because that was easier and it worked. But it’s not better. Innovation is better. It’s clearly better. If I make a teleport machine, I don’t need to make a video game, I don’t need to have levels and achievements. It doesn’t need to look nice. It doesn’t need any of those things. It’s just is what it is and everybody wants one. That is better. That’s the only way to really have prosperity. And this design/now gamification is a symptom of the limits of our minds. So instead of doing things in the physical world, we’re doing things in the psychological world now, and that may be permanent. And I hope that’s not true, but more and more of the economy is going into this exploit, automation, high-frequency trading, that kind of thinking. And it’s not rockets to Mars.

We’ve gotten to the point where we look at the two richest men… Like we used to have the Wright brothers, these two guys trying to make an airplane, they’re in the middle of nowhere, who are these guys like? Now we look to the two richest men in the world to solve our most difficult problems. The regular person has no chance in participating in the future of the economy now. The only people who have the chance [appear to be these rich people], “I hope Bill Gates figures out solar panels.” And the regular people are just kind of looking up to them saying, “Well, I don’t know what to do.” And I think the reality is the rich guys don’t know what to do either. We got the rockets going. Those are cool. And we’re making some incremental innovations. There’s been some really important things like crypto. So it’s not hopeless. It’s just not what we thought was going to happen. The dislocation between the economy and the reality of innovation is that the economy moved way ahead of innovation, under false expectations that we would be able to keep innovating at an exponential rate.

I think there’s a fear that we know that we can’t. So then you’re staring at deflation, like a reset, essentially. We’ve got too much of everything and there’s not enough innovation to pay this back. It doesn’t exist so we got to abandon ship basically. That’s pretty bad. But from my lens, from my point of view, it’s why gaming is becoming so important. It’s because we don’t have the teleport machine and we need one. And if we had teleport machines, nobody would be playing games.

Something More Uplifting: A Qualitative Screen For A Promising Investment

Patrick: Does the idea, I’ll call it the gooey teleportation principle or something, is this also an investing principle? You should look for stuff that has terrible design or is breaking?

Gabriel: NFTs are important the same way the App Store was important. Meaning that at the beginning of the App Store, everything was broken. It took like three months to get an app approved. Just crazy stuff. It was a real nightmare. And it was growing like crazy. That’s what you want. You want environment that’s completely broken. There’s like a couple spaces still in the innovation phase and crypto is clearly one of them.

You always hear these VCs who don’t know what they’re talking about. They go, “You know what crypto needs, it needs a good UI.” I’m like, “Oh my God, just stop. Like stop it.” It’s innovative, it doesn’t need that. It’s still growing despite that. If we get to the phase where all crypto can do is add UI, it’s over. That’s it. Right? Then it’s just a matter of who’s got more DAU at that point, and it’s over.

So crypto is a good example of something that’s still really deep in the innovation phase. It’s not everything, but crypto will eventually turn into a game too. It’s obvious. It’s kind of got elements like that. But my favorite stuff is you go to the websites, they look terrible. You ever noticed that? If you look at this DeFi projects, it’s like the worst looking website you’ve ever seen. That’s a good thing. That’s what I want. I want it to look terrible like it’s crashing all the time, and it’s just growing. That’s the sign. Because when you clean it up, when you do put the good UI in, and you do gamify it, it will be 100x bigger. If you’re 10 years deep and still looks terrible and still growing like crazy, that’s all you need to know.

VC is right that when it does get cleaned up, it’s going to be bigger. But that’s not what you’re looking for. You’re actually looking for it being a mess and it’s still growing.

Put all your money there. Anything that’s just growing like crazy and totally broken, just put all your money there because obviously when it gets fixed, it’s going to be better. And there are tons of examples of this. There’s like the MySpace/Facebook example, right? They both had the broken but working thing, but MySpace couldn’t fix itself fast enough. So that’s kind of the bet. But if I didn’t know the future, I’d go, “Yeah, put all your money in MySpace.” I mean it’s growing and it’s like totally broken all the time. That’s where I would look at the risk. I think you kind of have to be an entrepreneur to even understand that. But that’s how I look at it, where’s the space that’s just totally screwed up and it’s still working? That’s what you want to be involved in.

Sal Khan On The Finding Mastery Podcast

My personal notes from Sal Khan’s interview with Michael Gervais on the Finding Mastery podcast.

Link: https://findingmastery.net/sal-khan/

How did Sal mentally manage the risk of non-venture backed entrepreneurship?

Early on in the Khan Academy journey, even when, let’s go back to 2004 2005, I started tutoring my cousin’s 2005, I started writing software for them. That’s when I got the domain name Khan Academy. And I started writing software for my cousins. And I said, “Hey, if it’s just my cousins who are using it, it’s worth doing this, it’s helping them”. But obviously, as you start writing software you’re like, but maybe people who are not my cousins could use it. But I kept trying to keep myself from getting too attached to the big ambition, just saying, hey, just put one foot in front of the other, but keep the door open to the big ambition. I didn’t want to close that door either…

Even before I had quit my job, I would show my friends, “Hey, I’ve got this hobby. I’m tutoring my cousins.” My friends, out here in Silicon Valley, their natural inclination is “why are you doing this?” And I’m like, “oh, because it’s helping my cousins.” They’d ask, “How are you going to monetize this? I don’t see the business plan. Someone else’s is doing what you’re doing.”

I’m like, no, no, no, this isn’t a business. This isn’t anything. I’m doing it because it’s helping my cousins. And hey, if it helps other people, great. So that was one form of protection.

Dealing with cynics — who do you need to convince and what evidence do you hold?

Even today, when I encounter cynics, the first thing I say is, “Sal, don’t be defensive, there might be something in what they’re saying”. You don’t want to be delusional and ignore good feedback. But at the same time, you also have to remind yourself: you don’t have to convince this person.

We always want to impress our friends and convince them that what we’re doing is a good idea. But I don’t have to convince them. That’s the first somewhat liberating thing. And then what made me not question myself too much, I said, “Okay, so what evidence do you have?” This is a friend who’s smart, I respect their opinion, but what evidence do I have?

Well, I did transform several of my cousins’ lives. I was already getting letters from people who I didn’t know around the world about how it had transformed them in some way, shape, or form or their children.

Look, my well-intentioned friend is probably trying to save me from “wasting time” or getting distracted, but they haven’t even tried it out. They just did classic MBA-type thinking of “Well, I heard some other companies are making educational videos and doing software that creates questions. You’re like the 10th person to do this, so what makes you think…”. That’s their natural, competitive analysis type of thing.

I think there’s probably a lot of people who want to do entrepreneurial things. And when they meet a friend who’s doing something entrepreneurial, part of their brain wants to help the friend and wants to be constructive for the friend, part of their brain wants to help their friend. If they think their friend is going down the wrong angle, maybe protecting them from that a little bit. But some of it is also protecting their choices. “I’ve always wanted to be an entrepreneur, but I’ve been afraid to and now my friend is doing it…maybe it’s comfortable if I convince him to stop doing it, and do what I’m doing.”

The main thing is just what just keep reminding yourself, “Why are you doing it? What gives you confidence?” And remembering “Who do you really need to convince? And who do you not really have to convince?”

Where did Sal learn to focus on evidence and focusing on who he needed to convince?

He lightly responds: Probably is a coping mechanism for a bunch of things that happen in life…I’ve been described by even some of our early board members as a “pleaser”. Like I want people to say, “Good job.” [Me: Oh man, this hits hard]

I think I realized in my life you’re never going to win trying to please everybody. Trying to convince people, getting defensive about things, you just don’t feel good about yourself. 

I’m still working on it. I have a lot of ideas. I do try to share them with people who I really respect. And when they immediately get in the devil’s advocate position or the cynical side, I do get a little defensive if I’m honest. But I I’ve been working on myself.  “Okay, I don’t have to convince them, there’s probably some truth in what they’re saying, I should process it.”

And you know, also some of it’s on me. I realized that when I get excited about an idea, I go into “sell mode” almost immediately, like “this is all the reasons why it’s good, isn’t this exciting?…” And that almost automatically puts people into that devil’s advocate position. “But what about this? What about that?” And so now when I introduce ideas, I’m going against my stereotype, where I’m showing that I’m also looking at the risks and how this could go wrong.

Half the time, the next morning, I wake up, I’m like, “Yeah, they were kind of right.” But sometimes I’m like, “No, I still have evidence that this was worth this is worth pursuing.”

How did Sal frame the decision to leave the hedge fund path to start Khan Academy?

There were some basic mechanical, left-brain considerations.

Did I save up enough money?  I was an analyst at a hedge fund, I wasn’t a hedge fund manager. So I was able to save up some money, essentially a healthy downpayment for our house in Silicon Valley. We were saving up for, you know, several hundreds of thousands of dollars not like independently wealthy money. We don’t have big expenses. My wife and I grew up quite poor so we know how to economize.  That was a mechanical thing.

Even more was the opportunity cost of the [hedge fund] career. Every year your income is accelerating. In five or six years, I could be making what my boss was making,  what could have been in the millions of dollars every year. And that’s a real big opportunity cost to give up for something that’s unproven. That’s where a little bit of the heart came in. I just told myself “Well, what is the life that you want? And the life that I want is a healthy, happy family. But I really told myself, if I had a nice 2000 square foot house, which was the house that we were renting, and we later were able to buy — a four bedroom house with you know two cars in the driveway. We’re able to go on vacations, go to restaurants every now and I’m able to support my kids through college. That’s all I want, financially, really. And if I’m able to do that then also get to work on something that, every morning, I wake up and I’m inspired to work on, I get to work on an interesting problem, and I feel like I have a sense of purpose then I consider myself the luckiest person on the planet. I’m not saying this now just to sound you know anything, that’s literally what I told myself. I’m like, if you are able to have that lifestyle, that’s a really good life. And so that liberated me a little bit from the golden handcuffs.

A lot of times when I’m making some of these decisions like even “what Khan Academy should be” I do go a little bit into what inspires me. We have one life to live. If you have a shot of being able to live your life as a protagonist in a movie, live your life as a protagonist in a science fiction book, go for it! [Me: this is the type of thinking that doesn’t show up in a spreadsheet. This is an example of how “accounting” fails us…not everything that matters can be measured and vice versa]

He fills in the details:

Even in the early days, there were a lot of VCs who reached out who wanted to write a check and Khan Academy be a for-profit, and it was tempting. But then when we start talking about monetization, and how you’re going to exit and all that I was like, “Oh, this isn’t what I want to do I want to”

Then I thought about what is the homerun is for a for-profit. And then what’s a homerun for a non-profit. A homerun for a for-profit, we all know those stories quite well. But I was also thinking, “How’s it going to change the world? And how’s that going to change me?”

And then I thought about a home run as a non-profit. I’m like, “What if Khan Academy can be the next Smithsonian, the next Oxford, or the next, whatever. In some ways, it’s bigger than all of those because even in 2009, when I was thinking about these things, it had bigger reach than some of these hundreds-of-year-old institutions. And we were, there’s no reason why we couldn’t grow another 100 fold or not 1000 fold from there. So for me, it was like, “Wow, maybe it’s worth swinging for the even higher fence.” That’s a hard thing. The head kicks in and says, “Okay, is that at all reasonable?” And as ridiculous as it sounds, it isn’t unreasonable. If you just extrapolate the growth, if you just look at what Internet technologies allow us to do, if you just think about the scale of other people on the internet, for the most part for-profits…Google scale would have seemed like science fiction 30 years ago for what it does. But it’s not. And so couldn’t Khan Academy be that same thing, but as a social institution?

Did he share this thinking with others?

Going back to our earlier, I’ve realized that there’s certain contexts where you’re this type of conversation is going to be welcome. But the conversations where I’m talking to my friend who’s talking about how you’re going to monetize this, he’s not going to be in a headspace where I’m like, Well, what do you really want out of your life? And what do I really want in my life?

And do I need his approval for me to be able to do it? Now, I did talk about this with my wife, and I kind of do need her approval because this is “how do we want to live our life”.

Healthy and unhealthy “imposter syndrome”

I think some of that impostor syndrome, I actually want to retain. I never want to forget how, like, there, there was a time not too long ago that I would pass on the organic produce. I think it lets you just appreciate the world a little bit. And we all know about hedonic adaptation and the hedonic treadmill. I don’t claim that I’m immune so I don’t want to sound like I’m some guru here. I live in Silicon Valley. We live in that same house, and a lot of our friends have now moved into houses that are multiple of the size of our house. Every now and then it’s “maybe it would be nice to have two saunas.” But I always remind myself, “well imagine their electricity bill, or like, the gardening bill or the water bill or whatever.” But, yeah, I think it’s healthy imposter syndrome.

A healthy one keeps you grounded, allows you to enjoy it a little bit. Like every now and then I get invited to meetings with people or conferences with people, where both healthy and unhealthy impostor syndrome could be at play. The healthy imposter syndrome says  “Wow, you get to meet your childhood hero, or someone that you thought you could only read books about, and you’re meeting this person, and they are interested in what you have to say, and they’re supporting Khan Academy.” That’s kind of fun. I don’t know if that’s impostor syndrome, or that’s just remembering yourself when you’re younger. And you’re like, “Wow, how is little Sal in this meeting right now? That’s kind of wild.”

The little less healthy imposter syndrome is that if that goes to an extreme, where like there’s a discussion and I’m like “Who am I to say something?”

There, I try to remind myself that everyone here is literally just a person, like everyone here. And that’s another, I guess, coping mechanism. I just treat everyone as if they’re my childhood friend. And there’s something of a self-fulfilling prophecy there as long you’re respectful. Some people who have been great supporters of Khan Academy are household names — I’m gonna treat them as my friend. And I think they appreciate that too, because so many other people treat them with such reverence, and I respect them a ton, but I get to joke around with them a little bit. And that’s how I deal with that other potential imposter syndrome.

A resonant story: college can give you a safe space to explore things you have suppressed because you grew up perhaps in a narrow place

MIT was like heaven for me. I think when you are in high school in a fairly mainstream high school, you have to suppress certain instincts. You have to suppress how much you get excited about learning certain things so you don’t get beat up, you don’t get ostracized.

Why Sal wanted to dedicate himself to education

  1. First, I’ve always enjoyed teaching. Multiple times in my life, either informally, even when I was very young, I found that I had a knack for it. In a lot of cases where a classmate might be struggling to understand what’s in a textbook or a teacher,  and I’m like, “Oh, this is how I think about it”. And my friend was like, “Oh, man, that’s so cool. Yeah, that makes all the sense in the world”. I guess I have a knack for this thing. So that kind of built confidence in my ability to do that. [Me: importance of knowing yourself in helping determine what you should be doing!]I was the president of the math club and one of the things we did was math tutoring.  We created such a legitimate program that the school then made it a formal part of the school. It made anyone who had below a certain grade in any of their math classes go to this math tutoring, that I was essentially running with a bunch of other students who are in this club. And I saw time and time again, a lot of students who were struggling, barely passing a course, or thought they hated math, if they just had the opportunity, the incentive to fill in gaps, had things explained to them the right way, a chance to practice, they were off to the races. Some of them joined the math Honor Society. A month ago, they were about to fail their algebra class, and now they’re going to math competitions with us, because they started to get excited about it. So that also gave me confidence.And that’s all about mastery learning. The opportunity, incentive to fill in any gaps to finish any unfinished learning.
  2. The other thread is I think every young person who’s even vaguely idealistic, and I think this is all young people, look at the world and say, “Oh, there’s so many problems in the world. How do you solve it?” You think about climate, you think about inequality, think about whatever you pick, you pick the issue. Conflicts, when you really keep peeling the onion, it’s just what’s going on in people’s heads. Everything else is almost just a side effect of what’s going on in people’s heads. Okay, so then we got to change what goes on inside people’s heads or improve or remodeler? Well, what does that? Education. Education is the single highest leverage point.

A quote pulled from Sal’s writing:

If you believe in trying to make the best of the finite number of years we have on this planet, while not making anyone worse think that pride and self righteousness are the cause of most conflict and negativity, and are humbled by the vastness and mystery of the universe, then I’m the same religion as you.

What is the state of education today?

The good news

If I compare the State of the Union of education to what it was 250 years ago, it’s awesome. 250 years ago, even in more literate countries, 30-40% of the of the population was functionally illiterate. Free public school, or at least a high-quality public school was not a mainstream thing as recent as even 30, 40 or 50 years ago. Because of things like segregation even in places like the US, you did not have respectable access to education. I think it’s still not perfect, and there’s still a lot of inequality but for the most literacy rates are much, much better than they were for most of human history. Even in the last 10 years, as I’ve been on this journey, things like access to technology, to the internet, to high-quality instructional materials, etc. That’s all actually gotten better, even in the last 15 years.

The bad news

Even in affluent neighborhoods or fancy prep schools, you still have a model where a lot of kids are still falling through the cracks. And those are the places where they’re not resource-constrained. Imagine in the places where they are resource constrained. I mean, there are still schools, my school in fact, which is a suburb of New Orleans which was pretty mainstream, it wasn’t a gold-plated school by any stretch of the imagination. It was a normal Louisiana public school. But I remember even when I was growing up, there were schools in New Orleans and kind of urban corridors that didn’t have air conditioning. Can you imagine not having air conditioning in New Orleans?

The disappointing news

Let’s just assume that you have all the resources…the model of education is not mastery-based. Kids are moved ahead at a fixed pace. They cover some material, they get a test, some kids get 100 on it, some kids get a 90, some kids get a 70 on it, even though that student didn’t know 30% of the material that happened to be on the test, the whole class will move on to the next concept, and then build on those gaps. And then the next concepts are going to be that much harder to learn. And then those gaps just keep accumulating. [Me: In my own tutoring I see this at the elementary level. Kids that are 2 to 3 grades behind. There’s no concept of being left back. Just push them through the system]
At some point, kids hit a wall. It hits their self-esteem, they’re not able to move any further. And this isn’t theoretical, you just look at the graduates of a fancy prep school, it’s happening. It’s definitely happening on a nationwide basis. So I think that is the biggest problem.

60% of kids who to 2-year colleges and about 30% of the kids who go to 4-year colleges (and college-bound kids are in the top half of already) exhibit giant gaps in learning, many unable to learn algebra yet — a 9th grade course. The majority of kids attending college would need to go back to middle school-level learning to fill in gaps.

On American universities

American higher education is the envy of the world. Our research is the best in the world.  American universities have very nice facilities, and they have very nice programs. So what are the problems?

  1. They’re very expensive. Partially because of the landscaping and the facilities and the programs that they have.
  2. They can be very rigid. What’s magical about four years, whether you’re gonna be a software engineer, or art historian? It’s always 4 years. Clearly no one has said “Let me just work on the stuff that you need to learn. And not just to learn to be that career, but like learn to be a human being or participate in democracy.” The opportunity cost isn’t just in dollars, although those are significant. It’s also in lost time, the fact that in the US to become a working doctor, and I observed this with my wife, and she’s not even a surgeon,  You have to keep going even as a rheumatologist. She was 32 before she was really a rheumatologist and she never took a break since kindergarten. You’re losing a lot of talent that could help serve a more diverse community because they were the ones that said, “Hey, I gotta get a job fast. I can’t sit in school until I’m 32 years old, or 35 years old to become a surgeon or a professor or whatever else.” Those are the problems that I think we need to address.

On the stress of college admissions

I actually think our system is culturally broken in a lot of ways. There’s always been a Lord of the Flies aspect. I remember reading that book in middle school, I’m like, okay, yeah, you just described the locker room or the playground — bully or be bullied. Unfortunately, it’s part of the culture and in many cases, it happens more in some of the more affluent neighborhoods, the stress and anxiety. Here in Silicon Valley, Palo Alto, I can’t afford to live in those neighborhoods that go into those high schools — they have the highest suicide rates in the country. I talk to educators there. The stress, the anxiety, the depression, there is off the charts. So that’s another thing. Talk to anyone in higher education. Roughly a third of all students are in some way dealing with some of these things. 

What is the university tuition actually buying?

Universities study everything, except some very obvious questions, like what you just asked, “What are you paying for?”You can conduct a very simple study here. Go to the upcoming Harvard graduation, and go to some kids who have some debt, “Hey, graduate, I will pay your $200,000 right now, whatever, however much debt you have, you get to keep all the knowledge you got from Harvard and all of the experiences, but you can never tell anyone that you went to Harvard University, will you take it?” I’m guessing very few people will.

On the other hand, if I were to go to a lot of people, and say, “You can pay $200,000 right now and the whole world will think that you have gone to Harvard for the rest of your life. There’s no way of proving it. You get no new knowledge.” A lot of people will take you up on that. So I think that tells you something about what people might be paying for.

I do think there are other things. Like if I offer you $200,000 but all your memories of the great conversations and friendships go away. That also would be hard for people to take. And look, I think the knowledge matters as well. But I do think the credential and the brand and the halo is a big, big, big piece of it. You absolutely can learn some of the more tangible skills at a lower cost alternative or even online.

And for the experiential, maybe the less tangible skills. You also could learn in other ways.  Some people say, “Oh, well, it’s just an important coming-of-age experience, you learn how to learn.” I don’t disagree with that. That happened to me in college. I had a great college experience. I met some of the best friends in my life, I met my wife in college. But I could imagine other coming-of-age experiences that are just as powerful. The military is one. I could imagine traveling through Europe with a cohort of students while we get jobs while we do online learning at the same time. I imagine doing internships and co-ops I’m learning, whether it’s in person or online, and getting work experience. And if I’m able to have a cohort of people my own age, that could be a great coming-of-age experience.

A not-so-great coming-of-age experience that I’ve seen happen, including people in my own family, is you have this great experience, and then you hit reality. You’re 21 years old, you’re no longer living on the well-groomed Country Club of a fancy university you attended. You have $200,000 of debt or more. You realize that in that economic seminar at the Ivy League school they treat you like you’re going to be the Federal Reserve Chairman but that’s not how the world is treating you now. You’re having trouble getting that job in economics. And if you do, it’s not paying you enough to pontificate about interest rates. We have to think a little bit more holistically outside of even just those four years.

Sal’s desire for Khan Academy

We have all the components for school in the cloud so to speak (via Khan, sister orgs and partners, through schoolhouse.world, a free online tutoring initiative) but I don’t think we’re going to be a mainstream use-case. 

I’m doing what I’m doing because I want the whole world to change. I want the people who have access to school for that school to be that much better and personalized. I want for kids not to fall through the cracks and all the associated stress and mental health issues and self-esteem issues. I also want Khan Academy and the related organizations to be like the shadow school system, the strategic education reserve, the shadow safety net, for the world, where if you don’t have school, if your school is crappy, you have, you have a safety net.

Personal resonance and reflection on Sal’s takes

  • When you take risks, cynics will be constant. Sometimes they will be right and sometimes not. But you need to focus on 2 things:
    1. Who do I actually need to convince?
    2. What evidence do I possess that says the risk is worthwhile?
  • When making a decision separate what you need from what you think you want. Then don’t be afraid to chase what inspires you (”a protagonist in your own movie”). I think of it as shedding to build.
  • Imposter syndrome can keep you grounded
  • Sal’s north star is personalized mastery learning because it increases self-esteem and well-being. It’s the maximum leverage point because our largest problems and conflicts stem from what’s in our minds. This is highly adjacent to my own “agency” argument.
  • Sal is courageous because he is trying to demonstrate that there can be a better way. He is consciously trying to be a role model through his actions and while I understand that many believe this is nudgy or righteous thinking I have argued the same point. We are suffering from a lack of healthy models and have settled into a forest of Molochian equilibriums. The “lord of the flies” broken culture around college admissions Sal uses is but a metaphor for what I see everywhere — the type of competition that is unhealthy and eats its own competitors. The people who feel on top now cannot outrun it. If it doesn’t eat them, it will eat their children.

Summary of a Summary: Accelerated Expertise

Ced Chin wrote a synopsis of Accelerated Expertise. He opens:

This is a summary of a remarkable 🌳 tree book, which presents a theory for and methods to accelerate expertise in real-world contexts. This summary is not comprehensive; it only covers some of the actionable theories and recommendations in the book and leaves out the considerable lit review and the book’s recommendations for future research directions. I’ll note that Accelerated Expertise is not written for the lay person — it is a book primarily written for organisational psychologists, training program designers and researchers employed in the US military. If you must read it — say because you want to put the ideas in the book to practice — my recommendation is to read Chapters 9-13 and skim everything else.

Accelerated Expertise is about ‘taking the concept of skill development to the limit’. This is not a book about pure theory; nor is this a book about deliberate practice in well-developed skill domains. No: this is a book that pushes the limits of two lesser-known learning theories, and in so doing have created successful accelerated training programs in messy, real-world military and industrial contexts.

The following is are my takeaways from Ced’s summary repurposed for my own future reference. As a dues-paying member of the “learn in public” congregation, I’m posting it for anyone else who might care.

Context

In the current era of frequent deployments to a variety of locations worldwide to fight the War on Terror, there are far fewer opportunities to have systematic training and practice. These are highly dynamic tasks that require considerable cognitive flexibility. Speed in acquiring the knowledge and skills to perform the tasks is crucial, as the training must often be updated and provided shortly before the personnel must deploy to the theatres where the wars are being fought.

The ideas and recommendations in the book deviate from certain mainstream ideas about pedagogy and training.

(I notice that military applications like trading are adversarial environments — skill domains involving an adversary who is constantly evolving their tactics)

What is the book about?

Accelerated Expertise is about ‘taking the concept of skill development to the limit’. This is not a book about pure theory; nor is this a book about deliberate practice in well-developed skill domains. No: this is a book that pushes the limits of two lesser-known learning theories, and in so doing have created successful accelerated training programs in messy, real-world military and industrial contexts.

    • The report  that come out of those meetings became the precursor to Accelerated Expertise  — which was prepared by Robert R. Hoffman, Paul Ward, Paul J. Feltovich, Lia DiBello, Stephen M. Fiore and Dee H. Andrews for the Department of Defence and published in 2016.

Accelerated Expertise is divided into three parts. Part 1 presents a literature review of the entire expertise research landscape circa 2016. Part 2 presents several demonstrations of successful accelerated training programs, and then an underlying theory for why those training programs work so well. Part 2 also contains a generalized structure for creating these accelerated expertise training programs. Part 3 presents a research agenda for the future, and unifies Parts 1 and 2 by pointing out all the holes in the empirical base on which existing accelerated training programs have been built. This summary will focus on Part 2.

Goals

  1. Accelerate proficiency
  2. Increase retention

This necessitated 4 sub-goals:

  1. Rapid training
  2. Dynamic adjustments: rapidly incorporate changes in the metagame
  3. Higher levels of proficiency
  4. Facilitate retention

The classic tension: mastery vs time

Mastery or expertise takes time. It’s a higher bar than “accelerating” proficiency.

But what we do know is this: the set of successful accelerated training programs that currently exist enable accelerated proficiency, not accelerated mastery.

  1. Conventional approach to trainingFigure out a set of atomised skills and lay them out from the most basic skills to the most advanced, and then design a training syllabus to teach each skill in the right order, making sure to teach the pre-requisites first, and then incrementally complexify our taught concepts and skills and training programs. We would probably also design exercises for the lower levels of skills, and attempt to create intermediate assessment tasks or ‘tests’.

    We would, in short, attempt to replicate how we are taught in school.

    Problems with this approach:

    1. It takes too long
    2. Breaking a skill domain down to atomised skills is risky — it is likely that you will accidentally cause the construction of subtly wrong mental models, due to the incomplete nature of a skill hierarchy. This then slows expertise development, since trainers would now have to do additional work to help student unlearn.
    3. Experts are able to see connections and draw links between concepts or cues that novices cannot. Teaching atomised concepts will prevent novices from learning these connections, and may in fact result in either subpar performance or a training plateau later on.
    4. Assessments for atomised skills do not translate to assessments of real-world performance.
    5. Conventional methods try to lower the cognitive load of extraneous details to isolate skill acquisition, but this risks oversimplification.
    6. It is not easy to update the training program if the skill domain changes…a hierarchical syllabus resists updating. Which lesson do you update? At what level of complexity? What prerequisites must change? (I’m less concerned about this)
    7. A counterintuitive reason: external assessments often degrade the learner’s ability to sensemake in the field.  In other words, extremely clear feedback sometimes prevents students from learning effectively from experience, which may slow their learning when they arrive in a real world domai

The NDM Approach

The NDM field uses CTA, cognitive task analysis, to extract tacit mental models of expertise…This allows you to sidestep the problem of good hierarchical skill tree design. Once you have an explicated mental model of the expertise you desire, you may ask a simpler question: what kind of simulations may I design to provoke the construction of those mental models in the heads of my students?…This core insight underpins many of the successful accelerated expertise training programs in use today.

General structure of an accelerated expertise training program

  1. Identify who the domain experts are.
    1. In depth career interviews about education, training and job experiences
    2. professional standards or licensing
    3. measures of actual performance at familiar tasks
    4. social interaction analysis (asking groups of practitioners who is a master at what)
  2. Perform cognitive task analysis on these identified experts to extract their expertise.Depending on the exact CTA method you use, this step will initially take a few months, and require multiple interviews with multiple experts (and also with some novices) in order to perform good extraction.
  3. Building a case library of difficult cases

Store these cases, and code them according to measures of difficulty.

  1. Turn the case library into a set of training simulations

This step is a bit of an art — the researchers say that ‘no set of generalised principles currently exist for designing a good simulation’. They know that cognitive fidelity to the real world is key — but how good must the fidelity be? Training programs here span from full virtual simulations (using VR headsets) to pen-and-paper decision making exercises (called Tactical Decision-making Games) employed by the Marines.

  1. Feedback in simulation training is sometimes qualitative and multi-factorial.

Some exercises like Gary Klein’s Shadowbox method ask multiple-choice question at critical decision points during a presented scenario (e.g., ‘at this point of the cardiac arrest (freeze-frame the video), what cues do you consider important?’). Learners then compare their answers to an experts and then reflect on what they missed.

A common objection

A common reaction to this training approach is to say “wait, but novices will feel lost and overwhelmed if they have no basic conceptual training and are instead thrown into real world tasks!” — and this is certainly a valid concern. To be fair, the book’s approach may be combined with some form of atomised skill training up front. But it’s worth asking if a novice’s feeling of artificial progression is actually helpful, if the progression comes at the expense of real world performance. The authors basically shrug this off and say (I’m paraphrasing): “well, do you want accelerated expertise or not?” In more formal learning science terms, this ‘overwhelming’ feeling is probably best seen as a ‘**desirable difficulty’**, and may be an acceptable price to pay for acceleration. (When Zak had to figure out what was going on at the first club basketball practice I think the coach had premeditated this desirable difficulty and this was confirmed by another parent as the coach’s “style”. It’s intentional)

The importance of a case library

*Case experience is so important to the achievement of proficiency that it can be assumed that organisations would need very large case repositories for use in training (and also to preserve organisational memory). Instruction using cases is greatly enhanced when “just the right case” or set of cases can be engaged at a prime learning moment for a learner (Kolodner, 1993). This also argues for a need for large numbers of cases, to cover many contingencies. Creating and maintaining case libraries is a matter of organisation among cases, good retrieval schemes, and smart indexing—all so that “lessons learned” do not become “lessons forgotten.”

The US Marines, for instance, own a large and growing library of ‘Tactical Decision-Making Games’, or ‘TDGs’, built from various real or virtual battlefield scenarios; these represent a corpus of the collective operational expertise of the Marines Corps.*

The underlying theory behind this training approach

Cognitive Flexibility Theory (CFT)

Core syllogism

  1. Learning is the active construction of conceptual understanding.
  2. Training must support the learner in overcoming reductive explanation.
  3. Reductive explanation reinforces and preserves itself through misconception networks and through knowledge shields.
  4. Advanced learning is the ability to flexibly apply knowledge to cases within the domain. [This is what I mean when I use the word “learning” — effective behavior change]

Therefore, instruction by incremental complexification will not be conducive of advanced learning.

Therefore, advanced learning is promoted by emphasizing the interconnectedness of multiple cases and concepts along multiple dimensions, and the use of multiple, highly organized representations.

Empirical ground

  • Studies of learning of topics that have conceptual complexity (medical students).
  • Demonstrations of knowledge shields and dimensions of difficulty.
  • Demonstrations that learners tend to oversimplify (reductive bias) by the spurious reduction of complexity.
  • Studies of the value of using multiple analogies.
  • Demonstrations that learners tend to regularise that which is irregular, which leads to failure to transfer knowledge to new cases.
  • Demonstrations that learners tend to de-contextualize concepts, which leads to failure to transfer knowledge to new cases.
  • Demonstrations that learners tend to take the role of passive recipients versus active participants.
  • Hypothesis that learners tend to rely too much on generic abstractions, which can be too far removed from the specific instances experienced to be apparently applicable to new cases, i.e., failure to transfer knowledge to new cases.
  • Conceptual complexity and case-to-case irregularity pose problems for traditional theories and modes of instruction.
  • Instruction that simplifies and then complicates incrementally can detract from advanced knowledge acquisition by facilitating the formation of reductive understanding and knowledge shields.
  • Instruction that emphasizes recall memory will not contribute to inferential understanding and advanced knowledge acquisition (transfer).

Cognitive Transformation Theory (CTT)

Core syllogism

  1. Learning consists of the elaboration and replacement of mental models.
  2. Mental models are limited and include knowledge shields.
  3. Knowledge shields lead to wrong diagnoses and enable the discounting of evidence.

Therefore learning must also involve unlearning.

Empirical ground and claims

  • Studies of the reasoning of scientists
  • Flawed “storehouse” memory metaphor and the teaching philosophy it entailed (memorization of facts; practice plus immediate feedback, outcome feedback).
  • Studies of science learning showing how misconceptions lead to error.
  • Studies of scientist and student reactions to anomalous data.
  • Success of “cognitive conflict” methods at producing conceptual change.

Additional propositions in the theory

  • Mental models are reductive and fragmented, and therefore incomplete and flawed.
  • Learning is the refinement of mental models. Mental models provide causal explanations.
  • Experts have more detailed and more sophisticated mental models than novices. Experts have more accurate causal mental models.
  • Flawed mental models are barriers to learning (knowledge shields).
  • Learning is by sensemaking (discovery, reflection) as well as by teaching.
  • Refinement of mental models entails at least some un-learning (accommodation; restructuring, changes to core concepts).
  • Refinement of mental models can take the form of increased sophistication of a flawed model, making it easier for the learner to explain away inconsistencies or anomalous data.
  • Learning is discontinuous. (Learning advances when flawed mental models are replaced, and is stable when a model is refined and gets harder to disconfirm.)
  • People have a variety of fragmented mental models. “Central” mental models are causal stories.

The emphasis of CFT is on overcoming simplifying mental models. Hence it advises against applying instructional methods that involve progressive complexity.

CTT, on the other hand, focuses on strategies, and the learning and unlearning of strategies.

CFT and CTT each try to achieve increases in proficiency, but in different ways. For CFT, it is flexibility and for CTT, it is a better mental model, but one that will have to be thrown out later on. CFT does not say what the sweet spot is for flexibility. A learner who over complexifies may not get any traction and might become paralysed. It thus might be considered a “lopsided” theory, or at least an incomplete one. CFT emphasises the achievement of flexibility whereas CTT emphasises the need for unlearning and relearning. Both theories regard advanced learning as a form of sensemaking (discovery, reflection) and both regard learning as discontinuous; advancing when flawed mental models are replaced, stable when a model is refined and gets harder to disconfirm.

The core syllogism of the CFT-CTT merger

  1. Learning is the active construction of knowledge; the elaboration and replacement of mental models, causal stories, or conceptual understandings.
  2. All mental models are limited. People have a variety of fragmentary and often reductive mental models.
  3. Training must support the learner in overcoming reductive explanations.
  4. Knowledge shields lead to wrong diagnoses and enable the discounting of evidence.
  5. Reductive explanation reinforces and preserves itself through misconception networks and through knowledge shields. Flexible learning involves the interplay of concepts and contextual particulars as they play out within and are influenced by cases of application within a domain.

Therefore learning must also involve unlearning and relearning.

Therefore advanced learning is promoted by emphasizing the interconnectedness of multiple cases and concepts along multiple conceptual dimensions, and the use of multiple, highly organized representations.

2 frustrating realities

  1. That, first, everything in the expertise literature is difficult to generalise. Some methods work well in some domains but not in others. The ultimate test is in the application: if you attempt to put something to practice, and it doesn’t work out, it doesn’t necessarily mean that the technique is bad. It just means that it doesn’t work for your particular context. The sooner you learn to embrace this, the better.
  2. Second, the authors take care to point out that a great many things about training can probably never be known. For instance, it is nearly impossible to isolate the factors that result in successful training in real world contexts — and yet real world contexts is ultimately where we want training to occur. There are simply too many confounding variables.

Ced’s final point

The overall picture that I got from the book goes something like this: “We know very little about expertise. There are large gaps in our empirical base. (Please, DoD, fund us so we can plug them!) What we do know is messy, because there are a ton of confounding variables. And yet, given that we’ve mostly worked in applied domains, our training programs seem to deliver results for businesses and soldiers, even if we don’t perfectly understand how they do so. Perhaps this is simply the nature of things in expertise research. We have discovered several things that work — the biggest of which is Cognitive Task Analysis, which enable us to extract actual mental models of expertise. We also have a usable macrocognitive theory of learning. But beyond that — phooey. Perhaps we just have to keep trying things, and check that our learners get better faster, and we can only speculate at why our programs work; we can never know for sure.”

This appears to be the price of research in real world environments. And I have to say: if the price of progress in expertise is that we don’t really know what works for sure, then I think on balance, this isn’t too bad. But I am a practitioner, not a scientist; I want things that work, I don’t necessarily need to get at the truth