Scott H Young Blog Tue, 16 Jan 2018 23:58:24 +0000 en-US hourly 1 How Much Faster Can You Learn? Tue, 16 Jan 2018 23:58:24 +0000 Say you were to optimize everything you possibly could for a particular learning goal. You used the best time-management system, you picked exactly the right tasks that would drive learning improvement, you applied tremendous motivation and effort. How much faster could you learn something than the status quo would expect?

The answer, of course, will be: it depends. But that’s rather unsatisfying, if true, because the crucial question is: what does it depend on?

Asking how much improvement over the status quo or expected rate of progress is an interesting question in many domains. In some areas, there might be reasons to suggest you could learn something much faster, maybe two or three times as fast. In others, you may not be able to beat expectations much at all, and in others you might actually do worse.

In this article, I’d like to go over what I think some of those conditions are, so you can plan your own expectations.

1. Is the Status-Quo at a Competitive Limit?

Competitive pressures define many areas of life. The type of competition you face can give a good picture of whether it makes sense to be optimistic or pessimistic about your odds of success, as I’ve written before here.

Many activities for learning are actually fairly lousy compared to a well-known alternative. Classroom learning of a language, without extensive extracurricular practice compared with learning via continuous immersion, are pretty clear examples. The former is so much worse, that it’s not unreasonable to expect massive improvements over the status quo, even if you aren’t especially smart or talented.

This situation can happen because there’s no competitive pressure to weed out inferior language learning techniques. Instead, the method tends to fit whatever other constraints are available, which tend to be the limited teacher-to-student ratio in the classroom, classroom hours, the need for gradeable assignments and tests, etc..

On the other hand, consider a highly standardized test like the MCAT or GRE. In this instance, any test-taker is free to use almost any possible strategy to prepare for the exam. Stakes are high and so inefficient methods are unlikely to survive in the status-quo.

Here, the potential improvement you can get has to be on the margin of improving over the average human constraints (time-management, motivation, efficiency) rather than picking the low-hanging fruit of a novel and highly-effective studying strategy.

The level of competition being faced matters here as well. Improving over the average is a lot easier than improving over the elite. So if your goal is to get “good” at chess, that might be something you could optimize over the typical chess amateur. However, once you hit the grandmaster level, it’s unlikely that there will be a lot of optimizations you can make that other skilled players have conspicuously missed.

2. How Much Variety is There in Which Goals You Can Pursue?

One way you can “beat” the status-quo is to seek a different goal than is typically sought. If the pursuit has this kind of flexibility, you may be able to find innovations that can allow you to learn more quickly, with different patterns of trade-offs than others have considered.

The MIT Challenge was the best example of this. What enabled me to finish the project was that I was pursuing a highly unusual set of constraints—only exams and programming projects, with any other material being used on a discretionary basis to achieve those two objectives.

This project led to some interesting trade-offs: no credentials, no alumni network or extracurricular experiences. My experience was probably also strictly less than an actual MIT student academically, due to other limitations and my own pace. However, done in roughly a quarter of the typical time, there’s enough advantages here that it made sense to sacrifice on some other elements.

In many domains, the world actively discourages this kind of variety. Standardized tests and exams exist to create easy-to-make comparisons, so choosing non-standard approaches reduces the value of such approaches when the goal is to show off a well-defined set of knowledge or skills.

However, in other domains, the knowledge you acquire has value outside of generating comparisons. In those cases, switching to less conventional goals may enable different methods to beat the status quo.

3. How Much Talent and Prior Experience Do You Have?

Nothing is learned in isolation. Prior experiences inform new ones. If you accumulate a large amount of prior knowledge it can make learning a seemingly unrelated skill or subject considerably easier for you than someone else. And, although difficult to quantify, innate talents likely play a similar role at mediating advantages some might have over others.

Unfortunately these factors are rarely under your immediate control. However, the advantages given to a lifetime of experience can be beneficial, as you accumulate more skills and knowledge, that makes further improvements over the status quo more likely in domains that may leverage those skills.

4. How Much Effort is Typically Expended?

Related to the idea of competition is an understanding of what a “typical” effort is for a particular goal. By putting in more effort, even if that effort is simply applying a much more rigorous and systematic attack at the problem, you can beat the expected amount.

When a domain is susceptible to lots of effort and the expected effort is low, this alone can make a big difference.

This tends to appear more often in amateur domains or for non-elite levels of professional skills. Again, it’s hard to put in more effort than truly top competitors because that level of effort usually has been reached by enough to set a new “normal” for performance in that area.

5. How Unusual is Your Project?

Conformity bias is high, which means that the space of possible solution paths to a pursuit is typically under-explored. Copying and emulation, particularly of higher-status people, is an instinctive learning process most people use, and which tends to work fairly well most of the time.

Because the solution space to a given achievement isn’t fully explored, however, there’s the possibility of getting lucky and hitting upon novel approaches that simply haven’t caught on yet. Once again, the level of competition can give some insights into how likely this is, but it’s true to some degree in almost all pursuits.

More unusual approaches to learning something will have a higher variance of outcome than following a tried-and-true path to mastery. However, there are sometimes innovations that can come out of this that are rarely used, yet nonetheless, contribute to performance.

What Should You Expect to Achieve?

I tend to go into my projects with a much more conservative attitude than it probably seems from the outside. I usually suspect that significant improvements over the status quo probably aren’t possible, and then look for reasons why that opinion might be wrong, rather than assume the opposite.

I think this is especially true for extremely competitive domains, like you’d find in important standardized tests, chess, music or athletics. Here learning innovations likely still exist, but they are going to be more modest and harder to find.

However, many things you might want to learn don’t reach this rarefied air of competitive standards and the bar to innovation may be low enough that all it takes is a serious effort to overcome it. I’ve already mentioned languages, but tons of other subjects and skills exhibit similarly low bars which can be hurdled over with some thought and motivation.

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What’s Next? Thu, 11 Jan 2018 19:59:39 +0000 Completing a big project or achieving a goal can lead to an unexpected experience. Part of you feels proud and satisfied—you did the thing you wanted to do. But another part of you can end up feeling totally lost.

On the one hand, completing a hard-won project has given you the thing you set out to get. But, on the other hand, achieving it has also taken something away. That same ambition helped structure your life, your thoughts and your habits. With the goal achieved, there can be a vacuum as you’re not quite sure what to do next.

It’s a bit of a shame that so much ink has been spilled on how to set goals and achieve them, and relatively little on what to do after they’re done.

A Few Common Post-Achievement Experiences

Before I attempt a look at any solutions, it’s probably best to understand the different facets of the problem. I think there’s actually a few different distinct experiences one can have after completing a big project or goal.

#1 – Disappointment

One problem with many goals is that they’re set out to magically fix problems that they really can’t address. You may want to lose weight to address your relationship problems, only to find the skinnier you has all the same anxieties and difficulties from before. You might want to jump ahead in your career to feel successful and end up feeling no more valued than before.

#2 – Boredom

Working hard on a project occupies a lot of time. Putting time in towards a purpose can be occasional stressful. You might even wish you were less busy when working on a goal. But when that goal goes away, you may find it difficult to find something to do that is equally compelling.

#3 – Feeling Lost

Goals don’t just occupy time, they occupy your need for direction and meaning in your life. Some goals naturally extend outwards so that achieving them doesn’t rob your trajectory of direction. However, other goals, upon completion, remove an orienting device from your life that can give you a feeling of existential vertigo, as you aren’t sure where you should move next.

These different experiences can come separately or combined, depending on what happened with the goal you set. Their intensity is often a feature of the relative intensity of the goal that preceded them. Short projects create less of a vacuum than realizing lifelong dreams.

Should You Stop Setting Goals Altogether?

Given how common these post-achievement negative feelings actually are (especially since people tend not to talk about them), after going through it once, many people think perhaps that they shouldn’t have set goals in the first place. Why work hard to achieve something if it turns sour once you taste it?

I don’t agree with this reflex, but I understand it. The truth is that a lot of these unpleasant feelings can go away, once you have the right perspective.

#1 – Remedying Disappointment

Disappointment happens because you had unrealistic expectations for what achieving a goal could do. If you feel down, or even depressed, after achieving a hard-won goal, you may want to look at what your expectations were going into that project.

Be on the lookout for situations where solving one problem permanently improves your emotional state. This is usually unlikely, as our emotions have a tendency to adapt to our relative circumstances.

Similarly, exaggerated spillover effects can also lead to disappointment. If changing one isolated thing is supposed to bring tons of ancilliary benefits to unrelated areas of your life, you should be be cautious.

#2 – Remedying Boredom

Boredom often has a simple solution—set a new goal. Especially if the previous process of working on a goal had minimal costs to other areas of your life, this might be feasible.

These days, I find myself mostly setting goals because I enjoy life more with a goal than without it. This may be an extreme, as most people set goals primarily as a means to improve something rather than an end in itself, but the dual nature of goal setting as both a means and an end is worth appreciating even if you still feel there are many things you want to improve in life.

#3 – Remedying Feeling Lost

When a goal breaks with a continuous direction in your life, either because further pursuit of that goal is impossible or because your motivation to go further in that direction is impossible, this often creates a feeling of being lost. You don’t know where to go next now that the orienting direction of your life has diminished.

This moment often creates a spiritual or religious impulse. The vacuum of direction creates an intuitive desire for an ultimate direction or purpose, one which cannot disappear and therefore one cannot feel lost.

While this may work for some, I tend to subscribe to the philosophy of David Chapman, that such “ultimate” purposes and motivations are inherently unstable. This instability isn’t a turn to nihilism or despair, but rather a suggestion that mundane goals and purposes are full of meaning, even if it may not be within the power of the human mind to wrap them up into an ultimate direction.

As a solution, I believe feeling lost, for a time, is often a good thing. Trying to shut down these moments, often misses a valuable opportunity for growth, as the chance to realign values and beliefs with the current context of your life becomes much easier.

However, this feeling too can carry on too long. Especially if, out of fear of being lost again after pursuing a new goal, you turn to seek a final direction that will never make you feel lost again. It is better here, to recognize that meaning and purpose exist all around you and that you may have to reorient yourself to the strands of it to fit your current situation, even if there are no guarantees that the new trajectory will last the rest of your life.

Achieving a goal can be a wonderful thing. But it can also lead to some unexpected experiences if you’re not prepared for it. If you recognize what those experiences imply, whether they’re unrealistic expectations, unfilled time and energy, or a realignment of values and direction, they can end up being a positive thing.

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Choose Your Signal Wisely Thu, 04 Jan 2018 19:39:47 +0000 Psychological research has demonstrated that human beings are particularly susceptible to what are called framing effects. These are differences in the way we respond to a situation, based on how it is framed for us, rather than on its substance.

To take a particularly striking example, American physicians were presented with the following scenario:


To which physicians overwhelmingly preferred the former, less risky option. However, consider this slightly modified scenario:


Now the response was inverted. Most physicians preferred the second option by an almost equal majority as the first one had presented itself. Here’s the kicker: these two scenarios are identical! The only difference is the first is framed in terms of lives saved while the other is framed in terms of how many people will die.

This isn’t the only example where subtle changes in the way a problem is presented to us can radically alter our decisions in seemingly irrational ways. However, it does show that what matters often isn’t merely the facts that we face, but how we frame those facts, that lead to different decisions.

Signal and Noise

Another common problem people face is choosing what to focus on in a complex situation where the outcome of any event may have multiple causes.

Consider starting a business. What matters? You could say that product quality reigns supreme, to which you’d find plenty of examples of companies succeeding on the basis of superior products. You could argue that well-timed and targeted marketing is all that matters, pointing out companies that succeeded on the basis of catchy slogans or ad campaigns. You could argue that the dry fundamentals of finance and accounting matter more, with knowledge of costs and systems trumping external factors.

The truth is, you could argue any of the above propositions and you’d probably be right, at least some of the time. Businesses do often succeed and fail on the basis of their product quality, marketing message or cost control.

It’s also clear that none of these factors can explain everything. Regardless of what you take to be the dominant trend, there’s going to be a lot of unexplained, leftover variance in the outcomes of different businesses. Business success is, to use a statistical concept, noisy.

John Nerst argues that we tend to frame our discussions in terms of a signal, which we put emphasis on as the main explanatory variable, and a corrective, or all the other things which change our main result, but don’t fundamentally contradict it.

In his view, this signal-plus-corrective view can lead to some interesting situations where people may fundamentally agree on specific cases, but disagree more generally depending on which view they take as their signal and which as their corrective. To use an example from politics:

“Two people with political views like: ‘The free market is extremely powerful and will work best as a rule, but there are a few outliers where it won’t, and some people will be hurt so we should have a social safety net to contain the bad side effects.’ and ‘Capitalism is morally corrupt and rewards selfishness and greed. An economy run for the people by the people is a moral imperative, but planned economies don’t seem to work very well in practice so we need the market to fuel prosperity even if it is distasteful.’ . . . have very different fundamental attitudes but may well come down quite close to each other in terms of supported policies.”

The reason for the wild divergence in rhetoric for positions which may not be so far apart seems to come from framing effects. One side frames the goodness of markets as the signal, corrected by occasional injustices, the other side frames the injustices of markets as the signal, corrected by occasional efficiencies.

While Nerst focuses on how these framing effects distort our discourse on contentious issues, I believe they can have an important influence on how we handle things, even in our own private lives.

Deciding What is the Signal

Whatever you frame as the signal will tend to receive a disproportionate share of your attention. Conversely, whatever is not the signal will be seen as noise, and receive a lot less attention. Whichever factor gets picked as the signal can therefore have dramatic effects on the decisions you make.

Consider again our original business example. Success in business mostly depends on X. Whatever you answer X with will be your signal, and that will be the quality you’ll aim to optimize.

I know entrepreneurs who have implicitly picked marketing as their signal. These people are relentless in getting media exposure and word of mouth out about their business. And they often get it too, with television appearances, write ups in newspapers and buzz on social media.

The downside, is that by picking marketing as a signal, that necessarily relegates other business factors to the category of noise. Where marketing and product quality trade off, say in a product that oversells its value to users, or attracts a large number of people rather than the best qualified customers, this choice in signal tends to emphasize itself.

I know entrepreneurs who have implicitly picked product quality as their signal. Once again, they usually get it. High-quality products which are meticulously designed. The downside, again, is that these people may sacrifice on things that will get their products exposure, if it has a negative impact on quality—say by sacrificing speed of delivery or scope of distribution.

Where tradeoffs aren’t explicit, what you focus on for the signal can still have important impacts simply by how you allocate your time. It’s not possible to work on everything that could theoretically improve your business, so you end up emphasizing those that are in the signal, to the detriment of whatever is considered noise.

How to Pick Your Signal

All of this implies that picking a signal is going to have tradeoffs. Like the framing problems discussed above these tradeoffs will probably be handled at a subconscious level. That means picking your signal wisely will be very important for the types of side-effects it might create.

The first consideration should be how much your signal actually explains of the outcomes. If you pick an irrelevant attribute and boost it to the level of the signal, you may be disappointing yourself when you can’t actually control outcomes much.

In a fitness arena, it’s now known that diet matters more than exercise for the purposes of losing weight. Given this, if you pick exercise as your signal rather than diet, you may have a harder time shedding pounds because fitness doesn’t account for as much as you’d like it to.

The second factor should be how much of your signal is under your control. If you pick a signal that is good at explaining differences in outcomes, but is totally outside of your control, you may still struggle to shift outcomes.

Intelligence is an important factor, perhaps the most important factor, for success on intellectual tasks. But since we can’t generally improve our intelligence in the short-term, it’s probably not the best one to focus on. Indeed, studies with students find that those who believe in hard work tend to do better than those who take fixed ability as signal.

The third factor to consider, presuming you’ve picked a potential signal that has good explanatory power and is susceptible to your decisions is to look at how your choice of signal will create side-effects. Choosing the least-bad side-effects may be a reason to choose between seemingly similar choices for signals in your pursuits.

I generally opt for product quality over marketing in my own business for this reason. They both matter, obviously, but I prefer the subtle side-effects that a product-quality-as-signal mindset has over one that favors marketing.

Re-evaluating Your Signals

You already have signal-noise frames set for every area of your life. So, in a sense, you’ve already made a decision about what matters and which things are the annoying details that mess up your mental model. The key, therefore, isn’t choosing a signal, but potentially re-evaluating yours.

For any area you’re tackling in life, ask yourself what you believe is the most important attribute for success.

Next, you might want to check whether what you see as obviously being the signal is so obvious to other people. Poll some of your peers or people you respect for what they believe is the most important factor. If you get diverging opinions, you can start to see how different people have picked different signals to focus on.

Ask yourself if any of the signals you heard could plausibly be seen as a main explanatory variable AND a factor you can potentially control. “Luck” is often thrown around as a main explanation for success, but it probably isn’t the best signal to account for, even if it is quite prominent.

Next, try to see if you can spot any patterns of side-effects or weaknesses that people encounter based on their choice of signal. What traps do they fall into? What do they neglect at the expense of something else? Which of these pitfalls seems least-bad to you?

If you can go through all three of these steps with a signal that is not your current emphasis, you might want to open your mind to shifting what you focus on in that area. If the alternative emphasis has more explanatory potency, is more malleable to your decisions and if its side-effects are more tolerable, you may consider putting it as your signal.

Ultimately, getting the “correct” view of reality isn’t possible. At best, we can hope that our frames capture the most important features of a problem and that the simplifications they generate aren’t too harmful. However, once you see that reality is more than just your signal plus a little noise, you also open up the door to seeing things from a different, and sometimes a lot more valuable, perspective.

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Book Club: Godel, Escher, Bach (December 2017) Thu, 28 Dec 2017 23:44:41 +0000

This month we read Godel, Escher, Bach by Douglas Hofstadter

This is a fantastically weird and wonderful book. At one level, the book is about a parallel between three people: Johann Sebastian Bach, Kurt Godel and M.C. Escher, in particular how their work in music, math and art manages to loop back on itself and express a kind of self-referentiality. On another level, however, this book is really a hypothesis about the human mind itself, that selves and souls can come out from inanimate matter the same way that M.C. Escher’s hands draw themselves or Godel’s creates math that proves that it cannot be proven.


If you would like to stream audio on your browser, click here listen on Soundcloud. If you’d like to read the transcript, you may do so here.

Here are some of the highlights from this month’s review. First off, we establish what Douglas Hofstadter is referring to when he talks about a “strange loop”; it’s perhaps easiest to refer to the visual artist M.C. Escher to explain this very sophisticated concept:

An example would be [his images] of the drawing hands where he has drawn two pictures of hands which are holding pencils and drawing themselves. Other ones Escher has includes birds which turn into other animals and shift between the foreground and background. He even has one where there is a person looking at a picture in a museum and the scene is warping so that he is part of the museum itself.

So, this is something that I think is easy to see to visually, this kind of paradox, and it’s easy to dismiss it as well as being a bit of trickery. You might not even be a fan of M.C. Escher’s art, you might consider it too obvious. 

However, I think it’s a really good entry point to grasping this idea of a strange loop. Now what I think Douglas Hofstadter calls a strange loop or this tangled hierarchy is where you have layers of something where something is built on top of something else.

Next, I discuss mathematician Kurt Godel and how he showed that there were limits to logic itself: 

Hilbert’s problem was that, at the time, there were no different axiomatic systems for mathematics. His idea was that if someone could come up with a proof that shows that standardized axioms exists, and was consistent and also complete, that would be a major triumph. We could feel very secure resting in our knowledge that this mechanical system would work all the time. And what Godel did in the 1930’s, was that he showed that this was actually impossible.

Godel showed that any system that you have, any set of rules that you have, is powerful enough to represent the basics of natural numbers (the basics of arithmetic) will ultimately undermine itself by creating situations that we know are true but cannot be represented.

To explain Godel’s proof in another way: 

Think about how 2 + 2 = 4. You have a two, you have a plus sign, you have a two, you have an equal sign, and you have a four. What Godel is doing is saying, let’s take that 2 and put it in a number, let’s take that plus sign and put it as a number, let’s take that 2 and put it in a number, let’s take that equal sign and put it into a number and let’s take that 4 and put it into a number.

Now you have one super long number that represents 2 + 2 = 4 as not just a number but as something that involves plus signs and equals signs and has separate numbers but as just one big number. 

Okay so what can you do with this? Well if you go through a little bit of work what you can end up doing with this process is you can make a statement that is the mathematical equivalent of saying “this statement is false” or more specifically what it is saying is “this statement has no proof.”

There are also mind-bending ramifications of Godel’s work on our current concept of human consciousness:

…. he’s identified a system that has reached a level of sophistication that has the ability to loop back on itself. What’s the extension here? One of them is the idea of human consciousness. He’s saying that what perhaps the self is, what we are, as not bodies but sort of an abstract quality, what makes us different from rocks or computer programs that we have today, is that our machinery for representing things is sufficiently complex and we can represent ourselves in that machinery. Moreover, we can represent ourselves representing ourselves. 

We can have thoughts about our own thoughts and about the person thinking the thoughts and about their relation to the world at large.

Feel free to join in on our Facebook Group Discussion I’d love to discuss this book with you there, thanks. January’s book is James C. Scott’s Seeing Like A State

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Discovering the Meta Mon, 18 Dec 2017 18:02:03 +0000 One of my favorite early lessons in entrepreneurship was the idea of working “on” your business instead of merely working “in” your business.

To see the distinction, imagine running a restaurant. Here, working “in” the business is clear. Make delicious food. Offer great service to your customers. Keep the place clean and inviting. Being able to cook and host is often a motivation for many to start a restaurant.

Running a restaurant is a lot more than cooking and waiting tables. It’s business strategy, marketing, cost accounting and pricing. Working “on” the restaurant means thinking one layer above to examine what processes the business itself consists of and how you can improve them.

Many restaurateurs fail because they can’t think at that higher abstract level. They intimately understand the food and service dimensions. But they struggle because they can’t see the processes and systems that result in high-quality food, new customers and steady profits.

There is a pattern of thinking here, though, that’s a lot more general than just about business success. This is the idea of a basic level of understanding and a “meta” level, which takes as its objects the very elements of thinking in the basic level itself. I believe there’s reason to believe that much of what we deem “intelligence”, as opposed to mere calculation, involves this kind of “meta” leap in conceptual understanding.

“Aha!” Moments When Discovering the Meta

I can attribute one of the biggest changes in my own life to one of these moments of discovering a hidden meta layer. In this case, it was thinking about habits, goals and productivity systems instead of just the objects of those pursuits.

The “Aha!” moment for me was discovering that, instead of just trying to work on some project to achieve a particular goal, I could work on my habits directly to achieve that goal. Instead of blaming a failure on willpower or discipline, I could look at the habits that failed me and see how one could be redesigned in the future to avoid those problems.

After discovering this meta layer for myself, I became a little obsessed with it. I’m not alone. Many people I know who started blogs on personal development often do so with habits, goal setting or productivity systems as a first topic. The discovery of this “meta” layer to life can feel so profound that it’s hard to believe you didn’t see it sooner.

Meta-Metas or Turtles All the Way Up

There’s an old joke about an shaman and a scientist. The scientist asked the shaman what the origin of the world was and the shaman said that the world was resting on the back of a gigantic tortoise. The scientist responds smugly, “but what does the tortoise stand on?” The shaman responded casually, “Another tortoise.” “But what does that tortoise stand on?” the scientist asked again. The shaman replied, “It’s tortoises all the way down.”

Metas are a bit like tortoises, except in this analogy they stack up rather than stack downwards. Once you have a certain level of understanding of one layer, it’s always possible to reach out to a new higher layer and start seeing the “meta” of the layer you had previously discovered.

Consider our restaurant. The amateur restaurateur sees the business in terms of food and service. The smarter restaurateur sees it in terms of business processes that create the food and service. The smartest restaurateur, sees those business processes in terms of strategies that compel them. Metas on top of metas.

Or consider habits. The initial layer is to strive after things, and blame amorphous properties like willpower or motivation when you can’t reach them. The meta layer is to investigate the processes that guide willpower and motivation—habits, goals and systems. The meta-meta layer is to think about the ideas and philosophies that guide those meta-level objects. What kinds of goals should I have? What habits are meta-stable? Should a system be thorough or sparse?

You Can’t Force the Meta

Clearly meta-understandings are incredibly valuable. Since a meta layer encapsulates the layers below it, you can always reason downwards, if that is more appropriate. The restaurateur who has reached the level of seeing business processes, for instance, doesn’t automatically forget about the food.

Given this idea, it might seem reasonable to ask whether we can generate these meta-level insights directly. The pattern is relatively clear—instead of reasoning about the objects directly, you reason about the higher abstractions that themselves reason about the objects. This might seem to form a “pump” so to speak, that would allow you to generate meta layers automatically, simply by thinking hard enough.

Unfortunately, however, I don’t think you can force it. I believe that this is because the meta comes from having detailed understanding of the layer below. If you don’t have that, the “meta” layer you generate has no power. You might be able to understand that it exists, but you can’t actually elevate your thinking towards it.

To give an example of this, about a year or so ago, I started learning to play chess. I had learned the rules of the game as a child, but I never had any skilled opponents and didn’t practice. Then, recently, I started playing again with a good friend who was quite skilled at the game.

Chess knowledge is easy to think in terms of layers. The most basic understanding of chess are the rules themselves. Bishops move diagonally. Rooks move horizontally and vertically. Pawns move only forward, except to capture, which has to be on a diagonal.

The first “higher” layer of chess is encapsulated in the patterns that are not part of the basic rules, but are inevitable consequences of them. One such pattern is a “fork” where your piece simultaneously attacks two of your opponents pieces, and can sometimes force them to sacrifice one if they aren’t properly protected. There is no rule for fork in chess. It’s a higher-layer that comes from understanding the basic rules well enough to see that this pattern exists above them.

But there’s more than just forks. Further layers of chess become increasingly abstract. Great players can often lose on lower-level principles of chess, such as material, sacrificing a pawn or piece, but gain on meta principles like activity or positional dominance.

The thing is, when I started learning about chess as an adult, I knew about these things. I heard about concepts like pawn structure, aggressiveness, sharpness in tactics, etc.. but I couldn’t *see* them. I knew those layers existed, but when a chess master pointed out that a certain setup was favorable to white because of one of these higher-level concepts, I was blind to it. They literally saw the chess board differently than I did because their mastery of the lower levels allowed a facility of “meta” understanding.

Side note: Sticklers may be rustled at my overly loose usage of “meta” here. “Meta” interpreted strictly means something is “about” itself. So meta-chess would be… chess about chess? Maybe that’s meaningless. Incidentally, this is a problem with “meta” not being a concept in and of itself, but a prefix which depends on which word is used as the base. Therefore, there are many things which exhibit “layer-hopping” in the same way as strictly “meta” ideas, but may not officially qualify because the correct noun is lacking to truly make it reflexive. This is a little bit of an unconventional extension of the idea of “meta”, so for those who want to limit it strictly, feel free to substitute my overuse of the word “meta” with the somewhat more general (and in my opinion less illustrative) idea of “abstraction.”

Meta and Chunks

These days, the popular account of such understanding is that of “chunks”. Human working memory is famously limited to just a few objects. Our mental powers comes from being able, through exposure, practice and insight, to bind atoms of understanding together into larger and larger chunks.

Experts have expertise because their repertoire of lower-level chunks allows for increasingly abstract patterns to be deftly employed when they’re needed. Physics experts see physics problems differently than novices. They see them in terms of deep principles rather than surface features of a problem. An expert might look at a problem and say, “oh this is a conservation of energy issue,” whereas a novice might say, “hmmm this is one of the ones that has a string and a pulley… which formula do you use for those again?”

This view of chunks also implies that meta-layers, although I’ve conceptualized them as existing discretely on top of earlier understandings, aren’t really discrete. While the idea of working “on” one’s business as opposed to “in” it seems fairly clear, there’s still a lot of crossover. Does opting for smaller portion sizes represent a basic-level strategy of presenting fancy-seeming dishes? Or is it a higher level strategy of market positioning? It’s often not clearly separate, and the reasoning compelling such choices can blur boundaries.

What I think is useful to the meta understanding, rather than thinking about chunks alone, is that the meta understanding implies that often what you’re doing when building expertise is making understandings that directly manipulate the upstream causes of your previous reasoning.

Meta is Math

There’s a powerful analogy here between the meta-climbing of increasingly abstract conceptual understanding and learning mathematics. In a way, mathematics is a kind of rarefied meta-level thinking.

The hallmark of math is this kind of conceptual climb. You start by counting on your fingers. That generalizes to numbers that go past ten. Then you get arithmetic—plus and minus, multiply and division. What if you multiplied the multiplier? That gets you to exponents and logarithms. What if you took partial numbers, extended the number line backwards or allowed it to rotate? That gives you the continuum, negative numbers and complex numbers, respectively.

The hallmark of mathematics is to take one level and generalize it or extend it in some way. This goes on and on and on until eventually you have things like commutative rings in abstract algebra, which are completely opaque to anyone without advanced mathematics degrees.

Meta-levels have a similar flavor. There’s the layer you understand. There’s the layer above that you can see exists, but can’t really work with. Then there’s the layers above that which you don’t understand at all.

Depending on your feelings towards the topic, you may feel those meta layers are genuine, and represent a deficit in your understanding, or you may feel they represent and increasingly elaborate form of intellectual masturbation, with people coming up with increasingly esoteric descriptions of a fundamental lie.

The existence of a meta-generating process doesn’t say anything about its veracity, unfortunately. A genuinely useful process may get derailed if it introduces a falsehood at a lower layer. Then, you might get increasingly sophisticated elaborations of that falsehood. Alchemy and astrology had tons of smart people as adherents, but the sophisticated abstract understandings collapse since that’s not how stars or substances actually work.

Pathways to Finding the Meta

While I don’t think you can “force” a meta-level understanding where the object level is insufficient to support it, I do think the opposite is possible. That is, I think it’s possible to have a rich object-level and simply not notice the meta level sitting above it.

This explains why discovering the meta, for many, is an “Aha!” moment of insight. Discovering habits is such a personal development leap for many because they’ve trained themselves to take action to reach goals, but it didn’t occur to them to think about the processes that generate the behavior itself. If you’re ready, that insight can be digested relatively rapidly.

This suggests a path for finding the meta in many areas of life, whether it be self-development, chess, physics or art:

1. Acknowledge that there are levels beyond what you can currently perceive.

This is especially important if you have a tendency to dismiss them. “History is just one thing after another,” or, “All modern art is bullshit,” are meta-dismissing comments. Now it’s certainly possible that established views are wrong. It may be the case that historians are overconfident in their conceptual understanding of how events unfold, or that modern art’s philosophy is suspect.

However, if we accept that virtually everything has meta layers and meta-meta layers, turtling all the way up, then one needs to be careful dismissing the layers one can’t currently see as not actually existing. As I explained earlier, I simply couldn’t see the chess concepts the grandmasters were talking about. If chess had been a more subjective domain, I might have wanted to dismiss their concepts entirely simply because I lacked the ability to see them.

2. Probe your own meta-levels. You may be ripe for an “Aha!” moment in one of them.

Ask yourself what would be the meta level of the problem domain you’re trying to work in. What would it mean to “go up one level” in your business, career or philosophy? The answer may give you clues as to how to climb up there, if you’re ready.

3. Develop richer understandings one level below.

If you’re not ready, the answer will probably be vague or unintelligible, just as the advanced chess concepts were to me. The solution here isn’t to dismiss the meta or ignore it, but to work on enriching your understanding of the layer below. As that foundation ripens, it will be easier and easier to think of it abstractly until you’re ready to move up to the layer above.

Climbing Meta-Ladders

This idea, that meta-layers can only be reached with sufficient understanding of the layer below, I think prevents the biggest worry of this chain of reasoning, namely that if you obsess over the meta layer, where does it stop? Don’t you just go off into an increasingly heady realm, detached from the object-level concerns until you start asking those bizarre philosophical questions like what the meaning of the word “is” is?

This worry, of course, is perhaps a symptom of runaway abstracting without first trying to get a grip on the layer below. Properly construed, a higher meta layer should have even greater familiarity with the objects below it, so that they are enriched by that understanding, rather than forgotten.

That being said, perhaps there is a “meta” to this entire chain of meta-reasoning I’m presenting right now. Namely, when to think about the meta layer and when to focus on the ground-layer itself. If that’s the case, then perhaps I haven’t developed a sophisticated enough understanding to access that rung in that meta-meta. However, I’ll keep thinking about it, and perhaps I’ll discover something once I do.

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Book Club: Average Is Over (November 2017) Wed, 13 Dec 2017 17:51:54 +0000

Last month we read Average Is Over by Tyler Cowen. In this eye-opening book, renowned economist and bestselling author Tyler Cowen explains that high earners are taking ever more advantage of machine intelligence in data analysis and achieving ever-better results.



Here are some of the highlights from this month’s review. First off, we start with a look at how technology trends (automation, outsourcing, and what I call, “clustering”) and how they will change your career path in the future.


This is a popular topic, it seems like every day you see a new opinion piece about robots taking all of our jobs… I think a lot of these pieces exaggerate the facts. Personally I think that although the advancements in deep learning and neural nets are impressive, I don’t think we’re on an imminent path and there’s going to be a level of artificial intelligence that can do all the jobs that humans can do. 

But what you really want to be doing in your profession is pushing up the scale, because the further you push up the scale, the deeper your skill and competence is, the more you’re going to resist erosion from this middle vacuum of white collar easy to do jobs that will be taken over by machines or outsourced to other countries.

Next, I discuss Cowen’s different phases of machine and human relationships in the context of work: 

He [Cowen] really maps out a transition path that he imagines we’re going to go through. This isn’t something we go through collectively, meaning that we’re entirely at one stage and then we’re entirely at another stage, but rather, individual industries and individual job positions are going to go through these stages and it may take a short amount of time, or it may have already happened for some… There are four stages in total.

The first is “man only” where there’s a human being who is working on a specific job. The next is the “human + machine” where the human is doing the bulk of the work but is using the software or the tools to facilitate the work.

The next is a “machine + human” combo where the machine is doing most of the work and the human being is there simply to monitor. To make sure it doesn’t go wrong, to fix common errors, etc. Finally, we have the machine only where now, there’s isn’t really much room for the human being to improve upon the machine’s results. The machine itself gives the best results possible.

So what does all this mean for your future?


In some ways, this is already the world we live in. This is a world where we’re all using software all the time to do our jobs. Many, many opportunities are coming because the person needs to understand how to use the software better. But I think that with a lot of innovations in machine learning and pattern recognition this is only going to continue and we’re going to have more and more sophisticated software programs that are going to require more and more sophisticated people to employ them.


Will we all have to become programmers and engineers to ensure job security in the future?

One of the mistakes that Tyler Cowen notes that many people make is that they make the erroneous assumption that because innovations are coming from engineering, science, mathematics, technology, and so on, there’s many people who think “well maybe it’s the case that these are going to be all STEM jobs so the only thing we can do is teach everyone to become a programmer or an engineer” and what the author suggests here is that that’s not the case.

A lot of the professions that are going to come up are not going to be technical jobs. Instead it’s going to be using technology to do some job task that is not necessarily technical.


Feel free to join in on our Facebook Group Discussion I’d love to discuss this book with you there, thanks. December’s book is Godel, Escher, Bach: An Eternal Golden Braid by Douglas Hofstadter.

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Know Your Competition Wed, 06 Dec 2017 01:16:30 +0000 Almost all human accomplishments are, directly or indirectly, judged in competition with others. This is most directly true in domains such as sports or entertainment, where awards and trophies go to some, and not others.

What matters here isn’t absolute performance, but relative performance. Absolute performance can often go up and up, yet because it rises with competitors as well, the standards of what counts rise in lockstep. Before Roger Bannister, running a four-minute mile was thought nigh-impossible. Now it happens regularly. The standards get raised, so what determines success as a runner goes up with it.

Even in domains that aren’t directly competitive, there is still a broader, implicit kind of competition. Singular accomplishments are judged on their impressiveness, indirectly, through a complex comparison with other kinds of accomplishments. Learning to speak another language fluently is moderately impressive in North America, where monolingualism is common. But learning to speak several was common amongst the educated elite a few centuries ago in Europe. Thus the friend that speaks a couple languages fluently impresses more in modern America than it would have in seventeenth century France.

I’d argue that even the most private, resistant-to-comparison situations tend to have subtle, unconscious competitive layers. Consider romantic relationships. Only the most crass compete in competitions over who gets the most dates or has the best spouse. Yet, I believe a lot of relationship happiness comes from beliefs as to whether we have a good spouse (in terms of looks, personality, faithfulness).

Since competition, direct or indirect, has a large influence on what we qualify as a success, I think it’s worthwhile to examine. In particular, I think there’s different types of competition and they imply different things we should do about it. If you see all competitive domains the same, you’re bound to draw incorrect conclusions about what action to take.

Level One: Competing Against the Middle

The first type of competition is competing against the middle. This is when being better than average is enough to count as success.

In a career situation, being an employee or freelancer is, in many cases, a competition against the middle. This is because the scale at which people can compete is relatively small, and so the very best performers are often removed from competition because demand for their talents is too high compared with what they can provide.

A personal coach or therapist competes in this domain. You don’t need to be the best possible coach to succeed, because the very best coaches are completely saturated with demand. Because their success can’t scale easily, you can still compete even if you aren’t the best.

This is true in business and career settings, but this level of competition is also present in many other sorts of achievements. Live music, restaurants and original artwork also have limited scope for the greatest successes. Most interpersonal forms of impressiveness (charisma, fashion, humor, etc.) are also limited in this way because people experience them through face-to-face interactions, therefore you’re unlikely to ever be compared on funniness with Chris Rock, or compared on charisma with Bill Clinton, since most people will never have an extended interaction with those people.

With this level of competition, success can often be achieved simply by putting in the effort. Although some skills are possibly more learnable than others, the bar of competition is relatively low, and so it’s not unimaginable for someone with low or moderate talent to compete well here, provided the interest and commitment is there.

Level Two: Competing Against the Top

The second level of competition is competing against the top. This happens when you need to be one of the best in your category to succeed.

Blogging is this kind of competition. As is running any business that sells products. Now, the most successful people can compete with you directly. Readers of this blog can read anyone else’s blog on the planet, so it’s not enough that I be the best writer in my local environment, I need to be the best of your options to attract your time away from people like Tim Ferriss, Malcolm Gladwell or Paul Krugman.

This kind of competition occurs whenever your competitors can scale. Live music can succeed because big successes need to have big concerts, which lose some of the intimacy and connection with the band that a small show can provide. However, once you start selling or streaming your music, then there’s no difference between you and famous bands, so the competition goes up to this level.

Similarly, original art can compete locally, but prints and reproductions compete here as well. The extent that people don’t care about original art can also mean you’re stuck competing at this level whether you like it or not.

This isn’t the highest form of competition though, because niching and differentiation can allow for many more than a single player to stay in the game. I can compete as a blogger against Ferriss, Gladwell and Krugman because my writing isn’t quite like theirs, so it’s possible you might like to read my blog, even if objectively I’m less popular or lower quality.

With this level of competition, it only really makes sense to compete if you’re going to devote yourself completely. You should also consider competing only in areas where you have some natural advantages. In other words, don’t try to compete in an area here if your talents here are low compared to other talents you possess, simply because it is going to make hard success even harder.

Level Three: Competing Against The Singular Best

The final level of competition is when you are competing against the best possible person. This happens when there are weak barriers between categories, so someone who dominates in one niche will likely dominate in all other related niches, leaving little left for you.

Investing is this kind of competition. To earn a risk-adjusted higher rate of return than the market, means that you need to have actionable information about why that asset is mispriced. However, all other investors in the world can potentially do the same—including well-heeled Wall Street financiers with insider information, supercomputers and mathematical geniuses.

This doesn’t mean it’s impossible to beat the market, just very hard. You have to be able to answer not only why a particular asset is priced incorrectly, but also why nobody else has noticed it.

Of course, this doesn’t mean one shouldn’t invest money—the market still has a positive rate of return, so passive investing still makes sense for many. Active investing might also make sense in cases where these assumptions are violated (say the potential pool of investors are limited, or highly-skilled investors are ignoring the opportunity because it is too small, etc..)

With this level of competition, it rarely makes sense to compete at all. If you are going to compete, then there needs to be an overwhelmingly strong rationale for why you are, in fact, the best person in the world, in order to succeed. If that rationale isn’t present, being #10 or #115, which would nearly guarantee success in other contexts, is still a failure.

Example: Physics Success

One way to understand these three levels is to look at success in a field like physics.

Learning physics is a level-one success goal. Implicitly there is some relative performance standards because if physics got easier to learn, people would probably expect somewhat more learning in order for you to qualify has having above-average physics knowledge.

To see the competition inherent here, remember that a thousand years ago nobody had the physics knowledge of the average high-school senior. Most of us have a general gist about ideas like inertia, that electricity and magnets are somehow related or that the earth orbiting the sun is because of the same force as apples falling to the ground. The fact that such general insights don’t count as “knowing” physics is a sign of a relative increase in standards.

Becoming a physicist is a level-two arena. Now, it’s not enough to know physics better than average. You need to know it better than the “top” physicists. You can specialize in narrow areas of research, and thus eke out a living being merely in the top hundred thousand or million physicists in the world.

Winning a Nobel-prize for physics is now a level-three goal. It’s not enough to be good. It’s not even enough to be the best in your subfield. You need to dominate a large and encompassing category to win the prize.

One can see how advice for entering physics might change as one considers what level of success is being sought. If the person has middling or low talent, then level-one success is still clearly achievable with effort. Level-two success might be possible with minor talent, but is more dubious with low talent. Level-three success is basically impossible without high talent, luck and effort.

Optimism or Pessimism? Talent or Effort?

The net outcome of these different types of competition is that your view on the possibility of success will likely flip, depending on which you’re examining.

Level-one competition, which is restricted to a small pool of individuals, and often has the best performers removed because of their limited scope, is an area where most of your competitors may not be trying very hard. You can be more optimistic about success here, relatively speaking, because the barriers to winning the competition are a lot lower.

Similarly, I believe effort, attitude, gumption or any of the other success literature staples is probably quite useful here. Since your competitors may not be setting clear goals, or working very hard, it is often possible to do quite well just by trying harder than most and using a decent, proven strategy.

Level-two competition, which has a much larger scope, but is still limited because there are many different categories and niches one can be the “best” in, is much harder to be successful at. Here, I think effort must be combined with talent or aptitude to be optimistic about success. Success overcoming low natural ability is possible, but it’s no longer the case that you can succeed just by working hard. Your competitors are working hard too, and if they’re naturally better than you, that will only compound their advantage.

In this area of competition, differentiation and specialization is key. You want to quickly find the area you can outperform everyone, and that often means trying lots of stuff until you can find something you can truly be world-class at. This involves both tons of hard practice and testing to find out which skills and assets come easier to you than others. Strengths + deliberate practice = possible, though not guaranteed, success.

Level-three competition is a completely different beast. Here, I’m much more pessimistic about success. Obviously success is possible here, because someone must be the winner. But no longer can you make general statements about everyone being a potential winner. Success here inevitably requires extreme effort and extreme talent.

Similarly, if there are structural advantages that accrue to some people based on certain factors (say where they went to school, access to key mentors or investors) it may be nearly impossible for anyone without those things to succeed here.

Success stories surmounting obstacles to succeed at this scale are less common than ones in which the person had everything going for them and it was still incredibly difficult. If you do read about a case where someone had a high barrier, and overcame it nonetheless, it is more often that their other qualities (talent or effort) were so high as to be outliers. If you are not just more talented than average, but a standard deviation more talented than anyone, then overcoming extreme barriers to success may be in the cards.

First, Know Your Competition

Looking at these competitive ranges, you could either describe me as a self-help optimist—believing in the power of effort, goals and sound methods to be the ultimate determiner of success—or you could see me as an unabashed cynic—believing that there’s no possibility of success without extreme talent and luck.

However, I think if you analyze the type of competition you’re facing, it’s easier to see how the situation can look very different for different people.

This reversal of fortunes and the level of competition changes, is also one of the reason I get frustrated with book titles like Talent is Overrated or ones that focus on genius or inherited advantage to determine success. My feeling is that much of the conversation around these ideas neglects the essential competitive dimensions, and therefore misses the most crucial aspect in deciding whether something depends highly on fixed talents or not.

I think being able to think about the kind of competition you’re facing is a much more powerful mental model than dividing success into “effort/experience” and “talent/privilege.”

Don’t Like the Competition? Change It

For one, you can often change the type of competition you face. For many businesses, starting out in consulting is a softer move than trying to go immediately into products, since the former is level-one competition and the latter is level-two. Alternatively, you may aim for uniqueness (level-two competition) rather than try to be the best in the world (level three).

It goes without saying that competition is just one variable that explains different degrees of success, but it isn’t the only one. Some level-one arenas are still notoriously hard (such as running a local restaurant) and some level-two domains have enough niches to sustain quite a few people in the “top” (such as blogging). As such, it’s always possible that a level-one domain is actually harder than a level-two, or that a level-two is harder than a level-three domain.

However, the level of competition should still provide a useful lens for estimating requirements for success. It is also more accurate within-domains than between-domains. Opening a successful restaurant chain (level-two) is harder than running a successful restaurant (level-one) even if running a successful restaurant is harder than a level-two goal in a completely different field.

Since success is often defined relatively, either directly or implicitly, understanding the type of competition you’re facing is a stronger predictor of the requirements of success than almost anything else.

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Are Successful People Just Putting in More Effort? Mon, 27 Nov 2017 23:09:08 +0000 As someone who writes advice for a living, I’m always interested in the ways advice works, how it gets distorted and what the typical advice-receiver can do about it.

Recently, I came across some research that suggests a new way advice-givers aren’t being totally honest with you: paternalistic advice bias.

Here’s the abstract, from the journal article:

“Despite the near universality of the maxim that one should treat others as one ought to be treated, even well-intended advisers often advise others to act differently than they choose for themselves. We review several psychological factors that contribute to biased advice. Absent pecuniary motives to the contrary, advice tends to be paternalistically biased in favor of caution. Policies that would intuitively promote quality advice — such as making advisers accountable, taking advice from advisers who value the relationship, or having advisers disclose potential conflicts of interest — can perversely lower the quality of advice.”

Biased Advice Leads to Excess Caution

The idea here makes intuitive sense. An advice-giver, whether its someone giving advice in the form of a blog article, or a friend or mentor suggesting a course of action, is not merely transmitting what they know from their own experience.

Instead, there’s a subtle cost-benefit calculation that has to be done when giving advice. And here, there’s a big problem: the flaw of bad advice. If you give someone advice that ends up going disastrously wrong, you might get blamed for that. And the blame, reputationally speaking, might be worse than the benefit of helping you win big.

To use a purely hypothetical example, imagine you have to ask a trusted friend for advice about quitting your job to start a business. Suppose this person knows, privately, that there’s a 30% chance you’ll be a big success and 10% chance you’ll lose quite a bit of money, with the remaining 60% of the time the change is relatively neutral.

Now, if this trusted friend were doing the calculation themselves, they might value a 30% chance of big success more than a 10% chance of a financial blunder. So, privately, that person might go ahead with it anyways.

However, as an advice-giver, they may recognize that in the chance you’re successful you might only thank them mildly for encouragement, a small benefit, but if they go bankrupt they may blame you for goading them on, causing deep resentment or worse. As such, you may advise caution if this person is really on the fence about the decision.

Is There an Anti-Effort Bias in Some Advice?

This finding about advice was risk-aversion, but I can see how it could possibly extend to effort-aversion as well. If the effort itself forms a type of risk, you might caution a middle-route of reasonable effort as opposed to the high-intensity path you might personally take.

I may be over-generalizing the findings here, but this also makes intuitive sense to me. Expending a lot of effort is itself a kind of cost. Just as I could imagine being cautious advising someone to invest hundreds of thousands of dollars in an uncertain investment, I might also imagine being cautious telling someone to invest thousands of hours of effort in a project which isn’t guaranteed to work out.

This suggests to me the possibility that increased effort may be dissuaded against if it constitutes a greater risk.

Alternatively, if effort mostly guarantees success, then more effort would reduce risk and be (perhaps) overly recommended. How this affects advice might depend on the reliability of results after effort. People may recommend working hard at a new exercise plan to get in shape, which is a low-risk move, but not recommend working hard at becoming an actor or actress, which is high-risk.

Anti-Effort Posturing

It’s not related to the study mentioned earlier, but another plausible way advice can seem to reduce the emphasis on effort is when the person who is successful has an incentive to downplay their own effort invested.

This bias doesn’t seem to be one-sided. I think we can all think of situations where people have exaggerated the contribution of their personal efforts (such as the son of a U.S. president boldly claiming to be a self-made man). Others are humble and dismiss the idea that their (very obvious) hard work had anything to do with their successes.

Most people tend to attribute this bias to personality. Some people are braggarts who like to champion their hard work and effort, when they really don’t deserve the credit. Some people are modest and gracious and would rather have circumstances or other people get the acclaim.

While personality may be a factor, I prefer to see it another way. People try to maximize their appearance. Sometimes, claiming to have invested a lot of effort makes sense, especially if it can distract from less praiseworthy causal factors in success such as connections, wealth or inheritance.

However, sometimes claiming to have invested a lot of effort makes you look worse. You would appear more magnanimous by suggesting luck and feigning humility. In some endeavors, suggesting raw talent or intelligence is seen more highly than investing a lot of effort. Presumably the latter implies you made different choices, and therefore have different values, which can sometimes be a source of distrust or resentment itself.

My own experience has shown that in my personal life (less so professionally) there’s a strong social incentive to downplay effort. Being busy and overworked is okay (that’s circumstances), but one must be more careful advertising a self-inflicted ambition that requires immense effort (that’s different values).

Many people I’ve talked to who have succeeded at ambitious projects speak similarly, saying that, while working on such projects, they’re often given a rather uncomfortable reception from people who don’t exactly look up to their intense efforts. It seems weird, forced or unnatural, and they often politely question why this person would bother putting so much effort in.

What This Means for Advice

This all suggests to me, at least, that there’s a large possibility of a fairly invisible layer of people around you putting in a lot more effort than is deemed socially reasonable for the pursuit they are after, and often succeeding at it too.

Advice, especially when passed from person-to-person, may be overly risk-adverse, and encourage low-effort strategies for pursuits where success is uncertain.

The combination of these effects, if one doesn’t see through it, can be to fatally underestimate the intensity and effort successful people invest in their goals which inevitably leads to them doing well.

Ultimately, I think the magnitude of this effect will depend on how big a role these underlying factors play. More certain goals will probably show less anti-effort bias. Goals which are more conventionally appropriate to show extreme ambition in (athletics, academics in many settings, high-effort/high-status career paths such as medicine, etc.) will likely show less of this bias. In these cases, the bias might even reverse with successful people actually working *less* hard than you think.

However weird, risky goals like starting a new business, ultralearning projects and high-variance career paths, might have enough of the opposite bias that success for many people is inhibited simply because they don’t realize how hard successful people are actually working at those goals.

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How Much Can You Possibly Learn? Wed, 15 Nov 2017 17:59:51 +0000 How much can the brain store?

We all know how much our computers and phones can store, if only because we occasionally get the pings of messages telling us we’ve taken too many photos or downloaded too many apps or movies and something has to be deleted to store more.

The brain doesn’t seem to be like this. While we do forget things, this seems to be more a matter of decay from disuse than being actively “pushed out” by new knowledge.

On the other hand, the brain is still subject to the same laws of the universe that govern everything else. It can’t possibly store infinite amounts of data, as that would be physically impossible.

So how much can you actually learn?

Some Upper-Bounds on Memory

A good first attack on this kind of problem would be to look at the potential upper bounds of human memory, based on the laws of physics. These will be wildly too high, mostly because the brain is a living organism and not an idealized information storage medium, but they should give some starting points for thinking about it.

The brain is typically 350-450 cubic centimeters. The maximum possible information you can cram into a volume that size is defined by the Bousso bound, which ends up calculating to roughly 10^70 bits of information. However, in order to get this amount of information, your brain would become a black hole… so let’s try to reduce this bound further.

If we look, somewhat more modestly at the amount of information content possible in a volume of water at room temperature equivalent to the brain, we end up with a somewhat more modest 10^25 bits of information. This is one yottabyte of data or 7-8 orders of magnitude more data than the entire Internet.

This, of course is still way too high, since most of the matter in the brain isn’t encoding data but keeping the brain alive and functioning.

We’re still a long way from understanding the exact information carrying capacity of the neurons and synapses in the brain. As such, an estimate of brain information capacity has to use a simplified approximation of how much information these connections can possibly store.

If we ballpark the amount of data that can be stored in the brain as roughly the same order of magnitude as the amount of synapses in the brain, that leaves us with 100 trillion bits or ten terabytes of data—similar to the size of a large hard drive. Even if we imagine that synapses are storing more than one byte of data each (through multiple connections or non-binary connection strengths), we might be able to bump that up to a petabyte, but probably not much more.

By this look, the brain definitely can’t be storing more than a yottabyte of data, and it’s quite unlikely it’s storing more than a petabyte.

Of course, this is still an upper-bound. We know from people who suffer brain injuries, that the knowledge stored in the brain likely has some measure of redundancy. Those synaptic connections are not exclusively used for storing memories either—many are being used for processing, relaying information or may even be spurious, not doing anything at all. This suggests the memory storage of the brain might indeed be a fair bit smaller, but the certainty of this estimate is a lot less than the harder upper bounds mentioned before.

Why Don’t People Ever “Fill Up” Their Brain’s Capacity?

One explanation for why we don’t seem to run out of space to learn new things is that learning may be a lot slower than our mnemonic capacity. That is to say, the actual learning rate of information may be slow enough that we never reach that capacity.

Here’s an analogy: imagine you have a latest-generation harddrive which can store 10TBs of data, but you have to fill it up using a dial-up connection which only downloads at 3 kilobytes per second. It would take over a decade to fill it up, if you were downloading constantly, without rest, and without removing anything you previously downloaded.

Given that it’s likely only a fraction of our waking type is filling up our mental harddrive, and that we suffer from forgetting, it may simply be that we never experience the upper bound of our mental capacity because we learn too slowly.

However, a different explanation might be that, unlike a computer, we don’t store memories that way. Because we store them differently, when we run out of “space” the impact is different.

Vector Encoding, Learning and Forgetting

One of the most popular accounts for how the brain stores information comes from connectionism. This says that the brain uses vector encoding, which means each memory is distributed over many thousands of individual synapses and neurons, rather than there being a neuron which individually stores each atomic concept or memory.

In this view, there is no “grandmother neuron” which specifically points out a memory of your grandmother, but that memory of your grandmother is stored across many different neurons.

Each neuron may be involved in tens of thousands of memories, each contributing a tiny, but necessary, part to the processing that results in thinking of your grandmother, calculus or recognizing the words in this sentence.

What happens when we learn, therefore, is quite unlike storing a file on a computer, where each memory address exclusively and completely stores one piece of data. Instead, we “pile on” data on top of old data. As more and more memories are stored, older memories may get weaker and weaker, as they become harder to activate, since their contribution to the total network of weights is relatively small.

Intuitively, this seems to jive with our own experience of memory. Unlike a computer which remembers things all-or-nothing, human memory seems to fade, and needs to be refreshed or it will become harder and harder to summon up. It may even still exist in our brains, but become unretrievable, until the exact pattern of triggers can summon it up again.

If this is how our memory fills its capacity, it may be that we encounter the limits of our brain’s storage ability all the time.

What Kind of Memories Get Overwritten?

One idea here is also that the memory fading process, where accumulated new memories make older memories harder to find, may depend on the kind of information learned. Information that must be finely discriminated from similar, but different, possibilities, might require more storage than memories which are easy to tell apart.

This might explain the effect of interference on learning new languages. If you learn Spanish, and then learn Portuguese, for instance, you may have difficulty recalling Spanish words when they’re different from Portuguese. Because the languages are quite similar, but sometimes vocabulary is different, you may have difficulty remembering.

A more extreme example of this comes from mnemonics. People who train themselves to memorize vast swaths of information with techniques like the memory palace, have to be careful not to reuse the same areas for mapping information for two sets of things they want to retain in memory. Without care, the connections can get mixed up and old memories may become unretrievable.

By this account, you should be more careful when learning information which is quite similar to something you already know, but has distinct differences in use (say similar languages), rather than fields which are either completely different (chemistry and art history) or complementary (physics and math).

My own experience from learning multiple languages suggests that, if you want to go down that route, you often need to invest time switching between the languages, so the cues for distinguishing vocabulary get reinforced and they don’t mix together.

Should You Worry About Running Out of Space?

Probably not. Even if the brain does have a more limited capacity than an ideal physical medium for storage, and even if we occasionally run into the limits of memory from ideas and concepts that get pushed down, my sense is that running out of memory isn’t a concern for almost anyone.

One reason might be that memory decay happens naturally, interference or not. This might mean that trying to “save” space in your mind, by avoiding learning unnecessary things, may not stop forgetting any less than learning constantly.

Another reason is that many memories are supportive of each other. Learning one thing often connects to another thing. If retrieval, not storage, is the major flaw in our memory hardware, then overinvesting in memory cues more than makes up for trying to save extra space.

For extremely memory-intensive subjects or tasks, it may be possible to reach a saturation point, where new memories can only be created at the expense of old ones. I could imagine, for instance, that there’s an upper bound on how many languages one can learn to mastery, since each may require remembering hundreds of thousands of pieces of linguistic information.

However, it may be that those bounds are reached because natural decay processes, and thus the need to practice previously learned information in order to keep it active, eventually overwhelmns the ability to learn new things. This way, your memory capacity would be hit, not because you suddenly run out of space one day, but because maintaining everything else you’ve learned requires 100% of your time.

If this is the case, though, it is likely far greater than what most of us will ever experience. Polyglots like Alexander Arguelles have proficiency in 50+ languages, albeit through lifelong devotion. If there is a threshold for theoretically-maximal linguistic fluency, it might be well over a hundred, given that Arguelles is still a human being and needs to eat, sleep and do things other than learn languages.

We also can’t discount the possibility of the brain itself to expand its capacity under the pressure to learn more things. London taxicab drivers, who must memorize the city’s infamously complex road system, sights and stops, have larger hippocampuses (a part of the brain involved in forming long-term memories). What’s more, this seems to be caused by their intensive study, rather than being the result of those with larger hippocampuses becoming taxi drivers.

Albert Einstein’s brain supposedly had larger sections related to spatial reasoning and visualization. That could have been a genetic endowment, but it’s also possible it was an outcome of years of strenous thought experiments trying to imagine the warps and curvatures in spacetime. If the learning capacity of the brain is itself plastic, this provides extra weight on the idea that one shouldn’t “save” brain capacity for other things.

As a practical issue, it’s probably unlikely that the storage limits of the human brain should be a concern for everyday learning. However, by understanding how your memory works better, you maximize what you’re able to learn.

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Is Reading Blogs Like This One Keeping You From Improving Your Life? Wed, 08 Nov 2017 00:32:19 +0000 One idea I’ve been pondering over lately is to what extent reading about self-improvement is a complement versus a substitute for taking self-improvement action.

Complements and substitutes are terms that come from economics. A complement to a product is something you buy more of when you buy the product. Think popcorn and movies. The more movies you go to, the more likely you are to buy popcorn (at least here in North America). Wine and fine dining. Cars and gasoline. These are all complements.

The standard view of self-improvement writing, whether it’s fitness books, cookbooks, business books or popular psychology is that it should assist with personal development. That is to say, the more books you read, the more likely you are to actually work on improving yourself.

The alternative view, of course, is that reading isn’t a complement but a substitute.

Substitutes, again from economics, are products that compete with each other. When you go to the movie theater, each movie acts as a partial substitute of the others. If you go to see one, you forego the other. Similarly, Italian wines and French wines are substitutes, as is gasoline from different gas stations.

Here the theory is that what we really want out of personal development, both in active efforts and passive consumption, is that good feeling that we’re doing something to improve our situation. It’s an anxiety-reducing effect that the challenges we’re facing are somehow being dealt with, even if they aren’t being resolved immediately. Since both reading and doing something alleviate this tension, they are substitutes, and consuming one will decrease consumption of the other.

Which Dominates: The Substitute or Complement?

My own feeling is that both of these effects exist, and which dominates won’t be a universal consideration but will depend on a lot of factors.

One factor probably has to do with the material itself. Some types of self-improvement probably work as substitutes. They provide a large emotional payoff (and, thus, work well in anxiety-reduction), but they may be weak on substantial follow-up. Being weak on the latter, they don’t make good complements.

Another factor, however, is probably the nature of the self-improvement task itself. Some types of self-improvement work are probably particularly difficult, emotionally unrewarding and complicated. Because the anxiety-reduction from working in those areas is so hard to come by, it might be easier to seek it from consuming self-improvement material passively instead.

While I’d like to think I avoid the worst of the self-help vapidness of the former, I admit that many of the self-improvement problems I focus on here are exactly the kind of nebulous, hard-to-work-on, abstract categories that may encourage substitution.

As an example, compare what I write to a cookbook. The latter has a quite straightforward application, and therefore is more likely to serve as a complement to actual cooking. Of course it’s not a pure effect—some people buy cookbooks to alleviate the anxiety that they don’t cook enough, or need to learn to cook, and then don’t actually use them. But I imagine this is not the majority.

On the other hand, consider improving your ability to learn effectively, combat procrastination or improve your career. These are all hard pursuits that, even when you’re doing them right, have mixed emotional payoffs in the short-term. As such, I can imagine people consuming self-improvement material here as a way to get that emotional payoff more reliably than doing the actual work.

Note: Let me be clear that I don’t think anyone is actually conscious of this distinction, even if they abuse it. What probably happens, psychologically, is that there’s a desire to improve something, or more accurately, a desire to feel like things are going to be improved. When this desire is strong enough, it can trigger motivation to do something about it. Sometimes that manifests as taking action. Sometimes that manifests as buying a book that you tell yourself you’ll use, but never do.

The Problem with Substitution

I had a conversation with a friend of mine who is doing her doctorate in clinical psychology. I mentioned another friend of ours who was having some anxiety and who I was trying to offer encouragement.

To my surprise, she told me that this was likely harmful in the long-run. The best treatment doesn’t get patients to reduce their anxiety by consoling them, but by confronting that anxiety, which will increase it in the short-run, but has the long-term effect of reducing the intensity of anxiety the next time it comes up.

The problem here was, again, one of substitution. By offering consolation, you are escaping from your anxiety. It provides short-term relief, but it only reinforces the pattern that created the anxiety in the first place.

This is the problem with the substitution effect in self-improvement. If you are using reading a blog like this, buying books or doing “research” as a way of reducing the tension you feel that something needs to be improved, that can be potentially harmful. Without doing something and solving the underlying issue, consuming more information is counterproductive.

When to Decide If You Need a Break?

I’ve experienced self-improvement both as complements and as substitutes in my own life.

The key difference, it seems to me, is a question about how much effort are you expending to actively work on the areas you’re reading about. If the answer is low or zero, and it has been for some time, but the amount of time you’re spending consuming information is significant, you may be having some kind of substitution effect.

I’ve had success in cutting down my consumption. That tends to increase angst about whatever issue you wanted to use the material to solve, momentarily, but that same energy can hopefully be redirected towards taking some action.

Similarly, I’ve had times when I’ve been engaged in a lot of action and really benefited from having complementary material guide me through. Unfortunately, this isn’t an area I can give an easy prescription to read less or read more. Both might be useful! Instead, you need to look more closely at yourself–what are you using the time you spend reading books and blogs on. Is it a substitute for real action or a complement to it. Only you can decide.

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