“Premature Optimization” and the Pandora Box of Debates that Followed

All Evil Started with a Quote on All Evil

Donald E. Knuth, professor of computer science at Stanford University, popularized this phrase used in the programming community: “Premature optimization is the root of all evil.” Little did he know, however, this statement about “all evil” opened a Pandora’s Box – fierce / passionate / headbanging / crazy debates all the way from optimization to the meaning of engineering.

“Programmers waste enormous amounts of time thinking about, or worrying about, the speed of noncritical parts of their programs, and these attempts at efficiency actually have a strong negative impact when debugging and maintenance are considered.”

“We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil.“

“Yet we should not pass up our opportunities in that critical 3%. A good programmer will not be lulled into complacency by such reasoning, he will be wise to look carefully at the critical code; but only after that code has been identified.”

Donald Knuth, “Structured Programming with go to Statements” (1974)

Warning: you are about to peek inside the Pandora’s Box…which may lead to either an insightful soul-searching journey or a mental hurricane or somewhere in between.

Still with me? Then let’s dive in! 🙂

Premature Optimization vs. Technical Debt

A (somewhat) relevant concept to premature optimization is technical debt. Although most in the software engineering world would agree on the definitions of either term, folks are less aligned when it comes to how these two terms relate to each other – are they synonyms or opposites?

Technical debt refers to the “cost of additional rework caused by choosing an easy solution now instead of using a better approach that would take longer. (Wikipedia)” In layman terms, technical debt means if you are lazy now, you will have to make up for it later. Just like if you stock up dirty laundry, you will have to clean them sooner or later. And sooner is better than later better than never – that’s what people really mean when they remind you to “avoid technical debt“.

“Technical debt” as a phrase is looked upon favorably by programmers who believe chivalry isn’t dead. For them, “please avoid technical debt” is a civil alternative to “stop being lazy and get the $%@!#$$# up and do something.” So you could say “technical debt” existed in peace and had its supporters until it was put next to the “premature optimization,” and things get interesting.

This post asks the interesting question of whether premature optimization is “the opposite concept of technical debt”? What’s more interesting than the question itself are the comments that followed – highly recommend a read.

Some believe that “premature optimization” is generally a worse offense than “technical debt”, because at least technical debt saves you time now (although you need to pay back later), and the argument is that technical debt wastes less time than premature optimization on a net basis:

“There is no optimization included in this concept (of premature optimization). Optimization is doing something to improve value delivery. Eliminating waste is one form of optimization. This premature “optimization” introduces waste now (time is spent while not adding value). And if that isn’t bad enough, it introduces future waste as well.“

“To me it (premature optimization) seems even worse than technical debt. Both (premature optimization and technical debt) result in future waste, but with technical debt you at least don’t waste a whole lot of time now.”

Comment by Henri van der Horst

However, is it really true that premature optimization only wastes time and creates no benefit at all? Randall Hyde argues that premature optimization is not as bad as it sounds – on the contrary, programmers could gain experience and the code as a whole does not suffer a lot:

“One thing nice about optimization is that if you optimize a section of code that doesn’t need it, you’ve not done much damage to the application. Other than possible maintenance issues, all you’ve really lost is some time optimizing code that doesn’t need it. Though it might seem that you’ve lost some valuable time unnecessarily optimizing code, don’t forget that you have gained valuable experience so you are less likely to make that same mistake in a future project.”

“The Fallacy of Premature Optimization”, Randall Hyde

To put it simply, Hyde considers premature optimization to be a “tuition” paid for how-to-code-better. If we go with Hyde’s argument, then the logical implication would be that technical debt is worse than premature optimization – the former teaches you nothing (other than that being lazy in the moment has its consequences down the road – which is something you have chosen to conveniently forget the moment you decide to go lazy and let the technical debt accumulate).

Some say premature optimization and technical debt, instead of being opposite concepts, overlap in meaning:

“You suggest premature optimization as an opposite, but I would say that premature optimization is technical debt. At least in a software context, optimization usually comes at the expense of readability and maintainability of the underlying code. If you didn’t need the optimization to support the use of the system under design, all you accomplished is making the code more difficult to maintain. This difficulty in maintenance is likely to cause new features to take longer to design, develop, test, and deploy, which is a key indicator of technical debt.”

Comment by Thomas Owens

To rephrase, Owens’ comment above argues that premature optimization creates problems that need to be remedied later, and I agree with him on that. What I disagree with, however, is that premature optimization creates “technical debt.” If we use the definition from Wikipedia above, technical debt refers specifically to problems caused by being lazy now (going for an easy solution or not doing anything), instead of being inappropriately / unwisely diligent (i.e., premature optimization). Owens has broadened the definition of “technical debt” in his comment to refer to code with any kind of problems – regardless of whether the cause was laziness (technical debt) or wrongly-guided diligence (premature optimization). And the preceding sentence is a nice way to summarize where I stand on this:

I believe both “premature optimization” and “technical debt” create problematic code that need to be fixed later – the key difference is in the root cause of the problem. Premature optimization is caused by misguided diligence, which creates very low ROI at its best or 0% ROI (100% wasted efforts) at its worst; technical debt is caused by mere laziness. While technical debt reinforces the old lesson that one should not be lazy, premature optimization shows that too much of diligence could be a bad thing.

Writing great code does not mean writing perfect code at every single step, and not every single line is worth investing the same amount of time & energy. Premature optimization is the result of incorrectly optimizing your time – which is of limited supply – and is the cause of failed maximization of the quality of your code output.

That was a mouthful yet just the start on the interesting debates surrounding premature optimization. We then slide further down the slippery slope to talk about the slippery slope itself.

The Premature Slippery Slope and the “Swiss Cheese” Model

Slippery slope means “a relatively small first step leads to a chain of related events culminating in some significant effect. (Wikipedia)” It has been more than four decades since Donald Knuth first popularized “premature optimization” in his 1974 paper – and four decades is a time long enough for his statement to fall down a premature slippery slope. 🙂

Some programmers say they want to avoid “premature optimization” as an excuse for being lazy or thoughtless. In this post, Joe Duffy expresses frustration when programmers use Knuth’s statement “to defend all sorts of choices, ranging from poor architectures, to gratuitous memory allocations, to inappropriate choices of data structures and algorithms…in other words, laziness.” It sounds like “premature optimization is the root of all evil” has been slipped down the slope to “optimization is the root of all evil” to “optimization is evil”.

Check out this humorous yet witty take by Randall Hyde on the various manifestations of the “slippery slope” gone too far: “The Fallacy of Premature Optimization”. My favorite part are the sarcastic observations he makes of programmers – some are a bit exaggerating and obviously don’t apply to every programmer, yet they are food for thought and I find myself guilty of slipping into some errors in non-programming fields:

“Observation #3: Software engineers use the Pareto Principle (also known as the “80/20 rule”) to delay concern about software performance, mistakenly believing that performance problems will be easy to solve at the end of the software development cycle. This belief ignores the fact that the 20 percent of the code that takes 80 percent of the execution time is probably spread throughout the source code and is not easy to surgically modify. Further, the Pareto Principle doesn’t apply that well if the code is not well-written to begin with (i.e., a few bad algorithms, or implementations of those algorithms, in a few locations can completely skew the performance of the system).”

“Observation #4: Many software engineers have come to believe that by the time their application ships CPU performance will have increased to cover any coding sloppiness on their part. While this was true during the 1990s, the phenomenal increases in CPU performance seen during that decade have not been matched during the current decade.”

“Observation #6: Software engineers have been led to believe that their time is more valuable than CPU time; therefore, wasting CPU cycles in order to reduce development time is always a win. They’ve forgotten, however, that the application users’ time is more valuable than their time.“

“The Fallacy of Premature Optimization”, Randall Hyde

The central point that Hyde is trying to get across is that when some programmers claim to be “minimizing premature optimization”, what they are actually doing is “minimizing the time spent on thoughtful design” and, as a consequence, is a betrayal of the engineering ethos to maximize performance. There is no excuse for not investing the time to think through the systematic performance of the system as a whole – this is what expected of any good software developer, per Charles Cook (unfortunately, the link to Cook’s blog article is no longer valid):

“Its usually not worth spending a lot of time micro-optimizing code before it’s obvious where the performance bottlenecks are. But, conversely, when designing software at a system level, performance issues should always be considered from the beginning. A good software developer will do this automatically, having developed a feel for where performance issues will cause problems. An inexperienced developer will not bother, misguidedly believing that a bit of fine tuning at a later stage will fix any problems.”

Charles Cook

Rico Mariani is making a similar point when he says: “Never give up your performance accidentally.“

“Now, it’s time for the simple yet clever rule: Never give up your performance accidentally. That sums it up for me, really. I have used other axioms in the past — rules such as making sure you measure, making sure you understand your application and how it interacts with your system, and making sure you’re giving your customers a “good deal.” Those are all still good notions, but it all comes down to this: Most factors will tend to inexorably erode your performance, and only the greatest vigilance will keep those forces under control.“

“If you fail to be diligent, you can expect all manner of accidents to reduce your system’s performance to mediocre at best, and more likely to something downright unusable. If you fail to use discipline, you can expect to spend hours or days tuning aspects of your system that don’t really need tuning, and you will finally conclude that all such efforts are ‘premature optimizations’ and are indeed ‘the root of all evil.’ You must avoid both of these extremes, and instead walk the straight and narrow between them.“

Rico Martiani (Microsoft, Performance Architect, 2004)

Rico’s principle of “never give up your performance” – whether accidentally or consciously – is applicable to all walks of life, not just programming. It is particularly important when we are dealing with complex systems:

“What are good values for performance work? Well, to start with you need to know a basic truth. Software is in many ways like other complex systems: There’s a tendency toward increasing entropy. It isn’t anyone’s fault; it’s just the statistical reality. There are just so many more messed-up states that the system could be in than there are good states that you’re bound to head for one of the messed-up ones. Making sure that doesn’t happen is what great engineering is all about.“

Rico Martiani (Microsoft, Performance Architect, 2004)

There you go: great engineering is about great performance indeed, but great engineering is not about guaranteeing a perfect performance – in fact, that is downright impossible. Great engineering is about preventing, or minimizing, the chance of resulting in performance that is so messed up that you bring about catastrophic consequences. Great engineering is not about delivering a perfect show 100% of the time – it is about making sure that a messed up sh*t-show happens 0% (or close to 0%) of the time. Therefore, a truly great engineer will steer away from wasteful “premature optimization”, while never forgetting or giving up on the goal of performance optimization. In fact, avoiding premature optimization itself is a tactic to optimize performance by investing time where it matters the most for the output.

On the point about avoiding a sh*t-show from happening, I came across the Swiss cheese model on accidental management, as explained by Matt Parker in his book Humble Pi: When Math Goes Wrong in the Real World:

“[The] Swiss cheese model of disasters, which looks at the whole system, instead of focusing on individual people. The Swiss cheese model looks at how ‘defenses, barriers, and safeguards may be penetrated by an accident trajectory.’ This accident trajectory imagines accidents as similar to a barrage of stones being thrown at a system: only the ones that make it all the way through result in a disaster. Within the system are multiple layers, each with its own defenses and safeguards to slow mistakes. But each layer has holes. They are like slices of Swiss cheese.”

” I love this view of accident management, because if acknowledges that people will inevitably make mistakes a certain percentage of the time. The pragmatic approach is to acknowledge this and build a system robust enough to filter mistakes out before they become disasters. When a disaster occurs, it is a system-wide failure, and it may not be fair to find a single human to take the blame.“

Humble Pi: When Math Goes Wrong in the Real World (Matt Parker)

The Swiss cheese model is very easy to visualize: imagine putting slices of Swiss cheese on top of each other, each slice with holes on them representing problems. Imagine catastrophic events only happen if the holes on each slice happens to line up, and an error could pass through them in a straight line. As Matt Parker points out, when a bunch of mistakes “conveniently” line up and result in a gigantic mistake, it is usually indicative of some systematic issues. This is not to say that individuals or specific actions are not at fault – but one should not focus on the tree and forget about the forest, i.e., the system as a whole. There is often lots to be done on a systematic level, e.g., improved processes or better tools.

Two final remarks:

(1) I am not a programmer and I don’t code myself, so yes, I am commenting on an area of trade that I have little experience of. That being said, just as you don’t have to be a professional mathematician to apply mathematical thinking in your daily life, I believe you don’t have to be a full-time software engineer to appreciate computational thinking. At the end of the day, although concepts like “premature optimization” and “technical debt” originated in the context of software, they could be applied to and maintain relevance in all walks of life;

(2) I highly recommend Matt Parker’s highly entertaining & educational book on mathematics: Humble Pi: When Math Goes Wrong in the Real World. If you love mathematics, there is no reason not to read it. If you hate mathematics, the biggest reason to read it is it will make you fall in love with math. Mathematics is a truly beautiful language and way of thinking.

See you later, world.

“Uncommon Sense” About COVID-19: Data & Opinions Worth Knowing (live updating)

Read-Me-First: Much is being posted about the coronavirus on a daily, or even hourly, basis – sometimes a bit too much with fake news / data / pictures coupled with conspiracy theories, accusations of racism, and doomsday predictions. This blog post – live updated from time to time – aims to filter out the signal amidst the noise: data & opinions on the COVID-19 that (a) I think are worth knowing & reflecting about, and (b) are inevitably colored with my own biases & POV. Do your own research, form your own (informed) opinions, and stay safe!

Table of Contents (updated April 17, 2020)

• [Set the Stage] Other than masks, stop up some humor too
• [Science] Getting familiar with COVID-19 symptoms (vs. cold, flu, allergy)
• [Science] Understanding how fast the virus spreads and incubates
• [Protective Measures] Response of Individuals: Stock-Up vs. Laissez-Faire
• [Protective Measures] Response of Governments: Lock-Down vs. Herd Immunity
• [Thinking Smart] What a conspiracy theory teaches us about critical thinking
• [Thinking Smart] Veterans merely make better guesses – nobody knows for sure
• [Thinking Smart] “Aha” moments from working from home
• [Thinking Smart] Defining information
• [Thinking Smart] What went wrong with media coverage? A failure, but not of prediction

[Set the Stage] Other than masks, stock up some humor too

If you have not yet heard about the “coronavirus disease 2019” (COVID-19) – which is aptly named with a “19” suffix because we were obviously certain it would spread into 2020 and achieve monopoly over this year’s headlines (joking) – you must be living in a cave.

Rest assured, even if that were the case, I would not mock you. On the contrary, I would envy you, because living in a cave like Robinson Crusoe these days is probably one of the safest ways to protect yourself from the coronavirus. 🙂 Moreover, if you were able to get Wi-Fi connection in your cave, you could post on social media with glorious hashtags like #not-lonely-when-am-alone, #perfect-social-distancing, #responsible-self-quarantine etc.,

Just joking (again). We all need some positive energy in times like this. Some wise folk once said: “If you can’t laugh about it, you lose.” I, for one, am a big fan of John Oliver’s funny, sarcastic & witty take at the recent coronavirus news on “Last Week Tonight” (HBO, March 1, 2020):

Let’s not forget to keep some happy smiley faces up even when COVID-19 was called a pandemic by the WHO and the stock market + oil market + crypto market + [insert your past-favorite / now-most-hated market] are trapped by NOVGRA-20, a shorthand for “novel gravitational force 2020”. Can the Einstein-of-our-times come up with a new theory of relativity to explain what the h*** is going on?

Since searching for the next Einstein-of-our-times is too challenging, I opted for an easier option – searching on Google about what is interesting to know about the COVID-19. Here is your curated feed on “uncommon sense” about the coronavirus: not-your-typical headlines, yet probably worthy of attention.

[Science] Getting familiar with COVID-19 symptoms (vs. cold, flu, allergy)

To start with, let us first familiarize ourselves with what the virus does. As Peter Attia, MD with training in immunology, said in a podcast, the coronavirus mainly attacks the type II pneumocyte cell that makes surfactin. Surfactin lets the air sacs of the lungs to overcome the tension on the surface and hence open successfully. In other words, without sufficient surfactin, individuals could suffer from respiratory collapse. Dr. Attia recommends all infected persons with difficulty breathing to seek medical attention ASAP – regardless of their age.

COVID-19 could be tricky to diagnose because of overlapping symptoms with the cold, the flu and allergies. This article from Business Insider (March 2020) gives a good comparison of the symptoms across the 4 diseases.The key point is the three most common symptoms of COVID-19 are: fever + dry cough + shortness of breath.

The good news is: if you are sneezing and have a runny nose, it is very unlikely that you have COVID-19 – the flu or allergies are probably to blame.

The important footnote is: while nausea and diarrhea are rare for COVID-19, these symptoms could still be “early cues of infection (of COVID-19)” and thus should not be taken lightheartedly.

[Science] Understanding how fast the virus spreads and incubates

When it comes to studying the spread of the virus, a key concept to know is the viral coefficient, denoted by “R”. “R” stands for the number of people that each infected person goes on to infect. You may have also heard about R0, which stands for the viral coefficient in a community with no natural immunity against the virus and takes no special protective measures. Getting a fair estimate of R (and R0) could help us assess how viral the virus is and how effective interventions are:

“In the long term, the only way that this pandemic can actually end is for the R value of the virus to plunge below 1, consistently, in every part of the world, for a prolonged period of time.”

“A framework for thinking through what’s next for COVID-19”
(March 11, 2020)

I recommend reading “An in-depth look at four academic models of the Wuhan coronavirus outbreak’s spread” (January, 2020) for a concise summary of what scientists say (or infer) about the spread of the virus. The key takeaway on the virality factor is this:

“[T]here is still not an academic consensus on the basic replication number of the Wuhan coronavirus. Models range from finding an Ro of 1.4 after assuming a latent period of 14 days, to finding one of 4.0 after assuming only 4 days.“

“An in-depth look at four academic models of the Wuhan coronavirus outbreak’s spread”
(January, 2020)

Next, let us look at the incubation period of the coronavirus. In this March, 2020 study led by Johns Hopkins University, the researchers find the median incubation period is around 5 days:

“There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10,000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine.”

The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application
(March 10, 2020)

The Johns Hopkins research suggests that 14 days is a reasonable length for quarantine – cases that have longer incubation periods are possible yet unlikely outliers:

“Based on our analysis of publicly available data, the current recommendation of 14 days for active monitoring or quarantine is reasonable, although with that period, some cases would be missed over the long-term.”

5.1 days incubation period for COVID-19
(March 9, 2020)

Despite progress in understanding the viral coefficient (R) and the length of the incubation period, we are still not sure about when someone is contagious – in particular whether a person is contagious during the incubation period. The website of the US Center for Disease Control (accessed on March 16, 2020) reads: “[D]etection of viral RNA does not necessarily mean that infectious virus is present…it is not yet known what role asymptomatic infection plays in transmission. Similarly, the role of pre-symptomatic transmission (infection detection during the incubation period prior to illness onset) is unknown.“

That being said, Bill Hanage, an associate professor of epidemiology from Harvard, believes the answer “is an unambiguous yes” when it comes to “a person can transmit before they are aware they might be infectious.” Though please do note Hanage’s statement is yet to be backed with peer-reviewed research.

[Protective Measures] Response of Individuals: Stock-Up vs. Laissez-Faire

On the question of how to respond to the COVID-19 outbreak, the responses fall on two-ends of the spectrum (for individuals): go full force or do (almost) nothing. We see a juxtaposition of two contrasting camps: (1) Camp-Stock-Up rushing to supermarkets and stocking up on years of toilet paper vs. (2) Camp-Laissez-Faire wandering the streets without masks – assuming they have or are able to get masks – either a/ thinking optimistically that the COVID-19 is not that dangerous and everyone is making a fuss or b/ thinking pessimistically that all prevention measures are useless because they would get infected sooner or later.

Where should we pick our stance between the two extremes? Below is a stance that I find to be reasonable, which thinks about social distancing the way we think about car safety: “not as a single binary decision to go Full Turtle and shelter in place, but as a collection of little risk-reducing behaviors that add up to a big win“:

“To really get your mind around how this works, think about all the little things you do to manage risk when driving a car: wear a seat-belt, use a turn signal, drive the speed limit, don’t drink or text and drive, have your brakes checked regularly, etc. Each of these things helps a little, and when done together they all add up to a dramatically safer driving experience — both for you and those you share the road with — than if you didn’t do any of them at all.”

Even if you can’t go full lockdown right now, you can still #FlattenTheCurve
(March 13, 2020)

Another key point this author points out is “every new day is riskier than the previous one” – at least in the short term – as the number of infections increases and we are not yet fully equipped with dealing with the disease. What this entails is it makes sense for each individual to progressively level-up their self-protection every single day, at least until (a) we see reliable signs that the spread of the virus has been contained and / or (b) we have developed a solid cure and / or vaccine.

Most of us are probably working from home, but for those who are working in the office or in public places, consider this piece of advice:

“Take on progressively more social and reputational risk in order to reduce your physical risk: e.g., If you’re working a retail counter tomorrow and an obviously ill customer approaches you, discretely excuse yourself for the restroom at the risk of having that person try to get you fired. You might want to start using sick days next week. Get bold and creative with how to distance yourself in-the-moment, and be more willing to offend people as this progresses.”

Even if you can’t go full lockdown right now, you can still #FlattenTheCurve
(March 13, 2020)

“Be more willing to offend people.” If you are working in the office and a colleague is coughing, ask him / her to work from home or see a doctor. Do not be afraid to offend your colleague, because it is a responsible thing to do for both you and your colleague and everyone else in the office. Plus, if you were asking in a nice way and explain your rationale, most people in your colleague’s shoes should be able to understand.

[Protective Measures] Response of Governments: Lock-Down vs. Herd Immunity

The response of governments around the world could be broadly put into 2 types:

1. Camp Eradicate: represented by China, this group takes a resolute stance including city-wide lock-downs and quarantine at the cost of disrupting economic activities;
2. Camp Herd Immunity: represented by the UK (which has since then modified its stance to be more hard-line) is to focus on “flattening the curve,” i.e., focus on protecting the more vulnerable people. Instead of trying to eradicate the virus, this camp would try to slow down the spread of the disease a bit so as to “flatten the curve,” i.e., a slower spread of the disease could prevent over-burdening the healthcare system.

Scott Adams asks an interesting question about whether these two camps could co-exist in harmony. As long as Camp #2 Herd Immunity exists, does this mean Camp #1 Eradicate cannot possibly exist or sustain its success?

China seems to be trying to eradicate the virus. The US is trying to "flatten the curve" and protect the weak until herd immunity happens. As long as we follow our strategy, their strategy is doomed. Am I wrong? #WuhanVirus #coronavirus

— Scott Adams (@ScottAdamsSays) March 14, 2020

The UK’s proposal of “herd immunity” has been under criticism:

For me, herd immunity has never been the outright aim, it’s been a tragic consequence of having a virus that – based on current evidence – is unlikely to be fully controllable in long term in the UK. 2/

— Adam Kucharski (@AdamJKucharski) March 14, 2020

Some argue that “herd immunity” is a by-product of preventive measures, and should not be mistaken as an end in itself:

“[T]alk of ‘herd immunity as the aim’ is totally wide of the mark. Having large numbers infected isn’t the aim here, even if it may be the outcome. A lot of modellers around the world are working flat out to find best way to minimise impact on population and healthcare. A side effect may end up being herd immunity, but this is merely a consequence of a very tough option – albeit one that may help prevent another outbreak.”

Adam Kucharski, London School of Hygiene and Tropical Medicine

[Thinking Smart] What a conspiracy theory teaches us about critical thinking

A Reddit post from February 2020 went viral with the title: “Quadratic Coronavirus Epidemic Growth Model seems like the best fit” – it posits that the total case numbers reported by China fits “uncannily” well with a quadratic curve (15 days’ of data, R-squared value of .9995). Given none of the current epidemiological models supports a quadratic growth curve, the Reddit post makes a not-so-subtle hint that the Chinese numbers may be fabricated to fit a quadratic curve.

And the situation quickly gets dramatic, and like all (good) dramas do, the situation quickly gets messy with people pointing their fingers at the Chinese government and / or the WHO for allegedly making up and / or covering up the number of total cases in China.

Before anyone gets excited thus far, let us take a look at both sides of the debate. Ben Hunt from Epsilon Theory – one of my frequently-read and highly-recommended blogs on “the narratives that drive markets, investing, voting and elections” – sides with the Reddit skeptic:

“All epidemics – before they are brought under control – take the form of a green line, an exponential function of some sort. It is impossible for them to take the form of a blue line, a quadratic or even cubic function of some sort. This is what the R-0 metric of basic reproduction rate means, and if – as the WHO has been telling us from the outset – the nCov2019 R-0 is >2, then the propagation rate must be described by a pretty steep exponential curve. As the kids would say, it’s just math.”

“[T]o be clear, at some point the original exponential spread of a disease becomes ‘sub-exponential’ as containment and treatment measures kick in. But I’ll say this … it’s pretty suspicious that a quadratic expression fits the reported data so very, very closely. In fact, I simply can’t imagine any real-world exponentially-propagating virus combined with real-world containment and treatment regimes that would fit a simple quadratic expression so beautifully.”

Ben Hunt, “Body Count”
(February 10, 2020)

On the same day when Ben Hunt published his article, there is an Op-Ed published defending the validity of the case numbers, with a title that sums up the author’s stance: “No, 2019-nCoV case numbers were not fabricated to fit a curve”. It points out a few loopholes with the skeptics’ conspiracy theory:

1. Add a few more days of data to the original data-set (of 15 days) and what we get “is far from being a perfect quadratic”;
   
2. “If you look at the data from outside China, which is definitely not being faked by China, and fit a quadratic to cumulative case numbers, you’ll get a similarly eye-catching R-squared value of .992.”
   
3. Fitting data into a quadratic function is easier than it may sound: “Any data whatsoever with n points can be fit perfectly, with absolutely no error, using a polynomial of degree n-1.”

The author goes on to say we should pay attention to the fact that “modern statistical software can fit many types of models to the same data,” and therefore we should be extra-cautious with what conclusions we draw – especially when the data has a small sample size:

“[A]s our Redditor friend acknowledges, he tried many models before choosing the one with the most eye-catching R-squared value.”

“And the curve of a growing epidemic has some properties that inherently can make it kind of similar to a quadratic. It will be monotonically upward, and growing at an increasing rate. This means the regression calculation’s job is made easier by this crude similarity, and allows those eye-catching R-squared numbers. The R-squared value is calculated using the square of the differences between the model and reality, so it punishes a few large deviations more harshly than many small ones. That is, the joint information of the two curves being high is really just the observation that in general the curves look pretty similar, not a clinching judgment that the curve was faked using a model.”

“No, 2019-nCoV case numbers were not fabricated to fit a curve”
(February 10, 2020)

The author concludes with this stance: “We’re not saying the data is reliable, just that it’s not faked,” citing “even if every single authority in the world were the most competent they could possibly be and were reporting everything they knew with complete candor, the data would still not be accurate, because many cases are latent with no symptoms, and even among symptomatic cases, most are not known to public health authorities.” In short, it is impossible to have “accurate” (and timely) data when it comes the total number of cases – just as it is impossible to have “perfect” testing that covers every single case in real time.

The purpose of me sharing the above is not to tell you which side you should pick – to be honest, I think the real question here is not who to side with, but how to analyze data (& inferences, opinions) critically. To help us remember how easy it is to misinterpret data – whether intentionally or by accident – I would like to show you this graph where a quadratic curve and an exponential curve look very similar within a small range of data:

Here is an explanation of the graph above:

“We generated two curves, one exponential and one quadratic, that both start at 100 on day 1 and end at 1440 or so on day 29. We then fit a quadratic to the exponential, and vice versa. These data really are synthetic and perfect, and we’re fitting the wrong model to each one. But in both cases, the fit is close and the R-squared value is .97 when we fit the exponential to the quadratic, and .994 when we fit the quadratic to the exponential.“

“You can see that both fitted models start to fail at the end, as the exponential data grows faster than the quadratic model will allow, and vice versa.”

“No, 2019-nCoV case numbers were not fabricated to fit a curve”
(February 10, 2020)

It may be a good time to remind everyone of Cowen’s first law from Tyler Cowen, professor of economics: “There is something wrong with everything (by which I mean there are few decisive or knockdown articles or arguments, and furthermore until you have found the major flaws in an argument, you do not understand it).” I would say that is a good attitude to adopt when we read anything, what do you say? And that is a trick question – because if you agree with me, then it implies you think there is nothing wrong with my statement, but that is self-defeating of Cowen’s First Law; if you disagree with me, then it implies you think there is something wrong, which is an example that fits Cowen’s First Law.

Okay – I am just having fun with logic games. 🙂 The point is: do your own research, do your own research on the pro vs. against, and do your own research from every possible angle. Everyone could be wrong. Everyone must be wrong in some way – the only difference is whether you spot where they are wrong or not.

[Thinking Smart] Veterans merely make better guesses – nobody knows for sure

Howard Marks is the co-founder of Oaktree Capital Management, one of the largest investors in distressed securities. He publishes memos on his views on the market, investing, current affairs and other topics. In his latest memo “Nobody Knows II”, which I think is worth a 10-minute read from start to end, Howard shared his take on the coronavirus and the recent market downturn.

Howard breaks down information about the virus into 3 types:

“As Harvard epidemiologist Marc Lipsitch said on a podcast on the subject, there are (a) facts, (b) informed extrapolations [inferences] from analogies to other viruses and (c) opinion or speculation. The scientists are trying to make informed inferences. Thus far, I don’t think there’s enough data regarding the coronavirus to enable them to turn those inferences into facts. And anything a non-scientist says is highly likely to be a guess.“

Memo from Howard Marks: Nobody Knows II
(March 3, 2020)

In Howard’s previous memo called “You Bet” (January, 2020), he shared some quotes by Annie Duke, a PhD dropout who later became what Howard calls “the best-known female professional poker player” with over $4 million winnings from tournaments:

“[W]orld-class poker players taught me to understand what a bet really is: a decision about an uncertain future…[T]here are exactly two things that determine how our lives turn out: the quality of our decisions and luck. Learning to recognize the difference between the two is what thinking in bets is all about.”

“[W]inning and losing are only loose signals of decision quality. You can win lucky hands and lose unlucky ones…What makes a decision great is not that it has a great outcome. A great decision is the result of a good process, and that process must include an attempt to accurately represent our own state of knowledge. That state of knowledge, in turn, is some variation of ‘I’m not sure.’…What good poker players and good decision-makers have in common is their comfort with the world being an uncertain and unpredictable place…instead of focusing on being sure, they try to figure out how unsure they are, making their best guess at the chances that different outcomes will occur.”

“[W]e can make the best possible decisions and still not get the result we want. Improving decision quality is about increasing our chances of good outcomes, not guaranteeing them.“

Annie Duke, “Thinking in Bets: Making Smarter Decisions When You Don’t Have All the Facts”
(February, 2018)

Nowadays with (almost) everyone being called (or calling themselves) an “expert” and giving their (solicited and unsolicited) opinions on the Internet, let’s take a step back to ask ourselves what it means to be an expert:

“An expert in any field will have an advantage over a rookie. But neither the veteran nor the rookie can be sure what the next flip will look like. The veteran will just have a better guess.“

Annie Duke, “Thinking in Bets: Making Smarter Decisions When You Don’t Have All the Facts”
(February, 2018)

I applaud this tweet of Francois Balloux, a computational / system biologist working on infectious diseases. In sharing his opinion of the virus, he candidly admits: “Predictions from any model are only as good as the data that parametrised it. There are two major unknowns at this stage. (1) We don’t know to what extent covid-19 transmission will be seasonal. (2) We don’t know if covid-19 infection induces long-lasting immunity.” I recommend reading his full Twitter thread here:

I should be qualified to comment on the covid-19 pandemic. I'm a computational/system biologist working on infectious diseases and have spent five years in a world class 'pandemic response modelling' unit. In this thread, I will summarise what I believe I (don't) know. (1/12)

— Prof Francois Balloux (@BallouxFrancois) March 14, 2020

We need more consciously-responsible experts as such – experts who are candid in sharing their opinions and in admitting that they could be wrong and they could never be perfectly right. Nobody ever knows for sure. I’d like to share this quote on humility:

“Humility not in the idea that you could be wrong, but given how little of the world you’ve experienced you are likely wrong, especially in knowing how other people think and make decisions.”

Morgan Housel, “Different Kinds of Smart”
(September 27, 2018)

[Thinking Smart] “Aha” moments from working from home

This Tweet on technical difficulties people run into when they are working from home is a vivid illustration of the point: it is time to rethink work and work-tech.

Hearing stories from at least 2 banks that have asked people to work from home and suddenly realised:

1. Most staff work from desktop machines, not laptops
2. Many use phones and tablets and don't have access to a computer at home
3. No software is cloud-based, so need VPN

1/3

— Brad van Leeuwen (@BradvanL) March 18, 2020

The thing with a business continuity plan is it rarely gets the credit when business continues as usual. To the contrary, it is only missed (or blamed) when the business cannot continue as usual.

Re-imagining work extends to re-imagining the office building – this Tweet predicts voice or gesture controlled activation could become more prevalent. Imagine your office building lift becomes a mini Siri, Alexa or Google Assistant. Try saying: “Hey Lift, take me to the 19th floor.”

All elevators, doors, faucets, and handles will go to voice or gesture based activation as standard.

The technology now exists for hands-free everything. This is going to be hygiene 2.0 across society, at least in Asia. https://t.co/68gBWAT8Bk

— Balaji Srinivasan (@balajis) February 3, 2020

Other than conversations on work-tech, this “hot” Tweet takes it to the level of class consciousness:

This macro shock will result in more class consciousness than we have ever seen.

Expect bitter resentment.

You’re going through to spend the crisis dicking around with video conferencing tools while a whole class of people is getting decimated.

— Michael (@mmay3r) March 20, 2020

[Thinking Smart] “Aha” moments from working from home

With the surge of cases worldwide comes a surge in “information” about the coronavirus – though the information we see vary greatly in quality. I strongly recommend Defining Information from the Stratechery blog that shares insights on how to think about information:

“Given that over 90% of the PCs in the world ran Windows, writing a virus for Windows offered a far higher return on investment for hackers that were primarily looking to make money. Notably, though, if your motivation was something other than money — status, say — you attacked the Mac.”

“I suspect we see the same sort of dynamic with information on social media in particular; there is very little motivation to create misinformation about topics that very few people are talking about, while there is a lot of motivation — money, mischief, partisan advantage, panic — to create misinformation about very popular topics. In other words, the utility of social media as a news source is inversely correlated to how many people are interested in a given topic.“

Defining Information (Stratechery, April 2020)

In simple terms, as more people start talking about a topic, the average quality of the information you get drops. This is not surprising for two reasons: (a) you are more likely to hear higher number of repetitions of popular opinions and narratives; (b) there is a higher incentive for people to create or spread misinformation on a hot topic.

The Stratechery blog goes on to propose some helpful heuristics on how to deal with different types of information:

“For emergent information, like the coronavirus in February, you need a high degree of sensitivity and a high tolerance for uncertainty.”

“For facts, like the coronavirus right now, yo uneed a much lower degree of sensitivity and a much lower tolerance of uncertainty: either something is verifiably known or it isn’t.”

Defining Information (Stratechery, April 2020)

[Thinking Smart] What went wrong with media coverage? A failure, but not of prediction

Slate Star Codex is one of my favorite blogs by far. Scott Alexander’s post A FAILURE, BUT NOT OF PREDICTION is an insightful take on what went wrong with the media coverage on the coronavirus. A key concept that Scott discusses is that of probalistic reasoning:

“A surprising number of these people had signed up for cryonics – the thing where they freeze your brain after you die, in case the future invents a way to resurrect frozen brains. Lots of people mocked us for this – ‘if you’re so good at probabilistic reasoning, how can you believe something so implausible?’ I was curious about this myself, so I put some questions on one of the surveys.”

“The results were pretty strange. Frequent users of the forum (many of whom had pre-paid for brain freezing) said they estimated there was a 12% chance the process would work and they’d get resurrected. A control group with no interest in cryonics estimated a 15% chance. The people who were doing it were no more optimistic than the people who weren’t. What gives?”

“I think they were actually good at probabilistic reasoning. The control group said ‘15%? That’s less than 50%, which means cryonics probably won’t work, which means I shouldn’t sign up for it.’ The frequent user group said ‘A 12% chance of eternal life for the cost of a freezer? Sounds like a good deal!'”

A failure, but not of prediction (Slate Star Codex, April, 2020)

Scott summarized it well when he said: “Making decisions is about more than just having certain beliefs. It’s also about how you act on them.“

He shared a diagram showing two types of people: Goofus and Gallant. Goofus requires “incontrovertible evidence” before believing something is true, i.e., false until proven true. On the contrary, Gallant embraces uncertainty and does not look at things in an all-or-nothing fashion: he reasons in probability.

Scott argued that people behaved like Goofus when the coronavirus first started to spread:

“I think people acted like Goofus again.”
“People were presented with a new idea: a global pandemic might arise and change everything. They waited for proof. The proof didn’t arise, at least at first. I remember hearing people say thing like ‘there’s no reason for panic, there are currently only ten cases in the US’. This should sould like ‘there’s no reason to panic, the asteroid heading for Earth is still several weeks away’. The only way I can make sense of it is through a mindset where you are not allowed to entertain an idea until you have proof of it. Nobody had incontrovertible evidence that coronavirus was going to be a disaster, so until someone does, you default to the null hypothesis that it won’t be.“

“Gallant wouldn’t have waited for proof. He would have checked prediction markets and asked top experts for probabilistic judgments. If he heard numbers like 10 or 20 percent, he would have done a cost-benefit analysis and found that putting some tough measures into place, like quarantine and social distancing, would be worthwhile if they had a 10 or 20 percent chance of averting catastrophe.“

A failure, but not of prediction (Slate Star Codex, April, 2020)

Goofus-Gallant reasoning could also be applied to the debate about whether face masks are effective:

“Goofus started with the position that masks, being a new idea, needed incontrovertible proof. When the few studies that appeared weren’t incontrovertible enough, he concluded that people shouldn’t wear masks.”

“Gallant would have recognized the uncertainty – based on the studies we can’t be 100% sure masks definitely work for this particular condition – and done a cost-benefit analysis. Common sensically, it seems like masks probably should work. The existing evidence for masks is highly suggestive, even if it’s not utter proof. Maybe 80% chance they work, something like that? If you can buy an 80% chance of stopping a deadly pandemic for the cost of having to wear some silly cloth over your face, probably that’s a good deal. Even though regular medicine has good reasons for being as conservative as it is, during a crisis you have to be able to think on your feet.”

A failure, but not of prediction (Slate Star Codex, April, 2020)

[To be updated from time to time]

[Flash Fiction] Save the “Date” (1): Tinder Stories

Foreword: This is a flash fiction about dating & relationships. All characters and stories are fictional.

Harvey pushed open the doors of the bar and said to the receptionist without turning his head: “Reservation under Rachel M.”

“Yes sir. This way please.”

The receptionist led Harvey to a table with sofa seats right next to the bartender’s. He casually scanned the room – there was a lady with wavy dark hair in a pantsuit drinking alone, one hand holding the glass and the other hand mindlessly tapping the table. Harvey saw her briefcase had the letters Kimberly & Partners marked on it – it is the name of a law firm in the office building right across the street.

She is likely a frequent visitor of this bar, Harvey thought to himself, and made a mental note to get her number some time.

His thoughts were interrupted by a “thud” sound coming from the table. He turned around to see a black notebook land on the marble surface, followed by a “cling” sound of a pen landing next to it. He looked up in amusement as the owner of the stationery took off her suit jacket, put it on the empty sofa seat alongside her laptop bag, and sat directly opposite him.

“Good evening, Mr. Weinstein.” Rachel said without a smile.

Harvey chuckled at the sarcastic reference of Harvey Weinstein – film producer and convicted serial sex offender. “Good evening, babe. Mr. Weinstein here was planning to treat you to an unforgettable night…if you look like your profile pics.”

“Scarlett Johansson sends her regrets for a last-minute schedule clash. She has sent me in her place and hopefully I would meet your high standards.”

Harvey burst out laughing while shaking his head. “Rachel Mckingsley – the girl who bites with her tongue. Painful yet pleasing. How I have missed your spice.”

Rachel smiled. “Harvey Hamilton – the guy who flirts with his little toes. Annoying yet never knows to back off. How I have not missed your shamelessness.”

Harvey signaled for the waiter to order.

“Virgin mojito.” Rachel said.

Harvey raised his eyebrows. “Very fitting drink for our upcoming conversation on Tinder. So tell me, what’s up in life? How come you are working on a reality show about dating now? I was like FML when you told me this on the phone – what happened to the Rachel who is passionate about documentaries & live debates?”

Rachel let out a sigh. “I’ve been working on the The Weekend Chat since I joined NetFox TV 3 years ago – and I love the autonomy I have in running the show, the professionalism of my team, and the depth of analysis we are able to do and present. But the viewing statistics have been dropping – and dropping hard – Alex is having a hard time convincing the management to keep the show. One of the conditions of the show’s continuance is that everyone is 50/50 staffed – so I am working on The Weekend Chat and launching our new reality show on dating at the same time. I don’t have a very good idea yet on the format of the show – there are so many matchmaking or dating shows out there, and I am yet to find THE idea that could ‘wow’ people.”

“A reality show about dating?” Harvey laughed. “Sure, I could use some advice or probably offer some as the King of Dating.”

“Who has had all kinds of fantastic experiences that blow your mind away. So shoot Mr. Charming – tell me all about your fantastic Tinder journey. What’s your count for Tinder dates now? 157?”

“Sounds about right. You wanna be the 158th date?” Harvey added a wink.

“Why not? I am open-minded to being the 158th if you are able to get me just one referral from one of your past 157.” Rachel blinked and gave Harvey the told-you-don’t-mess-with-me stare.

“Wow girl, I won’t toy with that murderous look of yours.” Harvey shrugged. “Elle a les yeux revolver. Elle a le regard qui tue. Elle a tiré la première…” Harvey started singing the French pop song Elle A Les Yeux Revolver (She Has Eyes Like Revolvers):

Elle a les yeux revolver
Elle a le regard qui tue
Elle a tiré la première
M’a touché, c’est foutu
* * *
She has eyes like revolvers
She has a look that kills
She has fired first
That has hit me, and it is all finished

Elle A Les Yeux Revolver – Marc Lavoine (song)

Rachel couldn’t resist cracking up with laughter. She shook her head in disbelief as Harvey still sang off tune – even though this did not discourage him from joining the university choir, where he met Rachel.

Harvey was the “life of the party” at college, and has a reputation among their social circle of being the typical Butterfly – a “serial dater” as in one who hops between one “short-term date” to the other, usually a few weeks long and almost never more than two months. Rachel remembers the last time hearing Harvey say he has a girlfriend was when they were back in college.

“Okay, let’s get down to ‘business.'” Rachel uncapped her pen and started writing in her notebook. “I remember you mentioned you have been using Tinder for more than 2 years. Tell me more about what the Tinder experience is like for you?”

“Amazon.” Harvey said.

“Excuse me?” Rachel took a sip of the virgin mojito that just arrived.

“Swiping on Tinder is similar to shopping on Amazon.” Harvey clarified. “For me at least.”

“I have heard that analogy before, comparing online dating to online shopping.”

“Bingo!” Harvey snapped his fingers. “You know my style, Rachel – I am not looking for anything ‘stable’ or however you call it. At this stage of my life, I just wanna look for some fun. Dating for me is the icing on the cake – it is sweet and pleasant, but not something that I’d lose sleep over.”

“Am I right to say that for you, swiping profiles on Tinder is similar to browsing restaurants on a food delivery app?”

“That’s not a bad way to put it.” Harvey nodded. “In a way, yes. And don’t give me the ‘you are toying around with woman’ kind of line. I know it’s typical for people – especially women – to point their fingers at me and call me a playboy. But hey, you know what, when they tell you ‘all’s fair in love and war,’ they mean nothing‘s fair in love and war. There’s no such thing as a universal rule for dating – who says that I must enter the game with the ‘pure’ intention of looking for something committed? It’s a free market economy Rachel – and people freely choose what kind of dating they want. Going for casual dating is as legit as looking for commitment.”

Rachel took some notes and sipped some more mojito. “If you don’t misrepresent your intentions and are open about what you’re looking for, then sure why not? I’m not judging you for your dating model. I’m trying to understand what dating means for you.”

“Whatever.” Harvey shrugged. “You and I are both people who don’t hold back their thoughts, and I’ll be straightforward with you. I don’t care if people call me a playboy – or is there a new term called f***boy nowadays? As in guys who get a fat share of ‘Netflix & chills’? I’d say that’s just a jealous reaction from guys who have pathetically few matches and aren’t able to catch the hot women out there – who are all, unsurprisingly, falling for hot dudes like me.”

“I’ll give you 3 seconds to feel good about yourself. Now let’s come back: You don’t mind being called a playboy, or you take pride in being called a playboy?” Rachel paused writing and looked up at Harvey.

Harvey took a sip of his tequila. “Man, you’ve got some tough questions.”

“That’s because man, you’ve got some juicy answers.” Rachel smiled and raised her cup. “Plus, correction: ‘boss lady, you’ve got some tough questions.’”

Harvey pursed his lips for a while. “I think you are onto something. If I am completely honest, it does feel good to tell people things like you’ve dated XYZ number of girls this month. And it doesn’t hurt when some of them are Victoria’s Secret model material. Makes me come off as a lady’s man – which I am by the way.”

“Have you shared pictures of your dates with friends or family?”

“I know what you mean.” Harvey winked. “Yep, I confess I like to show off pictures of extremely hot dates to some pals and that’s my ego at play.”

“You see dating as a competition in a sense, don’t you?”

“Who says it isn’t? Dating – or mating – is a competition. Guys do compare who’s walking next to the hottest girl, and I bet you ladies size up each other’s boyfriends too. Come on, we are visual animals. Whether we realize it or not, we are comparing who’s more attractive than whom all the time. We all have an animal’s brain, Rachel. Not much better than the monkeys in the wild who fight to mate. It’s competition in the free market dear. By the way, have you noticed one thing?”

“Noticed what?” Rachel looked puzzled.

“Your pupils totally dilated just now when you looked at the bartender. He’s quite a handsome guy right?”

Rachel gave a shrug. “Or my pupils dilated because I couldn’t handle the strong liquor in my virgin mojito.”

“Hahahaha!” Harvey burst out laughing. “Good one Rachel! I’m glad all those years of serious investigative journalism haven’t taken away your humor. I’m starting to look forward to that dating show of yours – might be something really fun and funny.”

“And I believe it would be fun and funny to invite you to the show if I were not afraid of being accused as an accomplice in the conspiracy to break hearts around the world.”

“So what dating show ideas do you have in mind? Bounce them off me.” Harvey asked.

“One idea that’s being discussed is conflict resolution. An idea pitched is bringing in couples – married or not – who have problems and help them get over the issues.”

Harvey frowned. “Couple problems? You mean like people who can’t decide who throws out the trash or can’t figure out whether their other half is cheating?”

“Sounds like you’ve had your lucky share of problems. Tell me: what are some common problems in your past 157 Tinder dates? How come none of the amazing hot ladies you dated have met your critical eye and become your official girlfriend?”

“That’s a good question.” Harvey nodded. “I know I’ve got this double-reputation as a playboy and a picky dude because I date a lot and I’ve never ‘settled down’ with someone. To be fair, most of the ladies I’ve dated would make great girlfriends – there may be areas where we don’t gel, like I’m a night owl and she’s a morning bird – but then again there’s no such thing as the perfect girl. I’d be dating my clone – which would be boring.”

“If you accept that nobody is perfect and everybody has flaws, why didn’t you develop a more serious relationship with one of your dates?”

“I guess you could call this the ‘easy way out’ type of mindset. Think about it Rachel: there are hundreds and thousands of Tinder profiles right at my fingertips. When you’ve got a conflict with your date partner, it is usually much easier to swipe and find another date than to talk with your current partner and try to work things out. Yeah – Tinder is an easy retreat. Why not take the easy route?”

“The best one is always the next one?” Rachel rephrased. “Does that sound like a good description of what you’re thinking?”

“You could say that.” Harvey said thoughtfully. “It’s like how you ladies view clothes. The new arrivals are always prettier than the old wardrobe. Same logic.”

Rachel tapped her pen and got lost in thought for a few seconds. She recalled a book she has read by relationship expert John M. Gottman, former MIT mathematics major. It’s called Eight Dates: Essential Conversations for a Lifetime of Love.

“What’s on your mind?” Harvey asked as he saw Rachel fell silent.

“I remembered reading about the definition of commitment in a book.” Rachel replied. “It says part of being committed to someone means you put all your eggs in one basket – you never wonder whether the grass is greener on the other side; you never ask yourself whether there could be someone out there that could be better than your partner; you never look back and second guess your decision. What you said reminds me of this. Being committed to someone – by this definition at least – is hard, and it is even harder with Tinder. I get what you are saying. Nowadays it is more difficult to not wonder whether there’s someone out there who is a better match. This is the allure of Tinder: the promise of options, even though the next option is never guaranteed to be better than the current one.”

“That’s some deep s***.” Harvey said. “Way too deep for a drunkard like me to handle.”

“Then I’d say it’s time to put some food in your belly to neutralize the alcohol.” Rachel waved at a waiter and asked for the menu.

The waiter returned with two sets of menus – a booklet of regular food items, and a separate list of a few seasonal specials. Rachel looked at the two menus and thought of something.

“Harvey, I’d suggest we forget about the thick regular menu and choose only from this short list of seasonal specials.”

“Oh?” Harvey raised his eyebrows. “Did you have a bad experience with any of the items on the main menu?”

“Nope,” Rachel shook her head. “But a story about jam tells us that we’d probably be happier with our choices if we pick from a shorter list. When shoppers are asked to choose from a larger number of jam varieties, they take longer to make their decision and feels worse about their decision afterwards. So I’d say we start with a smaller sample and go from there.”

“Why am I sensing a reference to Tinder here?”

“There is.” Rachel nodded. “Have you ever wondered whether having more choices on Tinder is making you less satisfied with your choice? One reason could be, as you said, that you are more likely to wonder whether the other choices out there are better. Just like if you pick one jam bottle out of 1,000 options, you’d lose more sleep over whether the remaining 999 taste better, and probably fidget less if you picked one out of two jam flavors.”

Harvey chuckled. “Oh my Rachel, you could make your own show being the relationship therapist. You sound like you’ve been giving couples therapy for thirty something years!”

“I’ll take that as a compliment.” Rachel said as she stood up. “Excuse me for a toilet break. Tell you something interesting about a super dating app idea when I’m back.”

“Super dating app? I’m all in for it!”

“Wait and see.” Rachel smiled. This conversation on dating has turned out to be far more interesting than she expected.

(To be continued)

Dance in the Elevator, Dare to be Happy

Context: “Dare to be happy” were the words gifted to me by a V.I.P. in my life. Our conversation on happiness reminds me of recent shows I’ve watched, from Billions (Showtime) to Sex Education (Netflix) to Devil Wears Prada (Fox), hence this post on happiness was born. May we all kick start 2020 with happy vibes! 🙂

Let’s Dance with Ben Kim

For those who follow the US TV show Billions, I highly recommend checking out Ben Kim’s (hilarious and stunning) elevator dance scene (a.k.a. “public self-initiated humiliation”) in Season 3 Episode 10. Here is a clip:

Ben Kim’s hilarious elevator dance scene in “Billions” Season 3 Episode 10

For those who raise an eyebrow and go: “What is Billions?” I’d recommend giving the Billions show a shot – probably a good match for those who are looking for a smoothie blending together entrepreneurial vibes from Silicon Valley, juicy backstabbing from House of Cards, and legal heat from The Good Wife.

Back to the Ben Kim dance scene – I love it! Not to mention the clip on its own is funny, but also bear in mind that this is a very out-of-character move for Ben Kim. He is the type of person who wants to duck down rather than stand out, who prefers to sit downstairs with regular staff rather than sit upstairs in the C-suite, who aims to survive rather than thrive. His self-remark at his annual compensation review meeting with Axe is a vivid reflection of his personality:

I should not throw out the first number (of bonus that I would want to get), because I have a tendency to undervalue myself.

Ben Kim to Bobby Axelrod, Billions Season 3 (see clip here)

Ben Kim is the “good old guy” who feels happy at getting a new title while keeping the old salary. This pretty much sums up the trait that makes him stand out – and ironically, it is precisely the desire of him to not stand out.

You may pause here and ask: if Ben Kim is such a shy person who has trouble standing up for himself, where on earth did he garner the courage to dance (and strip his shirt off) in a lift with his big boss and complete strangers?

Answer: per the advice of Wendy Rhoades, the “spiritual animal” of Axe Capital, to step out of his comfort zone and have a voice of his own. (Though Wendy did try and failed to warn Ben Kim not to ruin the elevator ride with Axe and the fund’s potential investors.)

The elevator dance scene was a turning point for Ben Kim – afterwards, when Axe confronted him with a sharp: “What the hell was that?” Ben Kim, unlike his usual tongue-tied self when dealing with higher authorities, found the courage to spit out an investment idea he has held under his belt for a long time:

After spitting the investment idea out and receiving Axe’s pat on the shoulder, Ben Kim breathes a sigh of relief and is finally happy. He is happy because he has allowed himself to be happy by allowing himself to say what he wants to say – and this is no small feat for Ben Kim: a short while back, he had trouble peeing in the toilet after his half-fleshed out idea was challenged.

For Ben Kim, the question to ask is not: “Do you want to be happy?”
A better question to ask is: “Do you allow yourself to be happy?”
In other words: Do you dare to be happy?

Do You Dare to be Happy?

We tend to think of happiness as a wish beyond our control, when it could be and can be an option of our choice. We tend to think of happiness as an elusive goal to seize around us, when it could be and can be an inner state right within us. To borrow the words of the Bible to fit this context: “Ask and it will be given to you; seek and you will find; knock and the door will be opened to you.”

The question is not: can we be happy?
The question is: why can’t we be happy?

The question is not: why doesn’t this (thing or person) make us happy?
The question is: why don’t we allow ourselves to be happy?

Hence the ask is not about wanting to be happy, but about daring to be happy: Do we dare to dance in the elevator like Ben Kim? Do we dare to be crazy in the eyes of others and crazily happy in the eyes of ourselves? Do we dare to strip free of our shirt (metaphorically) alongside the weight of caring too much about how others look at us?

Ironically, in a sense the ask is about whether we truly want to be happy – because if we truly, desperately, seriously want to be happy with all our heart, then we would dare to be happy. Then we would overcome each and every single fear. Then we would say “go to hell” to any doubt, any worry, any fear. Then we would care about and only care about our happiness, because we want it so much.

If we truly want something badly enough, we would not hesitate to go for it. The “dare” would hardly be a hard choice – it would be natural step we take without hesitation. Ben Kim wanted to prove to Wendy – and ultimately to himself – that he could have an independent voice that he is daring to dance half-naked in the elevator.

It’s Not Crazy to be A Little Crazy

I’m a big fan of the song “Crazy” by Alanis M. as featured in the movie Devil Wears Prada. Quoting the lyrics:

But we’re never gonna survive, unless
We get a little crazy
No we’re never gonna survive, unless
We are a little crazy
– – –
In a sky full of people,
Only some want to fly,
Isn’t that crazy?

“In a sky full of people, only some want to fly. Isn’t that crazy?” I love this sentence – what is crazy is not that some people want to fly, but that so few people want to. What is crazy is not that some people day-dream, but that so few people do.

Where is the fun in life if we never get crazy? If we never experience something in life that we did not already predict? If we never dare to be happy and go against the inertia of “life as yesterday”?

Last but not least, I share the MTV of “Crazy” with you – may (a healthy dose of) crazy vibes bring us happy vibes! Cheers to a happy 2020 where we dare to be happy, dare to be crazy, and dare to be free! 😀

Come Out to Play for Fun – On “Finite and Infinite Games”

Context: This post is inspired by the book Finite and Infinite Games. As the subtitle reads, this book offers “a vision of life as play and possibility.” Perspective-changing. At time of writing, I have finished ~1/3 of the book.

Finite games play within boundaries.
Infinite games play with boundaries.

James P. Carse, “Finite and Infinite Games”

There Are Two Kinds of Games

Namely: finite games and infinite games. See quote above for what I think is the most important takeaway to remember on what sets the two apart.

But first, let’s talk about what all games have in common: whoever plays, plays freely (by free choice):

In one respect, but only one, an infinite game is identical to a finite game: if they play they play freely; if they must play, they cannot play.

James P. Carse, “Finite and Infinite Games”

Other than this similarity, finite and infinite games differ drastically. I summarize below the key takeaways for different types of readers:

A/ For efficiency-maximizing readers => here are your bullet points

P.S._version_fun: I am aware that “efficiency-maximizing” is sometimes used as an euphemism for “I don’t have time” and / or “I don’t care” and / or “I am too important for details”. Just joking. 🙂

How to read: trait_of_finite_games vs. trait_of_infinite_games (I give myself credit for clearly labeling my legend):

• Goal: to win vs. to continue playing;
• Is temporally bounded: yes (clear start and end) vs. no (unclear start and no end)
• Is spatially bounded: yes (within a marked area) vs. no
• Is numerically bounded: yes (fixed number of players, so that one could emerge as the clear winner and end the game) vs. no (players walk on and off the field as they wish)
• Rules of the game: contractual terms by which the players can agree who has won, and do not change throughout the play vs. contractual terms by which the players agree to continue playing and are dynamic

B/ For word-lovers and creatives => here is your metaphor

And a bonus picture for the metaphor:

P.S._version_creepy: 23. This number is why I chose the picture above. The 23 enigma is, depending on your perspective, creepy and/or mysterious and/or inexplicable and/or irrational and/or nonsense and/or [insert adjective(s) of your choice].

I bet after you read up on “23” and its stories, you will start to see the number everywhere. Just like how I was able to immediately spot the 23 in this picture when I was searching for theatre-related pics. Don’t say I didn’t warn you. For those who want to go down the rabbit hole of more things that will surprise your brain (disclaimer: surprise could mean “mess up seriously” for some people) – check out the book Cosmic Trigger I: Final Secret of the Illuminati. My biggest takeaway from the book is: don’t read the book if you want to remain sane. You’ve been warned. This is the one time I am trying (and I think I am actually) being nice.

The metaphor itself (finally emerges after a super-long ad above which does not generate any additional income for me): finite games = theatre, infinite games = drama:

Finite games mirror theatre in –

• Have a clear ending – finite games end when a clear winner emerges
• Have scripted roles – all players in a finite game play the role that (they think) will help them win

Infinite games mirror drama in –

• Avoid predictable outcomes – a game is an infinite game precisely because the outcome is not known
• No scripted roles – players in an infinite game constantly change to continue the game playing with no ending, and to continue the surprise

Insert-rant: And I totally love I also used bullet points in this section. It is as plain as day that I am an efficiency-maximizing writer. I have deliberately chosen the color red to emphasize how unimportant this rant is. Oh, I meant the color red *and* the italics.

Some addendums on acting: in finite games, “self-veiling” is inevitable, as in all players act according to a scripted role (that they have assigned themselves, or think they ought to be playing). I find this part from the book to be very thoughtful:

What makes this an issue is not the morality of masking ourselves. It is rather that self-veiling is a contradictory act – a free suspension of our freedom. I cannot forget that I have forgotten. I may have used the veil so successfully that I have made my performance believable to myself. I may have convinced myself I am Ophelia. But credibility will never suffice to undo the contradictoriness of self-veiling.

James P. Carse, “Finite and Infinite Games”

This reminds me of this quote of Irene Adler in BBC’s Sherlock TV series: “Do you know the big problem with a disguise, Mr. Holmes? However hard you try, it’s always a self-portrait.”

Why so serious? (And how to be playful?)

Seriousness is too boring to the playful human condition.

Michael Bassey Johnson

Here is some serious chain-of-thinking delivered in playful tones:

Seriousness is too boring yet all too common, because boredom is the default tone of life, which may not be a bad thing if you believe the existence of “boredom” is what makes the “NOT-boredom” possible, similar to how Taoism tells us that concepts exist in opposites just as brightness cannot exist without darkness, just as the “is” defines the “is not” and vice versa.

I appreciate you moving on to read this line, as the above paragraph has not scared you off. 🙂 Smiley emoji here because: why so serious?

And seriously: why are we so serious?

And the serious answer: “Seriousness always has to do with an established script, an ordering of affairs completed somewhere outside the range of our influence.“

Think about it, seriousness always implies there is a script, which implies there are scripted roles. We are more serious than usual when we interact with a uniformed policeman or doctor, compared with interacting them in their off-uniform casual clothes.

In contrast: “We are playful when we engage others at the level of choice, when there is no telling in advance where our relationship with them will come out – when, in fact, no one has an outcome to be imposed on the relationship, apart from the decision to continue it.”

As you may have guessed, being serious is the tone of finite games, while being playful is the game that the infinites play. Importantly, to be playful should not be confused with to be “trivial or frivolous, or to act as though nothing of consequence will happen”. To be playful means acknowledging that any consequence could happen, and welcoming this unbounded realm of possibilities:

To be serious is to press for a specified conclusion. To be playful is to allow for possibility whatever the cost to oneself.

James P. Carse, “Finite and Infinite Games”

Linking back to the common purpose of all finite games – play to win. Yet how can you be truly playing playfully, if you take winning seriously? Thus, being playful is the luxury reserved for the infinite game players – who play playfully with the goal to continue playing.

And I must conclude this section with a playful picture:

Pick your poison: Power or Strength?

Of course I am obliged to be playful and “not-so-serious” by this point. So the playful answer is: why not both? Get a personal trainer if you want some help with fitness.

Back to the serious topic: Finite games play for power. Infinite games play for strength.

Power is embedded in the emergence of a winner at the end of the game. Power is passive, it is “never one’s own,” as it requires the voluntary acceptance of the power by others.

Strength is paradoxical. “I am not strong because I can force others to do what I wish as a result of my play with them, but because I can allow them to do what they wish in the course of my play with them.” Strength is mocking power in the face and having no thoughts of it whatsoever.

Power concentrates only in a small hand of victors – because winning is not something you could opt into, but something that is decided for you according to the rules of the game.

Strength benefits potentially anyone – because strength is something we could all choose to have, something we decide for ourselves according to the will of our mind.

So my friends – decide how you want to play. Pick your script – or no script. Recite seriously or explore playfully. Fight for your power or defend your strength.

The night is getting dark…

…and time to come out to play.

Defending Selfishness and Questioning Altruism (on Ayn Rand’s philosophy)

“Why do you use the word ‘selfishness’ to denote virtuous qualities of character, when that word antagonizes so many people to whom it does not mean the things you mean?”
* * *
To those who ask it, my answer is:
“For the reason that makes you afraid of it.”

Ayn Rand, “The Virtue of Selfishness“

Context: This article looks at the virtue of selfishness & the vice of altruism, according to Ayn Rand‘s philosophy – widely referred to as “objectivism”. Rand is a Russian-American writer and philosopher, best known for her novels The Fountainhead and Atlas Shrugged. She has also published two collections of essays: The Virtue of Selfishness and For The New Intellectual. She is a strong advocate for rationality and capitalism (while being a firm critic of mysticism and socialism).

Popular Opinion: Selfishness = A Vice of Negative Value

“Sweetheart, do share your toys with other children, don’t keep it to youself selfishly!”
– parent to child

“How could you be so selfish and only think about yourself when you make decisions?”
– husband to wife

“For where you have envy and selfish ambition, there you find disorder and every evil practice.”
– Bible, James 3:16

“Is selfishness is a virtue or a vice?” If I ask this question, I would not be surprised to see a few folks roll their eyes or stare at me with a isn’t-this-obvious look.

The dictionary definition of selfish often has a negative connotation to it:

The Cambridge Dictionary : Selfish (adj.)
– caring only about what you want or need without any thought for the needs or wishes of other people;
– someone who is selfish only thinks of their own advantage.

It is a popular belief that “selfishness” is a vice to be corrected, and its opposite “altruism” is a moral ideal to be embraced. This narrative is so dominant – in fact, we rarely hear alternatives – that most people have taken it for granted.

However, just because something is “conventional” does not mean it is “wisdom”. Conventional wisdom is no substitute for thoughtful wisdom – and it is time we re-examine what it means to be selfish, and whether being selfish has its own merits.

Ayn Rand: Selfishness is Morally Neutral as a Term

Ayn Rand argues that the negative connotation we assign to the word “selfishness” is misplaced. On the contrary, she argues that the word “selfishness”, at its core, is a morally-neutral term:

This concept (of selfishness as concern with one’s own interests) does not include a moral evaluation; it does not tell us whether concern with one’s own interests is good or evil; nor does it tell us what constitutes man’s actual interests. It is the task of ethics to answer such questions.

Ayn Rand

Applying a similar logic, Rand argues the positive connotation assigned to the word “altruism” is misplaced. Being altruistic itself is not necessarily virtuous or beneficial. Rand says there are “two moral questions which altruism lumps together into one ‘package-deal'”, namely:

(1) What are values?
(2) Who should be the beneficiary of values?

Rand is firmly against the cult of altriusm:

Altruism substitutes the second (moral question) for the first; it evades the task of defining a code of moral values, thus leaving man, in fact, without moral guidance…the beneficiary of an action is the only criterion of moral value—and so long as that beneficiary is anybody other than oneself, anything goes.

Ayn Rand

In other words, Rand is saying the fact that the beneficiary of an action is someone other than oneself (i.e., altruistic) – this fact alone – does not give us any information about this action is more justifiable than others. We learn nothing about the underlying values associated with this action – and hence we should not jump to a moral judgment too soon, too wrong.

Whether a selfish act (or altruistic act) is morally justifiable or not – this is a situational question that should be looked at case by case. Rand presents this thought experiment: imagine two people – A is a “selfish” businessman who produces goods that society wants in order to earn money; B is a “selfish” robber who loots. A and B are both selfish, but most would argue that A’s selfishness actions are more morally justifiable than those of B’s.

In the words of Rand, there is “a fundamental moral difference between a man who sees his self-interest in production and a man who sees it in robbery”:

The evil of a robber does not lie in the fact that he pursues his own interests, but in what he regards as to his own interest; not in the fact that he pursues his values, but in what he chose to value.

Ayn Rand

It is not contradictory to say: (a) man should selfishly pursue his own interests, and (b) some interests are morally justifiable and others aren’t. Being selfish is a means to achieve one’s goal – whether that goal is ethical is a separate discussion.

Nature vs. Nuture: Is Everyone Born Selfish?

Some believe we are born with the natural desire that the world revolves around us – we are born with selfishness.

For Ayn Rand, being selfish requires one to first have a proper “self”. Having a (proper) sense of “self” is the prerequisite to being “selfish”. Rand defines self differently from popular usage of the term:

A man’s self is his mind – the faculty that perceives reality, forms judgments, chooses values.

Ayn Rand

A true sense of self is based on an active choice of values, rather than a passive imitation of what others value. Sadly, the sense of self is lost to those who live everyday being the person they think others would want them to be:

The abdication and shriveling of the self is a salient characteristic of all perceptual mentalities, tribalist or lone-wolfish. All of them dread self-reliance; all of them dread the responsibilities which only a self (i..e, a conceptual consciousness) can perform, and they seek escape from the two activities which an actually selfish man would defend with his life: judgment and choice.

Ayn Rand

Judgment of reality and choice of values – these are the two prerequisite activities that an “actually selfish” man would perform relentlessly – and he would defend with his life the right to define himself. The best of such men are what Rand calls the “New Intellectuals”, i.e., people who are “willing to think” and “who know that man’s life must be guided by reason”:

There are two principles on which all men of intellectual integrity and good will can agree, as a “basic minimum,” as a precondition of any discussion…a. that emotions are not tools of cognition; b. that no man has the right to initiate the use of physical force against others.

Ayn Rand

Knowing how to be “selfish” in a proper way is a privilege, a skill, a capability – not a trait we are born with, but rather a subject we should study.

Asking the Non-Obvious: What is Wrong with Altruism?

Following a defense of critism, let us switch to the opposite side and look at Rand’s critique of altruism. She calls altruism “the basic evil” that is “incompatible with freedom, with capitalism, and with individual rights.”

As before, let us first clarify what Rand means by the word altruism:

What is the moral code of altruism? The basic principle of altruism is that man has no right to exist for his own sake, that service to others is the only justification of his existence, and that self-sacrifice is his highest moral duty, virtue and value.

Ayn Rand

Importantly, Rand says altruism should not be confused with “kindness, good will or respect for the rights of others”. These are possible consequences, but not defining primaries or traits, of altruism (and altruistic actions). I find this analysis of Rand to be extremely powerful:

Do not hide behind such superficialities as whether you should or should not give a dime to a beggar. That is not the issue. The issue is whether you do or do not have the right to exist without giving him that dime. The issue is whether you must keep buying your life, dime by dime, from any beggar who might choose to approach you.

The issue is whether the need of others is the first mortgage on your life and the moral purpose of your existence. The issue is whether man is to be regarded as a sacrificial animal. Any man of self-esteem will answer: “No.” Altruism says: “Yes.”

Ayn Rand

Rand goes one step further to challenge the notion that giving makes the giver happier:

Even though altruism declares that “it is more blessed to give than to receive,” it does not work that way in practice. The givers are never blessed; the more they give, the more is demanded of them; complaints, reproaches and insults are the only response they get for practicing altruism’s virtues (or for their actual virtues).

Ayn Rand

Even from the perspective of a consequentialist, Rand claims that altruism does not lead to “a recognition of virtue”, “self-esteem or moral innocence.” To the contrary, Rand believes altruism suffocates the giver with guilt – placing a burden on him to give constantly, selflessly, tiringly; casting a spell on him to think it is his moral responsibility to give:

If the giver is not kept under a torrent of degrading, demeaning accusations, he might take a look around and put an end to the self-sacrificing. Altruists are concerned only with those who suffer—not with those who provide relief from suffering, not even enough to care whether they are able to survive. When no actual suffering can be found, the altruists are compelled to invent or manufacture it.

Ayn Rand

Concluding Remarks: Being a New Intellectual

At the end of writing about Rand’s philosophy, I must confess that I am fully aware of this: I am getting ahead of myself in writing about Rand. I have read so little of her writings (or writings about her) that my representation of her philosophy could be missing out key pieces.

Despite being new to Rand School, I did not hold back on writing about Rand, with the most important reason being that few philosophers have hit me hard like she did. It is the feeling of exaltation mixed with exasperation when I turn the pages of her books. It is the realization that there are so many questions out there that I have not asked (consciously or subconsciously), so many meanings out there that I have not pondered. It is the impulse that I must never stop the quest to understand the questions that define what it means to be alive, what it means to be human. These and so much more that I am at a loss of words to describe.

I leave you with words of Rand discussing The New Intellectual. I aim to live up to her definition and expectation of what it means to honor one’s intellect:

To support a culture, nothing less than a new philosophical foundation will do. […] The greatest need today is for men who are not strangers to reality, because they are not afraid of thought.

The New Intellectual will be the man who lives up to the exact meaning of his title: a man who is guided by his intellect – not a zombie guided by feelings, instincts, urges, wishes, whims or revelations.

[…] He will be an integrated man, that is: a thinker who is a man of action. He will know that ideas divorced from consequent action are fraudulent, and that action divorced from ideas is suicidal.

Ayn Rand

I part with two quotes (callings) from Rand at the end of her essay:

“Gentlemen, leave your guns outside.”

“The intellectuals are dead – long live the intellectuals!”

Does meritocracy lack merit? A critique from “The Meritocracy Trap”

Context: The Meritocracy Trap: How America’s Foundational Myth Feeds Inequality, Dismantles the Middle Class, and Devours the Elite is a book by Professor Daniel Markovits of Yale Law School, “attacking the false promise of meritocracy”. An insightful read – packed with elaborate arguments backed up by research & case studies. For those who are short on time, you could get the big ideas from Daniel’s sharing on the Erza Klein Show podcast, or from this article in The Atlantic.

The bold claim: merit is a counterfeit value

Merit itself has become a counterfeit value, a false idol…what it was invented to combat. A mechanism for the concentration and dynastic transmission of wealth and privilege across generations. A caste order that breeds rancor and division. A new aristocracy, even.

Daniel Markovits

The meritocratic ideal, i.e., “social and economic rewards should track achievement rather than breeding,” is a mainstream ideal that is often taken for granted and rarely even questioned. In his book, Daniel not only questions meritocracy, but goes one step further to challenge and critique it.

His central, unconventional claim is meritocracy is a form of aristocracy in disguise – just like the aristocratic system it aims to replace, “merit is not a natural or universal value, but rather the upshot of prior inequalities“.

The setup: meritocracy constructs the “elite class” via meritocratic competition

Daniel argues that meritocracy constructs what is commonly referred to as “the elite class” via two ways:

“First, meritocracy transforms education into a rigorous and intense contest to join the elite.
* * *
Second, meritocracy transforms work to create the immensely demanding and enormously lucrative jobs that sustain the elite.”

(1) The education race: the meritocratic inheritance

“Although meritocracy once opened up the elite to outsiders, the meritocratic inheritance now drives a wedge between meritocracy and opportunity.“

Inheritance under the old aristocratic system is largely viewed as “unjust” – the (relatively cost-free) inheritance of capital, such as passing down money or real estate, is widely viewed as unfair birth lottery. In layman terms, it is unfair that some are born with a silver spoon in their mouth.

Proponents of meritocracy believe that “merit” is the right answer to encouraging social mobility – build an education system that selects based on merits of the students, they say, and let the truly talented make their way up the ladder.

Daniel argues the reverse:

“Education assumes the role in meritocracy that breeding played in the aristocratic regime.”

Today, Harvard, Princeton, Stanford & Yale accept more students from households in the top 1% of the income bucket than from households in the bottom 60% combined. Students with parents whose annual income exceed $200K score ~250 points higher on the SAT compared with students whose parents make $40K-$60K.

The statistics on social mobility do not show a more optimistic picture. As The Atlantic reports:

“Absolute economic mobility is also declining—the odds that a middle-class child will outearn his parents have fallen by more than half since mid-century—and the drop is greater among the middle class than among the poor.”

In the meritocracy system, parents in the elite class pass on “inheritance” in forms other than direct capital transfer – these parents invest capital heavily into the education of their kids, at orders of magnitude that middle-class parents cannot expect to match.

When we hear educators advertise “equal opportunities to education” for children, we should pause and ask ourselves: what does the word “equal” mean here? It is not sufficient to apply the same (equal) screening criteria to applicants. The pre-requisite to equal opportunities comes from equal access to opportunities. This means the resources that a child has access to should not be constrained by the wealth of the family he or she is born into.

(2) The jobs race: “compulsive overwork” of the elites vs. “enforced idleness” of the middle class

The meritocratic competition “pervades elite life” and extends far beyond school into the professional lives of those who want to sustain their position at the top:

“Evaluations that were once quarantined to exceptional moments like college admissions season or promotion to partner or managing director now infect every step of a meritocrat’s career. Every year, from preschool through retirement, includes some contest or assessment that filters, tracks, or otherwise influences his opportunities.”

Daniel points out an interesting shift in the work paterns of the elites: the “once-leisured rich” work harder than ever before today. Along with a change in work behavior comes a change in values:

“Elite values and customs have adapted to suit these new facts (of compulsive overwork). High society has reversed course. Now it valorizes industry and despises leisure. As every rich person knows, when an acquaintance asks ‘How are you?’ the correct answer is ‘So busy.’“
* * *
“Meritocracy makes effortful and industrious work – busyness – into a sign of being valued and needed, the badge of honor.“

Daniel shares a “standard disciplinary joke” amongst investment bankers that “they will be lucky to get any day off besides their wedding day. Nor do the hours necessarily improve with seniority.” In a similar humorous fashion, the Wall Street Journal puts up an advertisement that reads, “People who don’t have time make time to read the Wall Street Journal.”

On the flip side, just as much as the elite class today take pride in being busy, they also look down on idleness & leisure. Daniel notes bankers often compain about the “outside (non-elite) world,” where “people leave work at five, six p.m.” and “take one hour lunch breaks”. These people are perceived as “just are not motivated in the same way” as they are.

The compulsive overwork of elites is “the same alienation that Karl Marx diagnosed in exploited proletarian labor” with “an added twist”, in the words of Daniel: “The elite, acting now as rentiers of their own human capital, exploit themselves, becoming not just victims but also agents of their own alienation.” Daniel believes the “busy” elite who takes pride in never creating time for one’s true self “places himself, quite literally, at the disposal of others – he uses himself up”.

An analogy is made with Chekhov’s The Cherry Orchard:

“The ancient orchard that gives the play its name yields its greatest rents by being cut down to make way for holiday villas – which is to say through its own absolute destruction and the destruction of the way of life that it once sustained.”

It is hard for elites to break out of this cycle of overwork, as long hours often is one of the reasons used to justify the (extremely) high pay of those at the top:

“As a dean of Stanford Law School recently observed in a letter to graduates, elite lawyers are caught in an intensifying ratchet: higher salaries require more billable hours to support them, longer hours require higher yet salaries to justify them, and each increase generates another in a seemingly endless cycle. Whose interests does this serve? He lamented. Does anyone actually want it?”

Goldman Sachs has renamed its personnal department “Human Capital Management” – the irony is not lost that the human labor itself today is one of the most exploited forms of capital:

“Unlike land or factories, human capital can produce income – at least using current technologies – only by being mixed with its owners’ own contemporaneous labor.”

While elites are stuck in compulsive overwork, the middle class are idled. Note that the middle class are not idle by active choice, as in “reluctant to work”. Rather, they are idled as a passive outcome, as in “denied opportunities to work.” Daniel attributes this to “technological transformation” that “shift(s) the center of production away from mid-skilled and toward super-skilled labor”.

As an example, Daniel says the middle-tier manager has gradually faded out from the labor market, replaced by a much smaller number of top executives (the overworked elite class with higher pay) and a large number of lower-end workers (the squeezed middle class with lower pay):

“The managerial control stripped away from production workers and middle managers has been concentrated in a narrow cadre of elite executives, who are separated from production workers by differences of kind rather than degree. The technologies that underwrite such concentrated managerial power – not just the information systems that monitor organizations and gather & manipulate data, but also the ideas and analytic frameworks employed to make sense of the data – are enormously complex. Only intensively trained managers can possibly acquire the sophistication needed.”

The result is the labor market is divided into “glossy jobs” of the elites vs. “gloomy jobs” of the middle class. Glossy refers to jobs whose ” outer shine masks inner distress”, whereas gloomy refers to jobs that “offer neither immediate reward nor hope for promotion.”

The product of meritocracy: Nativism & Populism in the middle class

Daniel argues meritocracy is the culprit behind nativism. Take white privilege as an example, he thinks the mere idea of white privilege itself irritates whites out of the elite class, because “they’ve never experienced it on a level that they understand. You hear privilege and you think money and opportunity and they don’t have it.”

“The meritocratic suggestion that a white man who cannot get ahead must be in some way deficient (i.e., lack of merit) stokes this anger…and the meritocratic fixation on diversity and inclusion channels the anger into nativist, sexist identity politics.”

Nativism allows the “native” group to blame all their problems on the “foreign” group. This finger-pointing on “aliens” is a mask for the insecurity of “natives” – sense of guilt even – that they themselves are the reason to blame: they are not good enough, they do not have enough merits, and hence they are behind where they would like to be in this (supposedly) “meritocratic” system. The “natives” seem to be on guard against the “aliens”, but what they are really pushing back against is their own sense of inferiority.

Daniel goes on to argue meritocracy is also at the root of populism: “a deep and pervasive mistrust of expertise and institutions.”

“Class resentments in America aim at the professional classes rather than at the entrepreneurial or even hereditary super-rich: not at oligarchs but rather at the doctors, bankers, lawyers, and scientists that working and middle-class Americans feel…’are more educated’ and ‘are often looking down on them.'”

Daniel makes the interesting comparison of Obama vs. Trump: Obama (and also Hillary Clinton) as “a superordinate product of elite production”, i.e., someone who rose and triumphed in meritocracy, and Trump as “a ‘blue-collar billionaire'” who rejects the meritocratic elites – the group that Obama & Clinton are both members of.

“Trumpism – and Trump’s own rise – exposes the incumbent elite’s meritocratic contempt for ordinary citizens and its own disenchanted weakness…When Hillary Clinton called half of Trump’s supporters a ‘basket of deplorables,’ she said aloud what the broad elite, regardless of party, had long thought in private. Indeed, Trump’s rise not only reconfirmed but redoubled the condescension that elites feel toward the Americans whom meritocracy excludes.“

The philosopher’s angle: Meritocracy and individual rights

According to philosopher Ayn Rand, the fundamental right of the individual, which is the pre-requisite & root of all other rights, is one’s right to his own life:

“There is only one fundamental right (all the others are its consequences or corollaries): a man’s right to his own life…which means: the freedom to take all the actions required by the nature of a rational being for the support, the furtherance, the fulfillment and the enjoyment of his own life. Such is the meaning of the right to life, liberty and the pursuit of happiness.”

By Rand’s definition, in the meritocratic system we live in today, neither the middle class nor the elite class have fully realized the fundamental right to one’s own life – neither is free to pursue their happiness. The curse of the meritocratic competition – starting from education all the way throughout one’s professional life – enslaves the poor & the rich alike: the former locked in their class with little hope of upward social mobility, the latter willingly enslaving themselves in work with brutal hours that they derive little pleasure from.

“A worker can quit his job. A slave cannot.” This is the curse fallen on the elites, who deceive themselves into believing they owe it to their expensive education to hold high-paying jobs with long hours, even those that they have little interest in.

“Man cannot be forced to devote his life to the happiness of another man nor of any number of other men.” This is the curse fallen on the middle class, who see themselves as producing for the consumption of the elites, whereas not moving up the social ladder themselves.

The collective illusion: Why it’s hard to critique meritocracy

Although the middle class and the elite class alike are harmed by meritocracy, both groups blame each other rather than critiquing the meritocratic system itself:

“Fragile elites disdain middle-class habits and values as a defense mechanism to ward off self-doubt. Meritocrats lionize achievement, or even just distinction, and disparage ordinariness as a bulwark against rising insecurity. They cling to any attitudes and practices – ranging from the absurd (food snobbery) to the callous (corporate rightsizing) – that might confirm their merit and validate their advantage, to others and, above all, to themselves.”

It leads one to wonder: why have we heard so little critique of the meritocratic system itself? Here is Daniel’s explanation:

“Mankiw sums this up when he observes, ‘When people can see with their own eyes that a talented person made a great fortune fair and square, they tend not to resent it.‘”
* * *
“The meritocratic transformation entails, bluntly put, that equality’s champions must justify redistribution that takes from a more industrious elite in order to give to a less industrious middle class. This makes meritocratic inequality difficult to resist.”

The success of a few in the meritocratic system has been used as the poster child to justify the merit of the system itself. The real danger of meritocracy lies not in it being unequal, but in it being justly unequal. It is white-washed to such an extent that those enslaved by meritocracy believe the way out is via the meritocratic system itself – the middle class believe in realizing the “American dream” via “meritocratic education” despite not even competing in the same arena as the elites; the elites cling to their high-paying jobs attained via “meritocratic job selection” despite physical fatigue and emotional voidness for work they feel little attachment to.

We are blindfolded, and yet we believe the way to see is to put more blinds over our eyes. Such is the irony. Such is the power of the meritocratic illusion – it not only makes us not see, it makes us refuse to see. This has to be the most ingenious form of slavery.

The way out: How should we fix the problems?

Daniel suggests we should go back to tackle meritocracy at its two major forms of manifestation, i.e., education & jobs.

For education, he suggests: ” Private schools and universities should lose their tax-exempt status unless at least half of their students come from families in the bottom two-thirds of the income distribution. And public subsidies should encourage schools to meet this requirement by expanding enrollment.”

For the job market, he suggests: “favoring goods and services produced by workers who do not have elaborate training or fancy degrees. For example, the health-care system should emphasize public health, preventive care, and other measures that can be overseen primarily by nurse practitioners, rather than high-tech treatments that require specialist doctors.”

As Daniel admits, change will not come easy: “Any victory will be long-fought and hard-won.” The key first step is acknowledging the problems of meritocracy, and the need of a united force to tackle them. I leave you with the last sentence from the book:

To update an old slogan: the workers of the world—now both middle-class and superordinate—should unite. They have nothing to lose but their chains, and a whole world to win.

Daniel Markovits

How Strangers Confused Spies and Diplomats (Reading “Talking to Strangers” by Malcolm Gladwell)

Malcolm Gladwell is back in town with a new book this month: Talking to Strangers. Great read – insightful & crisp like Gladwell’s earlier works. Never dry, sometimes actionable, frequently inspiring. Full of specific stories & research, a walking example of Gladwell’s belief: “Most interesting people talk about things with a great deal of specificity.“

For podcast lovers: Oprah Winfrey interviewed Gladwell about this book in the latest episode of Super Soul Sunday. A nice intro into the book.

From Neighbors to Strangers: Change in Interactions

Setting up the context in the opening chapter, Malcolm talks about how we interact with others have changed:

“Throughout the majority of human history, encounters – hostile or otherwise – were rarely between strangers. The people you met and fought often believed in the same God as you, built their buildings and organized their cities in the same way you did, fought their wars with the same weapons according to the same rules.“

Our ancestors mostly interacted with “neighbors”, as in people who lived in close proximity and had a common base for communication – including a common language & common cultural norms. This “common ground” reduced the cost of communication, making it very unlikely that things were “lost in translation” – both literally & metaphorically.

In contrast:

“Today we are now thrown into contact all the time with people whose assumptions, perspectives, and backgrounds are different from our own…struggling to understand each other.”

Today, we live in an Era of Strangers – people whose beliefs, upbringings & habits that are drastically different from our own. Yet, we could be terrible at times in understanding these differences. As Malcolm put it, the book “Talking to Strangers is about why we are so bad at that act of translation.”

Let’s dig in to look at key takeaways from the book.

Two Puzzles We Got from Spies & Diplomats

Fidel Castro released a documentary on Cuban national television titled The CIA’s War Against Cuba:

“Cuban intelligence, it turned out, had filmed and recorded everything the CIA had been doing in their country for at least ten years – as if they were creating a reality show…On the screen, identified by name, were CIA officers supposedly under deep cover…The most sophisticated intelligence service in the world had been played for a fool.”

The Cuban government had, in effect, converted almost all of CIA agents in Cuba into their agents, and fed fake information back to CIA for years. Years!

Malcolm says the CIA’s spectacular failure brought up Puzzle #1: “Why can’t we tell when the stranger in front of us is lying to our face?“ Why did the CIA – with the world’s top minds trained in espionage – failed to realize their agents lied to them for years?

Similar misjudgments happened on the other side of the world, in Britain. Before World War II broke out:

“(Then UK Prime Minister) Chamberlain’s negotiations with Hitler are widely regarded as one of the great follies of the Second World War. Chamberlain fell under Hitler’s spell. He was outmaneuvered at the bargaining table. He misread Hitler’s intentions.”

Others in Britain saw through Hitler – Winston Churchill was one of the people who “never believed for a moment that Hitler was anything more than a duplicitous thug.”

What’s interesting, though, is although Chamberlain spent hours with Hitler in person, Churchill only read about Hitler on paper. “The people who were right about Hitler were those who knew least about him personally.” Here comes Puzzle #2: “How is it that meeting a stranger can sometimes make us worse at making sense of that person than not meeting them?“

Even trained spies & diplomats could get it all wrong when it comes to strangers – just imagine how complicated this whole thing is:

“We have people struggling with their first impressions of a stranger. We have people struggling when they have months to understand a stranger. We have people struggling when they meet with someone only once, and people struggling when they return to the stranger again and again. They struggle with assessing a stranger’s honesty. They struggle with a stranger’s character. They struggle with a stranger’s intent.”
* * *
“It’s a mess.”

Talking to strangers is a mess indeed. Below are some tips that may provide some guidance.

“Default to Truth” is A Mental Shortcut that Works Most of the Time, but Trips Us Over at Unexpected Times

Psychologist Tim Levine did an experiment: he asked participants to watch videos of students talking, and try to spot liars among them. The result:

“We’re much better than chance (>>50%) at correctly identifying the students who are telling the truth. But we’re much worse than chance (<<50%) at correctly identifying the students who are lying. We go through all those videos, and we guess – ‘true, true, true’ – which means we get most of the truthful interviews right, and most of the liars wrong.”

Malcolm calls this “default to truth: our operating assumption is that the people we are dealing with are honest.” More importantly, Levine finds “we stop believing only when our doubts and misgivings rise to the point where we can no longer explain them away”. In other words, for us to switch off the default-truth mode, we not only require some doubt – we require enough doubt, unshakable doubt, undeniable doubt that it would take an insane person to not change his or her opinion.

Borrowing words from the legal principle of “innocent until proven guilty” here, we all practice the mental shortcut of “trust until proven a lie” – and this burden of proof has an extremely high threshold. We require evidence to go way, way, way beyond reasonable doubt.

As Malcolm summarizes it:

“That is Levine’s point. You believe someone not because you have no doubts about them. Belief is not the absence of doubt. You believe someone because you don’t have enough doubts about them.“
* * *
“Just think about how many times you have criticized someone else, in hindsight, for their failure to spot a liar. ‘You should have known. There were all kinds of red flags. You had doubts.’ Levine would say that’s the wrong way to think about the problem. The right question is: were there enough red flags to push you over the threshold of belief? If there weren’t, then by defaulting to truth you were only being human…doubts trigger disbelief only when you can’t explain them away.”

Our mental shortcut of “default to truth” is not completely useless – to the contrary, it is an evolutionary toolkit that gives us “efficient communication and social coordination” – at the cost of “an occasional lie”:

“Lies are rare…it doesn’t matter so much that we are terrible at detecting lies in real life. Under the circumstances, in fact, defaulting to truth makes logical sense. If the person behind the counter at the coffee shop says your total with tax is $6.74, you can do the math yourself to double-check their calculations, holding up the line and wasting 30 seconds of your time. Or you can simply assume the salesperson is telling you the truth, because on balance most people do tell the truth.”

Every day, we make countless decisions about whether or not to trust someone. Our default decision is to opt for the higher-probability scenario, i.e., the other side is telling the truth. In a handful of scenarios, we misjudge and pay for misplaced belief in a liar.

But overall, the total cost we pay is lower than the reverse “default to lie” position – imagine aggressively fact checking & analyzing every word others say, every action others take. It would be impossible to go on with life without becoming schizophrenic!

“Default to truth biases us in favor of the mostly likely interpretation.”

Related reading: A case in point of when “default to truth” goes wrong is the story of the scandal of Theranos – a company that made repeated lies that tripped over some of the world’s best investors & experts, who refused to change their belief in the company despite red flags. I highly recommend the investigative journalism into this: Bad Blood. Page-turner. Amazing story about ethics, business, and the human mind.

What the TV Show “Friends” Got Wrong: Transparency of Feelings is Rarer than We Think

For those who watched Friends, think about this: “it is almost impossible to get confused (when watching the show)…you can probably follow along even if you turn off the sound.” Why is this?

Malcolm cites research done via the Facial Action Coding System (FACS), a scoring system for facial expressions:

“FACS analysis tells us that the actors in ‘Friends’ make sure that every emotion their character is supposed to feel in their heart is expressed, perfectly, on their face…the facial displays of the actors are what carry the plot. The actors’ performances in Friends are transparent.”

Malcolm defines “transparency” as “the idea that people’s behavior and demeanor – the way they represent themselves on the outside – provides an authentic and reliable window into the way they feel on the inside.”

I would define transparency as an idea about consistency: “transparency” = the facial expression someone displays is consistent with what the majority of people would display, if they felt the same feelings. Borrowing the terminology “group-think”, perhaps this could be called “group-face”, i.e., have facial displays that the majority of your group would put on if put in the same shoes.

For example, a person who feels happy and wears a wide grin is being ‘transparent’, whereas the same person would be considered ‘not transparent’ if he frowns instead. Friends is a TV show of high transparency.

Fans of Friends, beware – the transparency you see in the show is rarely seen in practice!

“Transparency is a myth – an idea we’ve picked up from watching too much television and reading too many novels where the hero’s ‘jaw dropped with astonishment’ or ‘eyes went wide with surprise.'”

German psychologists Schutzwohl and Reisenzein carried out an experiment – they created a scenario that would surprise participants, who were later asked to describe their facial expressions. Almost all of the participants “were convinced that surprise was written all over their faces.”

But it was not:

“In only 5% of the cases did they (researchers) find wide eyes, shooting eyebrows and dropped jaws. In 17% of the cases they found two of those expressions. In the rest they found some combination of nothing, a little something, and things – such as knitted eyebrows – that you wouldn’t necessarily associate with surprise at all.”

The researchers concluded “participants in all conditions grossly overestimated their surprise expressivity…[t]hey inferred their likely facial expressions to the surprising event from…folk-psychological beliefs about emotion-face associations.”

So the next time you think you have “read” someone from their facial expressions, think again. People are less transparent than you think.

Related TV show: Lie To Me is a US TV series about solving crimes analyzing micro-expressions, i.e., voluntary & involuntary facial expressions which happen so fast that they are not captured by the untrained naked eye. The show’s story-line rests on the premise that certain micro-expressions may be involuntary and universal across cultures, a helpful tool for investigators to decipher the real feelings that criminals are trying to mask. Consider it as an alternative to your regular lie detector. There is academic research into micro-expressions too, though I have not looked at it in-depth.

What Suicide & Criminal Behaviors Have in Common: Both are Coupling Behaviors

In 1962, gas suicide was the #1 form of suicide in England, accounting for over 40% of the cases. By the 1970s, town gas throughout the country was replaced with natural gas that contained no carbon monoxide, that would give you “a mild headache and a crick in your neck” at the worst, but nowhere near lethal.

“So here is the question: once the number-one form of suicide (town gas) in England became a physiological impossibility, did the people who wanted to kill themselves switch to other methods? Or did the people who would have put their heads in ovens now not commit suicide at all?”

If you think people will go for alternative forms of suicide, then you believe in displacement, which “assumes that when people think of doing something as serious as committing suicide, they are very hard to stop.” If you think suicides will drop once the top form of suicide becomes impossible, then you believe in coupling: “the idea that behaviors are linked to very specific circumstances and conditions.” Statistics suggest suicide and crimes are both coupling behaviors tied to specific contexts.

For example, after a suicide barrier was installed on the Golden Gate Bridge in San Francisco, a survey followed up on 515 participants who once attempted to jump from the bridge – only 25 of them (<5%) tried to kill themselves in other ways.

Similarly, crime is also shown to be a coupling behavior. Studies in different cities have converged on the same result: “Crime in every city was concentrated in a tiny number of street segments.” This is referred to as the Law of Crime Concentration. Malcolm thinks the lesson for takeaway is:

“When you confront the stranger, you have to ask yourself where and when you’re confronting the stranger – because those two things powerfully influence your interpretation of who the stranger is.”

Don’t Fall Into the “Illusion of Asymmetric Insight”

Let’s play a game of word completion. Suppose I showed you “G L _ _”, which word would you fill it with?

Now suppose I handed you 3 words that a participant has wrote: WINNER, SCORE, GOAL, what could you infer about this participant’s personality? In one response, an interviewee wrote: “It seems this individual has a generally positive outlook toward the things he endeavors…indicate some sort of competitiveness.”

Now let’s flip the game on its head – suppose I asked you to complete the words, and then asked you what these words you completed reveal about your personality. Guess what? The majority of participants in this game refused to”agree with these word-stem completions” as a measure of their own personality.

This is what the psychologist Pronin calls the Illusion of Asymmetric Insight:

“The (biased) conviction that we know others better than they know us – and that we may have insights about them they lack (but not vice versa) – leads us to talk when we would do well to listen and to be less patient than we ought to be when others express the conviction that they are the ones who are being misunderstood or judged unfairly.”

As Malcolm phrases it, it is easy to blame it on the stranger: “We think we can easily see into the hearts of others based on the flimsiest of clues. We jump at the chance to judge strangers. We would never do that to ourselves, of course. We are nuanced and complex and enigmatic. But the stranger is easy. If I can convince you of one thing in this book, let is be this: Strangers are not easy.“

If I could leave you with only one takeaway, then let it be this: strangers are not easy. What is easy to do is to blame the strangers for any meaning lost in translation – without assessing our own biases. Hopefully this book has given all of us some actionable tips on “talking to strangers”. Once again, I highly recommend reading the whole book from cover to cover – I hope you will find it to be a page-turner as I did.

What does it mean to be “Educated”?

Education must be conceived as a continuing reconstruction of experience…the process and the goal of education are one and the same thing.

John Dewey

Education is a continuing reconstruction of experience – at least according to philosopher John Dewey. John’s quote was splattered across the first page of Tara Westover’s memoir Educated. This book is so amazing that I am at a loss of words to describe its impact – parts of it hit me like a truck, while parts of it softened me like a lullaby; parts of it sent chills down my spine, while parts of it swelled warmth in my chest.

If I could only recommend one book to read this year, Educated would be my pick. In the words of Bill Gates, this is “the kind of book everyone will enjoy. It’s even better than you’ve heard.”

Tara’s book is aptly named and poses this grand question, among others: what does it mean to be educated? What makes one deserving of this word?

Educated = Claiming Selfhood. Unapologetically.

You could call this selfhood many things. Transformation. Metamorphosis. Falsity. Betrayal.
* * *
I call it an education.

Tara Westover

“I am not a good daughter. I am a traitor, a wolf among sheep; there is something different about me (from my family) and that difference is not good. I want to bellow, to weep into my father’s knees and promise never to do it again.”

Traitor. That was how Tara Westover felt when her father & family wrestled for control over her life, and she attempted to fight back.

That was how Tara felt after she rushed her injured brother to the hospital instead of to her mom’s herbal therapy. That was how Tara felt for simply thinking about going to school instead of growing up into her “rightful” place as a stay-at-home mom & wife. That was how Tara felt for telling her brother to stop physically abusing her and throwing her onto the floor. That was how Tara felt for wanting to try on jeans & fitting crops, clothes that she were told to belong to “whores”.

There were moments where Tara had doubts about what she was taught by her parents:

“Sometimes I wondered if perhaps school was less evil than Dad thought, because (my brother) Tyler was the least evil person I knew, and he loved school – loved it more, it seemed, than he loved us.”

But these seeds of doubt & curiosity rarely blossomed into the fruits of action. These prescient signs of Tara’s claim to her selfhood were crushed time and time again in a vicious loop:

“Mother had always said we could go to school if we wanted. We just had to ask Dad, she said. Then we could go.
* * *
But I didn’t ask. There was something in the hard line of my father’s face, in the quiet sigh of supplication he made every morning before he began family prayer, that made me think my curiosity was an obscenity, an affront to all he’d sacrificed to raise me.”

Naval Ravikant said: “If you want to see who rules over you, see who you are not allowed to criticize.” I would take that one step further – if you want to see who has the greatest power over you, see who you do not allow yourself to even question.

Such power at its most forceful throws its slaves into this endless cycle of rejecting one’s claim to selfhood, over and over again. Such power at its most damning whispers the hyptonizing words “to simply be is to be evil,” until these words are tatooed into the victim’s soul. One feels its chilling effect from Tara’s words: “I believed then – and part of me will always believe – that my father’s words ought to be my own.”

The most lethal poison is one that you drink as if your life depended on it; the most deceitful mask is one that you wear as if it were part of your natural skin. Eventually, you are no longer able to discern between what is your voice vs. what is the voice from others – they blend into one, and you take the latter as your own. You have rejected selfhood. You have given up believing in selfhood.

The dictionary definition of “selfhood” is “the quality that constitutes one’s individuality; the state of having an individual identity”. Interestingly, according to Google Books, the frequency that the word “selfhood” appears in English works have been on the rise in the past two centuries. This upward trend coincides with the rise of individualism and freedom of expression:

I argue what sits at the core, as the prerequisite, of being “educated” is to claim our selfhood. To claim our selfhood unapologetically. To question others’ claim over our selfhood critically. Becoming educated starts with saying: “I recognize and honor my innate right to define and continuously redefine my self.” Selfhood is where education starts. Selfhood is where identity starts. Selfhood is where living as a free, breathing being starts. As Oscar Wilde said, “Be yourself. Everyone else is taken.”

Tara remembers vividly the defining moment where her brother, Tyler, stood up for his selfhood:

“‘College is for extra school for people too dumb to learn the first time around,’ Dad said (when Tyler wanted to go to college). Tyler stared at the floor, his face tense. Then his shoulders dropped, his face relaxed and he looked up; it seemed to me that he’d stepped out of himself. His eyes were soft, pleasant. I couldn’t see him in there at all.”
* * *
“I will always remember my father in this moment, the potency of him, and the desperation. He leans forward, jaw set, eyes narrow, searching his son’s face for some sign of agreement, some crease of shared conviction. He doesn’t find it.”

Selfhood starts when we no longer copy the “shared conviction” of the group. When we “step out of ourselves” to inspect who we are. When develop convictions that we could truly call our own.

“Everything I had worked for, all my years of study, had been to purchase for myself this one privilege: to see and experience more truths than those given to me by my father, and to use those truths to construct my own mind…If I yielded now, I would lose more than an argument. I would lose custody of my own mind. This was the price I was being asked to pay, I understood that now.
* * *
What my father wanted to cast from me wasn’t a demon: it was me.“

Educated = (Re-)Creating the Structure of Life. Unconstrained.

You are like a river. You go through life taking the path of least resistance…The underlying structure of your life determines the path of least resistance.
* * *
Structure determines behavior.

Robert Fritz, The Path of Least Resistance

The shape of water is defined by the structure it is in

“‘It’s time to go, Tara,’ Tyler said.
‘The longer you stay, the less likely you will ever leave.‘
‘You think I need to leave?’
* * *
Tyler didn’t blink, didn’t hesitate.
‘I think this is the worst possible place for you.’ He’d spoken softly, but it felt as though he’d shouted the words. ‘There’s a world out there, Tara…And it will look a lot different once Dad is no longer whispering his view of it in your ear.“

Leave. Leave home. This was the advice Tara’s brother Tyler gave her, before he himself walked away from home, and never looked back.What Tyler was really telling Tara was this: change the structure of your life. As long as you are stuck in the same structure, you will never know what the world is like out there. Worse still, you will never be able to imagine what life on the other side is like.

Tara’s recalls her experience taming a wild horse:

“In the space of a moment, he had accepted our claim to ride him, to his being ridden. He had accepted the world as it was, in which he was an owned thing. He had never been feral, so he could not hear the maddening call of that other world, on the mountain, in which he could not be owned, could not be ridden.“

People commonly believe that if they change their behavior, they can change the structures in their lives. In fact, just the opposite is true.
* * *
If you are in a structure that leads to oscillation, no solution
will help. This is because these psychological solutions do not
address the structure, but rather the behavior that comes from
the structure.

Robert Fritz, The Path of Least Resistance

In the memoir, Tara wrote about native Apache women, whose fate were dictatated by the customs & rules set in their community:

“I thought about the Apache women. Like the sandstone altar on which they had died, the shape of their lives had been determined years before…Decided. Choices, numberless as grains of sand, had layered and compressed, coalescing into sediment, then into rock, until all was set in stone.“

Just like the Apache women, the shape of Tara’s life has been determined years before she was born. Before she was born, her parents had decided not only what she would become, but also what she would believe. She would believe schools and medicine were evil. She would believe women should not work. She would believe giving birth at home with a “midwife” without any formal training or certification was safer than giving birth in a hospital. She would believe the “non-believers” – those who held opposing beliefs – were out here to get her. She would believe the Feds could come with their guns to hunt her family down anytime.

As long as Tara was stuck in this structure, she would never have a shot of truly breaking free:

“I could have my mother’s love, but there were terms…that I trade my reality for theirs, that I take my own understanding and bury it, leave it to rot in the earth.”
* * *
“All I had to do was swap my memories for theirs, and I could have my family.”

Leaving her birth family was an educated decision for Tara. It is hard to imagine how she felt as she wrote these words: “You can love someone and still choose to say goodbye to them…You can miss a person every day, and still be glad that they are no longer in your life.”

It takes education and courage to re-create the structure of life, such that the path of least resistance takes you to where you want to go, such that you re-shape the cup so the water morphs into the shape you have in mind.

This could mean saying goodbye to people you love and / or people who love you:

“We think love is noble, and in some ways, it is. But in some ways, it isn’t. Love is just love. And sometimes people do terrible things because of it.“
* * *
“It’s strange how you give the people you love so much power over you…It’s very difficult to continue to believe in yourself and that you’re a good person when the people who know you best don’t.”

Perhaps part of us would always miss the old structure that we broke away from, just as a part of Tara would always miss her family – or rather, the parents she wish she had:

“…(I thought of) my father as I wished he were, some longed-for defender, some fanciful champion, one who wouldn’t fling me into a storm, and who, if I was hurt, would make me whole.”

But to be educated means the ability to detect the unsolvable conflict between the present structure & your future self. To be educated means the audacity to craft a new structure where your true self could blossom. After the initial ‘cultural shock’, you will eventually find peace:

“I shed my guilt when I accepted my decision on its own terms, without endlessly prosecuting old grievances…I learned to accept my decision for my own sake.”

Believe it: you will eventually find your inner peace when you let your inner self blossom.

Education is about Making a Person

I leave you with one last quote from Tara:

An education is not so much about making a living as making a person.

Tara Westover

Educated means claiming selfhood – your right to define yourself as a person. Educated means crafting structure – the birth-bed to let your selfhood flourish.

Borrowing words from the rationalist school of thought that it’s not about being more right but being “less wrong”, the making of a person is not about becoming more perfect but “less flawed” and “less plastic”.

Circling back to John Dewey’s quote at the very top: education is the continuing reconstruction of experience. I wish we all continue smoothly along the journey of education, of bringing us closer to the person we want and deserve to be.

[Big Ideas – Special] Understanding Markets via “Narrative Economics”

The secret of effective market game-playing is to recognize that the market game hinges on the Narrative, on the strength of the public statements that create Common Knowledge.

Epsilon Theory Manifesto

Nobel-winning economist Robert Shiller recently published Narrative Economics, a book on “How Stories Go Viral and Drive Major Economic Events“. Shiller gave a talk at LSE on the big ideas (video, audio, related 2017 paper).

Context: This article is part of the Big Ideas series, where I synthesize takeaways from the world’s best experts in multiple disciplines. This article is a special in the series, because unlike other articles that are synthesized from Discover magazine expert interviews, this piece is largely inspired by a public lecture.

What is a Narrative?

Let’s start with definitions. According to Shiller:

• Narrative = a telling of a story that attaches significance, meaning or emotions to it;
• Story = a chronology of events.

What is Narrative Economics?

Shiller makes a key distinction between narrative economics as defined in the dictionary vs. defined by himself. The textbook definition of narrative economics is “economics research that takes the form of telling a narrative about economic events”.

For Shiller, narrative economics should have a narrower focus, i.e., only investigating popular economics narratives that “went viral”, “changed things” and “became contagious”.

Shiller thinks economics narratives are powerful in affecting (& shaping) economic decisions. He identifies 9 perennial economics narratives:

1. Panic vs. confidence narratives – e.g., the Big Depression is a panic narrative;
   
2. Frugality vs. conspicuous consumption – e.g., Trump’s book “Think Like a Billionaire”;
   
3. Monetary standards – e.g., the Gold Standard vs. Bimetallism debate;
   
4. Technical unemployment, i.e., labor-saving machines replace many jobs;
5. Automation & AI replace most jobs;
   
6. Real estate booms & busts;
7. Stock market bubbles;
   
8. Boycotts, profiteers & evil business;
9. The wage-price spiral & evil labor unions.

Broadly speaking, the 9 narratives above focus on the macro economics momentum / “culture” (1-3), employment (4-5), investment (6-7) or actors in power (8-9).

Shiller argues that data sources are at the root of economics evolutions. He believes the recent “digitization of search” is and will bring shifts to narratives. Moreover, Shiller claims that big events occur often not because of a single narrative, but because of a “confluence of narratives“, i.e., as a result of the chemical reaction of multiple narratives.

With an interesting twist, the word “narrative” appears less frequently academic articles in economics & finance compared with other subjects – see this analysis of JSTOR articles below:

Studying Narrative Economics via the Virality Model of Epidemics

If we think of a narrative as a disease, then we could study its spread by borrowing patterns from research on epidemics. In other words, we could leverage research on how viruses “go viral”, and try to figure out how narratives get popular.

The Kermack-McKendrick (1927) mathematical theory of disease epidemics is a breakthrough in medicine, because it “gave a realistic framework for understanding the all-important dynamics of infectious diseases” in the words of Shiller.

The Kermack-McKendrick model divides the population into three groups: susceptibles, infectives, and recovered. Importantly, the model suggests the curve of the number of infectives to take a “humpback” shape, i.e., rising sharply before declining at a similarly fast speed:

We could see similar “humpback” shaped curves in data that could serve as proxy measurements for how popular an economics narrative is.

Here’s an example on how frequent the phrase “stock market crash” appears in news & newspapers:

Here’s another example on how frequent the phrase “Great Depression” appears in news & newspapers:

The Future of Narrative Economics

Shiller is hopeful that ” the advent of big data and of better algorithms of semantic search might bring more credibility to the field”.

Meanwhile, narrative economics faces challenges, including:

• On data collection, we need to move beyond “passive collection of others’ words, towards experiments that reveal meaning and psychological significance”, e.g., via focus groups or social media – though the proper design & implementation of such experiments is not easy;
  
• Dealing with the overlap & “chemical reactions” of multiple overlapping narratives is difficult;
  
• Causality is tricky. As Shiller says, one challenge is in “distinguishing between narratives that are associated with economic behavior just because they are reporting on the behavior, and narratives that create changes in economic behavior.”

Nevertheless, the challenges make the field more interesting. I am particularly interested in predicting which narratives will gain momentum. Perhaps the narrative machine will serve, to some extend, as a crystal ball that offers a narrow glimpse into the future.