Mental Model Master Flashcards
Familiarize yourself with this comprehensive list of Mental Models.
Inversion
“Otherwise known as thinking through a situation in reverse or thinking “backwards,” inversion is a problem-solving technique. Often by considering what we want to avoid rather than what we want to get, we come up with better solutions. Inversion works not just in mathematics but in nearly every area of life. As the saying goes, “Just tell me where I’m going to die so I can never go there.” - Shane Parrish
“By imagining the worst case scenario ahead of time, they could overcome their fears of negative experiences and make better plans to prevent them. While most people were focused on how they could achieve success, the Stoics also considered how they would manage failure. This way of thinking, in which you consider the opposite of what you want, is known as inversion.Inversion is a powerful thinking tool because it puts a spotlight on errors and roadblocks that are not obvious at first glance. “ - James Clear
“Many problems resist being solved “from the front.” They demand that you solve them backwards or from an unintuitive angle. This is the art of inversion. Sometimes the question should not be: “What features do we build?” Rather, it should be: “What features would destroy this product?” Once you know which features are going to run your product into the ground, you can achieve a simple win just by not doing those. For PMs, the label of “CEO of the product” can sometimes tempt them into over-relying on their instincts when it comes to building product. However, it is much easier to avoid making mistakes than it is to be perfect all the time. Inversion is also a powerful way to break out of the repetitive thought-loops that can hurt your team’s ability to learn. We can easily fall into “retro-fatigue” asking questions like, “How can we innovate more?” or “Why did that project not go well?” over and over again. Our brains go on autopilot and start giving similar-sounding answers. That is why asking questions like “What can we do to innovate less?” can be such a powerful rhetorical technique. It provides you with a slightly different point of view—but one that is usually much more insightful.” - Hiten Shah
Arguing from First Principles
“A first principle is a basic, foundational, self-evident proposition or assumption that cannot be deduced from any other proposition or assumption.” (related: dimensionality reduction; orthogonality; “Reasonable minds can disagree” if underlying premises differ.)
Falsification / Confirmation Bias
“What a man wishes, he also believes. Similarly, what we believe is what we choose to see. This is commonly referred to as the confirmation bias. It is a deeply ingrained mental habit, both energy-conserving and comfortable, to look for confirmations of long-held wisdom rather than violations. Yet the scientific process – including hypothesis generation, blind testing when needed, and objective statistical rigor – is designed to root out precisely the opposite, which is why it works so well when followed.
The modern scientific enterprise operates under the principle of falsification: A method is termed scientific if it can be stated in such a way that a certain defined result would cause it to be proved false. Pseudo-knowledge and pseudo-science operate and propagate by being unfalsifiable – as with astrology, we are unable to prove them either correct or incorrect because the conditions under which they would be shown false are never stated.”- Shane Parrish
“The tendency to search for, interpret, favor, and recall information in a way that confirms one’s preexisting beliefs or hypotheses, while giving disproportionately less consideration to alternative possibilities.” (related: cognitive dissonance)” - Gabriel Weinberg
“It is the peculiar and perpetual error of the human understanding to be more moved and excited by affirmatives than by negatives.”?—?Francis Bacon
Circle of Competence
An idea introduced by Warren Buffett and Charles Munger in relation to investing: each individual tends to have an area or areas in which they really, truly know their stuff, their area of special competence. Areas not inside that circle are problematic because not only are we ignorant about them, but we may also be ignorant of our own ignorance. Thus, when we’re making decisions, it becomes important to define and attend to our special circle, so as to act accordingly.
The Principle of Parsimony (Occam’s Razor)
Named after the friar William of Ockham, Occam’s Razor is a heuristic by which we select among competing explanations. Ockham stated that we should prefer the simplest explanation with the least moving parts: it is easier to falsify (see: Falsification), easier to understand, and more likely, on average, to be correct. This principle is not an iron law but a tendency and a mindset: If all else is equal, it’s more likely that the simple solution suffices. Of course, we also keep in mind Einstein’s famous idea (even if apocryphal) that “an idea should be made as simple as possible, but no simpler.” - Shane Parrish
“Among competing hypotheses, the one with the fewest assumptions should be selected.” (related: conjunction fallacy, overfitting, “when you hear hoofbeats, think of horses not zebras.”) - Gabriel Weinberg
“Don’t concoct a complicated, extravagant theory if you’ve got a simpler one (containing fewer ingredients, fewer entities) that handles the phenomenon just as well. If exposure to extremely cold air can account for all the symptoms of frostbite, don’t postulate unobserved “snow germs” or “arctic microbes.” Kepler’s laws explain the orbits of the planets; we have no need to hypothesize pilots guiding the planets from control panels hidden under the surface.” - Daniel Dennett
Hanlon’s Razor
“Harder to trace in its origin, Hanlon’s Razor states that we should not attribute to malice that which is more easily explained by stupidity. In a complex world, this principle helps us avoid extreme paranoia and ideology, often very hard to escape from, by not generally assuming that bad results are the fault of a bad actor, although they can be. More likely, a mistake has been made.” - Shane Parrish
“Never attribute to malice that which is adequately explained by carelessness.” (related: fundamental attribution error — “ the tendency for people to place an undue emphasis on internal characteristics of the agent (character or intention), rather than external factors, in explaining another person’s behavior in a given situation.”) - Gabriel Weinberg
Second-Order Thinking
In all human systems and most complex systems, the second layer of effects often dwarfs the first layer, yet often goes unconsidered. In other words, we must consider that effects have effects. Second-order thinking is best illustrated by the idea of standing on your tiptoes at a parade: Once one person does it, everyone will do it in order to see, thus negating the first tiptoer. Now, however, the whole parade audience suffers on their toes rather than standing firmly on their whole feet.
The Map Is Not the Territory
The map of reality is not reality itself. If any map were to represent its actual territory with perfect fidelity, it would be the size of the territory itself. Thus, no need for a map! This model tells us that there will always be an imperfect relationship between reality and the models we use to represent and understand it. This imperfection is a necessity in order to simplify. It is all we can do to accept this and act accordingly.
Thought Experiments
A technique popularized by Einstein, the thought experiment is a way to logically carry out a test in one’s own head that would be very difficult or impossible to perform in real life. With the thought experiment as a tool, we can solve problems with intuition and logic that could not be demonstrated physically, as with Einstein imagining himself traveling on a beam of light in order to solve the problem of relativity. - Shane Parrish
“considers some hypothesis, theory, or principle for the purpose of thinking through its consequences.” (related: counterfactual thinking) - Gabriel Weinberg’
Mr. Market
Mr. Market was introduced by the investor Benjamin Graham in his seminal book The Intelligent Investor to represent the vicissitudes of the financial markets. As Graham explains, the markets are a bit like a moody neighbor, sometimes waking up happy and sometimes waking up sad – your job as an investor is to take advantage of him in his bad moods and sell to him in his good moods. This attitude is contrasted to an efficient-market hypothesis in which Mr. Market always wakes up in the middle of the bed, never feeling overly strong in either direction.
Probabilistic Thinking (See also: Numeracy/Bayesian Updating)
The unknowable human world is dominated by probabilistic outcomes, as distinguished from deterministic ones. Although we cannot predict the future with great certainty, we are wise to ascribe odds to more and less probable events. We do this every day unconsciously as we cross the street and ascribe low, yet not negligible, odds of being hit by a car.
Default Status
The USCB ecologist/economist Garrett Hardin once said that “The scientific mind is not closed: it is merely well-guarded by a conscientious and seldom sleeping gatekeeper.” The way it does that is with the concept of the default status: The “resting position” of common sense, whereby the burden of proof falls on assertions to the contrary. Given the problem of opportunity costs and limited time and energy, a default status is nearly always necessary to avoid wasting time. Examples include the laws of thermodynamics, the law of natural selection, and the incentive-caused bias.
Reductio ad Absurdum
The crowbar of rational inquiry, the great lever that enforces consistency, is reductio ad absurdum—literally, reduction (of the argument) to absurdity. You take the assertion or conjecture at issue and see if you can pry any contradictions (or just preposterous implications) out of it. If you can, that proposition has to be discarded or sent back to the shop for retooling.
Rapoport’s Rules
How to compose a successful critical commentary:
- You should attempt to re-express your target’s position so clearly, vividly, and fairly that your target says, “Thanks, I wish I’d thought of putting it that way.”
- You should list any points of agreement (especially if they are not matters of general or widespread agreement).
- You should mention anything you have learned from your target.
- Only then are you permitted to say so much as a word of rebuttal or criticism.
One immediate effect of following these rules is that your targets will be a receptive audience for your criticism: you have already shown that you understand their positions as well as they do, and have demonstrated good judgment (you agree with them on some important matters and have even been persuaded by something they said).
Sturgeon’s Law
“Sturgeon’s Law is usually put a little less decorously: Ninety percent of everything is crap. Ninety percent of experiments in molecular biology, 90 percent of poetry, 90 percent of philosophy books, 90 percent of peer-reviewed articles in mathematics—and so forth—is crap. Is that true? Well, maybe it’s an exaggeration, but let’s agree that there is a lot of mediocre work done in every field….”
“Now, in order not to waste your time and try our patience, make sure you concentrate on the best stuff you can find, the flagship examples extolled by the leaders of the field, the prizewinning entries, not the dregs.”
Occam’s Broom
“The process in which inconvenient facts are whisked under the rug by intellectually dishonest champions of one theory or another.”
Using Lay Audiences as Decoys
“In many fields—not just philosophy—there are controversies that seem never-ending and partly artifactual: people are talking past one another and not making the necessary effort to communicate effectively. When experts talk to experts, whether they are in the same discipline or not, they always err on the side of under-explaining. The reason is not far to seek: to overexplain something to a fellow expert is a very serious insult—“Do I have to spell it out for you?”—and nobody wants to insult a fellow expert.
Solution for this problem: Have all experts present their views to a small audience of curious nonexperts (here at Tufts I have the advantage of bright undergraduates) while the other experts listen in from the sidelines. They don’t have to eavesdrop; this isn’t a devious suggestion. On the contrary, everybody can and should be fully informed that the point of the exercise is to make it comfortable for participants to speak in terms that everybody will understand. By addressing their remarks to the undergraduates (the decoy audience), speakers need not worry at all about insulting the experts because they are not addressing the experts. (I suppose they might worry about insulting the undergraduates, but that’s another matter.) When all goes well, expert A explains the issues of the controversy to the undergraduates while expert B listens. At some point B’s face may light up. “So that’s what you’ve been trying to say! Now I get it.””
Jootsing
“Jootsing stands for “jumping out of the system.” This is an important tactic not just in science and philosophy, but also in the arts. Creativity, that ardently sought but only rarely found virtue, often is a heretofore unimagined violation of the rules of the system from which it springs. It might be the system of classical harmony in music, the rules for meter and rhyme in sonnets (or limericks, even), or the “canons” of taste or good form in some genre of art. Or it might be the assumptions and principles of some theory or research program. Being creative is not just a matter of casting about for something novel—anybody can do that, since novelty can be found in any random juxtaposition of stuff—but of making the novelty jump out of some system, a system that has become somewhat established, for good reasons.”
Three Species of Goulding: Rathering, Piling On, and the Gould Two-Step
Rathering is a way of sliding you swiftly and gently past a false dichotomy. The general form of a rathering is “It is not the case that blahblahblah, as orthodoxy would have you believe; it is rather that suchandsuchandsuch—which is radically different.” Some ratherings are just fine; you really must choose between the two alternatives on offer; in these cases, you are not being offered a false, but rather a genuine, inescapable dichotomy. But some ratherings are little more than sleight of hand, due to the fact that the word “rather” implies—without argument—that there is an important incompatibility between the claims flanking it.
The “Surely” Operator: A Mental Block
“When you’re reading or skimming argumentative essays, especially by philosophers, here is a quick trick that may save you much time and effort, especially in this age of simple searching by computer: look for “surely” in the document, and check each occurrence. Not always, not even most of the time, but often the word “surely” is as good as a blinking light locating a weak point in the argument, a warning label about a likely boom crutch. Why? Because it marks the very edge of what the author is actually sure about and hopes readers will also be sure about. (If the author were really sure all the readers would agree, it wouldn’t be worth mentioning.) “
Rhetorical Questions
Just as you should keep a sharp eye out for “surely,” you should develop a sensitivity for rhetorical questions in any argument or polemic. Why? Because, like the use of “surely,” they represent an author’s eagerness to take a short cut. A rhetorical question has a question mark at the end, but it is not meant to be answered. Whenever you see a rhetorical question, try—silently, to yourself—to give it
an unobvious answer.
What Is a Deepity?
A deepity is a proposition that seems both important and true—and profound—but that achieves this effect by being ambiguous. On one reading it is manifestly false, but it would be earth-shaking if it were true; on the other reading it is true but trivial. The unwary listener picks up the glimmer of truth from the second reading, and the devastating importance from the first reading, and thinks, Wow! That’s a deepity.
Example: Love is just a word.
“love” is an English word, but just a word, not a sentence, for example.
Scientific Method
“Systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses.” (related: reproducibility) - Gabriel Weinberg
“The scientific method is a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge. To be termed scientific, a method of inquiry is commonly based on empirical or measurable evidence subject to specific principles of reasoning.The Oxford Dictionaries Online defines the scientific method as “a method or procedure that has characterized natural science since the 17th century, consisting in systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses”. Experiments need to be designed to test hypotheses. Experiments are an important tool of the scientific method.” - Wikipedia (James Clear)
Proxy
“A variable that is not in itself directly relevant, but that serves in place of an unobservable or immeasurable variable. In order for a variable to be a good proxy, it must have a close correlation, not necessarily linear, with the variable of interest.” (related: revealed preference; Proxy War — “A conflict between two nations where neither country directly engages the other.”)
Selection Bias
“The selection of individuals, groups or data for analysis in such a way that proper randomization is not achieved, thereby ensuring that the sample obtained is not representative of the population intended to be analyzed.” (related: sampling bias)
Response Bias
“A wide range of cognitive biases that influence the responses of participants away from an accurate or truthful response.”
Observer Effect
“Changes that the act of observation will make on a phenomenon being observed.” (related: Schrödinger’s cat)
Systems Thinking
“By taking the overall system as well as its parts into account systems thinking is designed to avoid potentially contributing to further development of unintended consequences.” (related: causal loop diagrams; stock and flow; Le Chatelier’s principle, hysteresis — “the time-based dependence of a system’s output on present and past inputs.”; “Can’t see the forest for the trees.”)
Scenario Analysis
“A process of analyzing possible future events by considering alternative possible outcomes.” (related: “Skate to where the puck is going.”; black swan theory — “a metaphor that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight.”)
Normal Distribution
“A very common continuous probability distribution…Physical quantities that are expected to be the sum of many independent processes (such as measurement errors) often have distributions that are nearly normal.” (related: central limit theorem)
Sensitivity Analysis
“The study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be apportioned to different sources of uncertainty in its inputs.”
Cost-benefit Analysis
“A systematic approach to estimating the strengths and weaknesses of alternatives that satisfy transactions, activities or functional requirements for a business.” (related: net present value — “a measurement of the profitability of an undertaking that is calculated by subtracting the present values of cash outflows (including initial cost) from the present values of cash inflows over a period of time.”, discount rate)
Simulation
“The imitation of the operation of a real-world process or system over time.” (related: Queuing theory?— “the mathematical study of waiting lines, or queues.”)
Pareto Efficiency
“A state of allocation of resources in which it is impossible to make any one individual better off without making at least one individual worse off…A Pareto improvement is defined to be a change to a different allocation that makes at least one individual better off without making any other individual worse off, given a certain initial allocation of goods among a set of individuals.”
Permutations and Combinations
The mathematics of permutations and combinations leads us to understand the practical probabilities of the world around us, how things can be ordered, and how we should think about things.
Algebraic Equivalence
The introduction of algebra allowed us to demonstrate mathematically and abstractly that two seemingly different things could be the same. By manipulating symbols, we can demonstrate equivalence or inequivalence, the use of which led humanity to untold engineering and technical abilities. Knowing at least the basics of algebra can allow us to understand a variety of important results.
Randomness
Though the human brain has trouble comprehending it, much of the world is composed of random, non-sequential, non-ordered events. We are “fooled” by random effects when we attribute causality to things that are actually outside of our control. If we don’t course-correct for this fooled-by-randomness effect – our faulty sense of pattern-seeking – we will tend to see things as being more predictable than they are and act accordingly.
Stochastic Processes (Poisson, Markov, Random Walk)
A stochastic process is a random statistical process and encompasses a wide variety of processes in which the movement of an individual variable can be impossible to predict but can be thought through probabilistically. The wide variety of stochastic methods helps us describe systems of variables through probabilities without necessarily being able to determine the position of any individual variable over time. For example, it’s not possible to predict stock prices on a day-to-day basis, but we can describe the probability of various distributions of their movements over time. Obviously, it is much more likely that the stock market (a stochastic process) will be up or down 1% in a day than up or down 10%, even though we can’t predict what tomorrow will bring.
Compounding
It’s been said that Einstein called compounding a wonder of the world. He probably didn’t, but it is a wonder. Compounding is the process by which we add interest to a fixed sum, which then earns interest on the previous sum and the newly added interest, and then earns interest on that amount, and so on ad infinitum. It is an exponential effect, rather than a linear, or additive, effect. Money is not the only thing that compounds; ideas and relationships do as well. In tangible realms, compounding is always subject to physical limits and diminishing returns; intangibles can compound more freely. Compounding also leads to the time value of money, which underlies all of modern finance. - Shane Parrish
“Interest on interest. It is the result of reinvesting interest, rather than paying it out, so that interest in the next period is then earned on the principal sum plus previously-accumulated interest.” - Gabriel Weinberg
Multiplying by Zero
Any reasonably educated person knows that any number multiplied by zero, no matter how large the number, is still zero. This is true in human systems as well as mathematical ones. In some systems, a failure in one area can negate great effort in all other areas. As simple multiplication would show, fixing the “zero” often has a much greater effect than does trying to enlarge the other areas.
Churn
Insurance companies and subscription services are well aware of the concept of churn – every year, a certain number of customers are lost and must be replaced. Standing still is the equivalent of losing, as seen in the model called the “Red Queen Effect.” Churn is present in many business and human systems: A constant figure is periodically lost and must be replaced before any new figures are added over the top.
Law of Large Numbers
One of the fundamental underlying assumptions of probability is that as more instances of an event occur, the actual results will converge on the expected ones. For example, if I know that the average man is 5 feet 10 inches tall, I am far more likely to get an average of 5?10? by selecting 500 men at random than 5 men at random. The opposite of this model is the law of small numbers, which states that small samples can and should be looked at with great skepticism.
Bell Curve/Normal Distribution
The normal distribution is a statistical process that leads to the well-known graphical representation of a bell curve, with a meaningful central “average” and increasingly rare standard deviations from that average when correctly sampled. (The so-called “central limit” theorem.) Well-known examples include human height and weight, but it’s just as important to note that many common processes, especially in non-tangible systems like social systems, do not follow the normal distribution.
Power Laws
One of the most common processes that does not fit the normal distribution is that of a power law, whereby one quantity varies with another’s exponent rather than linearly. For example, the Richter scale describes the power of earthquakes on a power-law distribution scale: an 8 is 10x more destructive than a 7, and a 9 is 10x more destructive than an 8. The central limit theorem does not apply and there is thus no “average” earthquake. This is true of all power-law distributions. - Shane Parrish
“A functional relationship between two quantities, where a relative change in one quantity results in a proportional relative change in the other quantity, independent of the initial size of those quantities: one quantity varies as a power of another.” (related: Pareto distribution; Pareto principle — “for many events, roughly 80% of the effects come from 20% of the causes.”, diminishing returns, premature optimization, heavy-tailed distribution, fat-tailed distribution; long tail — “the portion of the distribution having a large number of occurrences far from the “head” or central part of the distribution.”; black swan theory — “a metaphor that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight.”) - Gabriel Weinberg
Fat-Tailed Processes (Extremistan)
A process can often look like a normal distribution but have a large “tail” – meaning that seemingly outlier events are far more likely than they are in an actual normal distribution. A strategy or process may be far more risky than a normal distribution is capable of describing if the fat tail is on the negative side, or far more profitable if the fat tail is on the positive side. Much of the human social world is said to be fat-tailed rather than normally distributed.
Bayesian Updating
The Bayesian method is a method of thought (named for Thomas Bayes) whereby one takes into account all prior relevant probabilities and then incrementally updates them as newer information arrives. This method is especially productive given the fundamentally non-deterministic world we experience: We must use prior odds and new information in combination to arrive at our best decisions. This is not necessarily our intuitive decision-making engine.
Regression to the Mean
In a normally distributed system, long deviations from the average will tend to return to that average with an increasing number of observations: the so-called Law of Large Numbers. We are often fooled by regression to the mean, as with a sick patient improving spontaneously around the same time they begin taking an herbal remedy, or a poorly performing sports team going on a winning streak. We must be careful not to confuse statistically likely events with causal ones. - Shane Parrish
“The phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement.” (related: Pendulum swing; variance; Gambler’s fallacy) - Gabriel Weinberg
Order of Magnitude
In many, perhaps most, systems, quantitative description down to a precise figure is either impossible or useless (or both). For example, estimating the distance between our galaxy and the next one over is a matter of knowing not the precise number of miles, but how many zeroes are after the 1. Is the distance about 1 million miles or about 1 billion? This thought habit can help us escape useless precision. - Shane Parrish
“An order-of-magnitude estimate of a variable whose precise value is unknown is an estimate rounded to the nearest power of ten.” (related: order of approximation, back-of-the-envelope calculation, dimensional analysis, Fermi problem) - Gabriel Weinberg
Scale
One of the most important principles of systems is that they are sensitive to scale. Properties (or behaviors) tend to change when you scale them up or down. In studying complex systems, we must always be roughly quantifying – in orders of magnitude, at least – the scale at which we are observing, analyzing, or predicting the system.
Law of Diminishing Returns
Related to scale, most important real-world results are subject to an eventual decrease of incremental value. A good example would be a poor family: Give them enough money to thrive, and they are no longer poor. But after a certain point, additional money will not improve their lot; there is a clear diminishing return of additional dollars at some roughly quantifiable point. Often, the law of diminishing returns veers into negative territory – i.e., receiving too much money could destroy the poor family.
Pareto Principle (80/20 Rule)
Named for Italian polymath Vilfredo Pareto, who noticed that 80% of Italy’s land was owned by about 20% of its population, the Pareto Principle states that a small amount of some phenomenon causes a disproportionately large effect. The Pareto Principle is an example of a power-law type of statistical distribution – as distinguished from a traditional bell curve – and is demonstrated in various phenomena ranging from wealth to city populations to important human habits.
Feedback Loops (and Homeostasis)
All complex systems are subject to positive and negative feedback loops whereby A causes B, which in turn influences A (and C), and so on – with higher-order effects frequently resulting from continual movement of the loop. In a homeostatic system, a change in A is often brought back into line by an opposite change in B to maintain the balance of the system, as with the temperature of the human body or the behavior of an organizational culture. Automatic feedback loops maintain a “static” environment unless and until an outside force changes the loop. A “runaway feedback loop” describes a situation in which the output of a reaction becomes its own catalyst (auto-catalysis).
Chaos Dynamics (Sensitivity to Initial Conditions or Butterfly Effect)
In a world such as ours, governed by chaos dynamics, small changes (perturbations) in initial conditions have massive downstream effects as near-infinite feedback loops occur; this phenomenon is also called the butterfly effect. This means that some aspects of physical systems (like the weather more than a few days from now) as well as social systems (the behavior of a group of human beings over a long period) are fundamentally unpredictable.
Preferential Attachment (Cumulative Advantage)
A preferential attachment situation occurs when the current leader is given more of the reward than the laggards, thereby tending to preserve or enhance the status of the leader. A strong network effect is a good example of preferential attachment; a market with 10x more buyers and sellers than the next largest market will tend to have a preferential attachment dynamic.
Emergence
Higher-level behavior tends to emerge from the interaction of lower-order components. The result is frequently not linear – not a matter of simple addition – but rather non-linear, or exponential. An important resulting property of emergent behavior is that it cannot be predicted from simply studying the component parts. - Shane Parrish
“Whereby larger entities, patterns, and regularities arise through interactions among smaller or simpler entities that themselves do not exhibit such properties.” (related: decentralized system, spontaneous order) - Gabriel Weinberg
Irreducibility
We find that in most systems there are irreducible quantitative properties, such as complexity, minimums, time, and length. Below the irreducible level, the desired result simply does not occur. One cannot get several women pregnant to reduce the amount of time needed to have one child, and one cannot reduce a successfully built automobile to a single part. These results are, to a defined point, irreducible.
Tragedy of the Commons
A concept introduced by the economist and ecologist Garrett Hardin, the Tragedy of the Commons states that in a system where a common resource is shared, with no individual responsible for the wellbeing of the resource, it will tend to be depleted over time. The Tragedy is reducible to incentives: Unless people collaborate, each individual derives more personal benefit than the cost that he or she incurs, and therefore depletes the resource for fear of missing out.
Gresham’s Law
Gresham’s Law, named for the financier Thomas Gresham, states that in a system of circulating currency, forged currency will tend to drive out real currency, as real currency is hoarded and forged currency is spent. We see a similar result in human systems, as with bad behavior driving out good behavior in a crumbling moral system, or bad practices driving out good practices in a crumbling economic system. Generally, regulation and oversight are required to prevent results that follow Gresham’s Law.
Algorithms
“While hard to precisely define, an algorithm is generally an automated set of rules or a “blueprint” leading a series of steps or actions resulting in a desired outcome, and often stated in the form of a series of “If ? Then” statements. Algorithms are best known for their use in modern computing, but are a feature of biological life as well. For example, human DNA contains an algorithm for building a human being.” - Shane Parrish
An algorithm is a certain sort of formal process that can be counted on—logically—to yield a certain sort of result whenever it is “run” or instantiated. Algorithms are not new, and they were not new in Darwin’s day.
The idea that an algorithm is a foolproof and somehow “mechanical” procedure has been present for centuries, but it was the pioneering work of Alan Turing, Kurt Gödel, and Alonzo Church in the 1930s that more or less fixed our current understanding of the term. Three key features of algorithms will be important to us, and each is somewhat difficult to define.
(1) Substrate neutrality
(2) Underlying mindlessness
(3) Guaranteed results
- Daniel Dennett
Fragility – Robustness – Antifragility
Popularized by Nassim Taleb, the sliding scale of fragility, robustness, and antifragility refers to the responsiveness of a system to incremental negative variability. A fragile system or object is one in which additional negative variability has a disproportionately negative impact, as with a coffee cup shattering from a 6-foot fall, but receiving no damage at all (rather than 1/6th of the damage) from a 1-foot fall. A robust system or object tends to be neutral to the additional negativity variability, and of course, an antifragile system benefits: If there were a cup that got stronger when dropped from 6 feet than when dropped from 1 foot, it would be termed antifragile.
Backup Systems/Redundancy
“A critical model of the engineering profession is that of backup systems. A good engineer never assumes the perfect reliability of the components of the system. He or she builds in redundancy to protect the integrity of the total system. Without the application of this robustness principle, tangible and intangible systems tend to fail over time.” - Shane Parrish
“In reliability engineering, redundancy is defined as the existence of more than one means for accomplishing a given task. Thus all of these means must fail before there is a system failure.
A Backup System is turning a Multiplicative System with a single break point into an additive system with two or more break points.
How to use this mental model: Analyze the primary system
- Is the primary system a multiplicative one or additive one ? If the system if additive, by definition it doesn’t need a backup system.
if the primary system is a simple or complex one ? If the system is a simple one, other means of increasing reliability could be more effective( margin of safety )
- Designing Backup System.
if the primary system is a complex and multiplicative one, adding backup system could greatly improve reliability.” - James Clear
Margin of Safety
“Similarly, engineers have also developed the habit of adding a margin for error into all calculations. In an unknown world, driving a 9,500-pound bus over a bridge built to hold precisely 9,600 pounds is rarely seen as intelligent. Thus, on the whole, few modern bridges ever fail. In practical life outside of physical engineering, we can often profitably give ourselves margins as robust as the bridge system.” -Shane Parrish
“The difference between the intrinsic value of a stock and its market price.” - Gabriel Weinberg
“This term, margin of safety, is an engineering concept used to describe the ability of a system to withstand loads that are greater than expected.
There are many ways to implement a margin of safety in everyday life. The core idea is to protect yourself from unforeseen problems and challenges by building a buffer between what you expect to happen and what could happen. This idea is widely useful on a day-to-day basis because uncertainty creeps into every area of life. Let’s explore a few ways we can use this concept to live better.” - James Clear
Criticality
A system becomes critical when it is about to jump discretely from one phase to another. The marginal utility of the last unit before the phase change is wildly higher than any unit before it. A frequently cited example is water turning from a liquid to a vapor when heated to a specific temperature. “Critical mass” refers to the mass needed to have the critical event occur, most commonly in a nuclear system.
Network Effects
“A network tends to become more valuable as nodes are added to the network: this is known as the network effect. An easy example is contrasting the development of the electricity system and the telephone system. If only one house has electricity, its inhabitants have gained immense value, but if only one house has a telephone, its inhabitants have gained nothing of use. Only with additional telephones does the phone network gain value. This network effect is widespread in the modern world and creates immense value for organizations and customers alike.” - Shane Parrish
“Network effects occur when a product or service becomes more valuable as more people use it. Network effects help you build better, faster-growing and more valuable products and businesses.” - ?Robert Metcalfe
“The effect that one user of a good or service has on the value of that product to other people. When a network effect is present, the value of a product or service is dependent on the number of others using it.” - Gabriel Weinberg
Black Swan
Also popularized by Nassim Taleb, a Black Swan is a rare and highly consequential event that is invisible to a given observer ahead of time. It is a result of applied epistemology: If you have seen only white swans, you cannot categorically state that there are no black swans, but the inverse is not true: seeing one black swan is enough for you to state that there are black swans. Black Swan events are necessarily unpredictable to the observer (as Taleb likes to say, Thanksgiving is a Black Swan for the turkey, not the butcher) and thus must be dealt with by addressing the fragility-robustness-antifragility spectrum rather than through better methods of prediction.
Via Negativa – Omission/Removal/Avoidance of Harm
In many systems, improvement is at best, or at times only, a result of removing bad elements rather than of adding good elements. This is a credo built into the modern medical profession: First, do no harm. Similarly, if one has a group of children behaving badly, removal of the instigator is often much more effective than any form of punishment meted out to the whole group.
The Lindy Effect
The Lindy Effect refers to the life expectancy of a non-perishable object or idea being related to its current lifespan. If an idea or object has lasted for X number of years, it would be expected (on average) to last another X years. Although a human being who is 90 and lives to 95 does not add 5 years to his or her life expectancy, non-perishables lengthen their life expectancy as they continually survive. A classic text is a prime example: if humanity has been reading Shakespeare’s plays for 500 years, it will be expected to read them for another 500.
Renormalization Group
The renormalization group technique allows us to think about physical and social systems at different scales. An idea from physics, and a complicated one at that, the application of a renormalization group to social systems allows us to understand why a small number of stubborn individuals can have a disproportionate impact if those around them follow suit on increasingly large scales.
Spring-loading
A system is spring-loaded if it is coiled in a certain direction, positive or negative. Positively spring-loading systems and relationships is important in a fundamentally unpredictable world to help protect us against negative events. The reverse can be very destructive.
Complex Adaptive Systems
A complex adaptive system, as distinguished from a complex system in general, is one that can understand itself and change based on that understanding. Complex adaptive systems are social systems. The difference is best illustrated by thinking about weather prediction contrasted to stock market prediction. The weather will not change based on an important forecaster’s opinion, but the stock market might. Complex adaptive systems are thus fundamentally not predictable.
Laws of Thermodynamics
The laws of thermodynamics describe energy in a closed system. The laws cannot be escaped and underlie the physical world. They describe a world in which useful energy is constantly being lost, and energy cannot be created or destroyed. Applying their lessons to the social world can be a profitable enterprise.
Reciprocity
“If I push on a wall, physics tells me that the wall pushes back with equivalent force. In a biological system, if one individual acts on another, the action will tend to be reciprocated in kind. And of course, human beings act with intense reciprocity demonstrated as well.” - Shane Parrish
“The norm of reciprocity requires that we repay in kind what another has done for us. It can be understood as the expectation that people will respond favorably to each other by returning benefits for benefits, and responding with either indifference or hostility to harms. The social norm of reciprocity often takes different forms in different areas of social life, or in different societies. All of them, however, are distinct from related ideas such as gratitude, the Golden Rule, or mutual goodwill. See reciprocity (social and political philosophy) for an analysis of the concepts involved. The norm of reciprocity mirrors the concept of reciprocal altruism in evolutionary biology. However, evolutionary theory and therefore sociobiology was not well received by mainstream psychologists. This led to the revitalisation of reciprocal altruism underneath the new social psychological concept, norm of reciprocity. Reciprocal altruism has been applied to various species, including humans, while mainstream psychologists use the norm of reciprocity to only explain humans.” - Wikipedia (James Clear)
Velocity
“Velocity is not equivalent to speed; the two are sometimes confused. Velocity is speed plus vector: how fast something gets somewhere. An object that moves two steps forward and then two steps back has moved at a certain speed but shows no velocity. The addition of the vector, that critical distinction, is what we should consider in practical life.” - Shane Parrish
“The velocity of an object is the rate of change of its position with respect to a frame of reference, and is a function of time. Velocity is equivalent to a specification of its speed and direction of motion (e.g. 60 km/h to the north). Velocity is an important concept in kinematics, the branch of classical mechanics that describes the motion of bodies.
Velocity is a physical vector quantity; both magnitude and direction are needed to define it.” - Wikipedia (James Clear)
Relativity
“Relativity has been used in several contexts in the world of physics, but the important aspect to study is the idea that an observer cannot truly understand a system of which he himself is a part. For example, a man inside an airplane does not feel like he is experiencing movement, but an outside observer can see that movement is occurring. This form of relativity tends to affect social systems in a similar way.” - Shane Parrish
“The theory of relativity usually encompasses two interrelated theories by Albert Einstein: special relativity and general relativity.Special relativity applies to elementary particles and their interactions, describing all their physical phenomena except gravity. General relativity explains the law of gravitation and its relation to other forces of nature. It applies to the cosmological and astrophysical realm, including astronomy.” - Wikipedia (James Clear)
Activation Energy
“A fire is not much more than a combination of carbon and oxygen, but the forests and coal mines of the world are not combusting at will because such a chemical reaction requires the input of a critical level of “activation energy” in order to get a reaction started. Two combustible elements alone are not enough.” - Shane Parrish
“The minimum energy which must be available to a chemical system with potential reactants to result in a chemical reaction.” - Gabriel Weinberg
“In chemistry, activation energy is the energy which must be available to a chemical system with potential reactants to result in a chemical reaction.[1] Activation energy may also be defined as the minimum energy required to start a chemical reaction. The activation energy of a reaction is usually denoted by Ea and given in units of kilojoules per mole (kJ/mol) or kilocalories per mole (kcal/mol).
Activation energy can be thought of as the height of the potential barrier (sometimes called the energy barrier) separating two minima of potential energy (of the reactants and products of a reaction). For a chemical reaction to proceed at a reasonable rate, there should exist an appreciable number of molecules with translational energy equal to or greater than the activation energy.” - Wikipedia (James Clear )
Catalysts
A catalyst either kick-starts or maintains a chemical reaction, but isn’t itself a reactant. The reaction may slow or stop without the addition of catalysts. Social systems, of course, take on many similar traits, and we can view catalysts in a similar light. - Shane Parrish
“Catalysis (/k??tæl?s?s/) is the increase in the rate of a chemical reaction due to the participation of an additional substance called a catalyst, which is not consumed in the catalyzed reaction and can continue to act repeatedly. Often only tiny amounts of catalyst are required in principle.
In general, reactions occur faster with a catalyst because they require less activation energy. In catalyzed mechanisms, the catalyst usually reacts to form a temporary intermediate which then regenerates the original catalyst in a cyclic process.” - Wikipedia (Gabriel Weinberg)
“A substance which increases the rate of a chemical reaction.” (related: tipping point) - James Clear
Leverage
“Most of the engineering marvels of the world have been accomplished with applied leverage. As famously stated by Archimedes, “Give me a lever long enough and I shall move the world.” With a small amount of input force, we can make a great output force through leverage. Understanding where we can apply this model to the human world can be a source of great success.” - Shane Parrish
“The force amplification achieved by using a tool, mechanical device or machine system.” (related: Theory of constraints — “a management paradigm that views any manageable system as being limited in achieving more of its goals by a very small number of constraints.” - Gabriel Weinberg
Math & Engineering: “Mechanical advantage is a measure of the force amplification achieved by using a tool, mechanical device or machine system. The device preserves the input power and simply trades off forces against movement to obtain a desired amplification in the output force. The model for this is the law of the lever. Machine components designed to manage forces and movement in this way are called mechanisms.An ideal mechanism transmits power without adding to or subtracting from it. This means the ideal mechanism does not include a power source, is frictionless, and is constructed from rigid bodies that do not deflect or wear. The performance of a real system relative to this ideal is expressed in terms of efficiency factors that take into account departures from the ideal.” - Wikipedia (James Clear)
Inertia
“An object in motion with a certain vector wants to continue moving in that direction unless acted upon. This is a fundamental physical principle of motion; however, individuals, systems, and organizations display the same effect. It allows them to minimize the use of energy, but can cause them to be destroyed or eroded.” - Shane Parrish
“the resistance of any physical object to any change in its state of motion; this includes changes to its speed, direction or state of rest. It is the tendency of objects to keep moving in a straight line at constant velocity.” (related: strategy tax — “sometimes products developed inside a company…have to accept constraints that go against competitiveness, or might displease users, in order to further the cause of another product.”; flywheel — “a rotating mechanical device that is used to store rotational energy. Flywheels have an inertia called the moment of inertia and thus resist changes in rotational speed.”) - Gabriel Weinberg
Alloying
When we combine various elements, we create new substances. This is no great surprise, but what can be surprising in the alloying process is that 2+2 can equal not 4 but 6 – the alloy can be far stronger than the simple addition of the underlying elements would lead us to believe. This process leads us to engineering great physical objects, but we understand many intangibles in the same way; a combination of the right elements in social systems or even individuals can create a 2+2=6 effect similar to alloying.
Critical Mass
“The smallest amount of fissile material needed for a sustained nuclear chain reaction.” “In social dynamics, critical mass is a sufficient number of adopters of an innovation in a social system so that the rate of adoption becomes self-sustaining and creates further growth.” - Gabriel Weinberg
“A critical mass is the smallest amount of fissile material needed for a sustained nuclear chain reaction. The critical mass of a fissionable material depends upon its nuclear properties (specifically, the nuclear fission cross-section), its density, its shape, its enrichment, its purity, its temperature, and its surroundings. The concept is important in nuclear weapon design.” - Wikipedia (James Clear)
Half-life
“the time required for a quantity to reduce to half its initial value. The term is commonly used in nuclear physics to describe how quickly unstable atoms undergo, or how long stable atoms survive, radioactive decay.” (related: viral marketing)
Heisenberg Uncertainty Principle
“A fundamental limit to the precision with which certain pairs of physical properties of a particle, known as complementary variables, such as position x and momentum p, can be known.”
Incentives
All creatures respond to incentives to keep themselves alive. This is the basic insight of biology. Constant incentives will tend to cause a biological entity to have constant behavior, to an extent. Humans are included and are particularly great examples of the incentive-driven nature of biology; however, humans are complicated in that their incentives can be hidden or intangible. The rule of life is to repeat what works and has been rewarded. - Shane Parrish
Negotiating: “Something that motivates an individual to perform an action.” (related: carrot and stick — “a policy of offering a combination of rewards and punishment to induce behavior.”) - Gabriel Weinberg
Business - Economics: “An incentive is something that motivates an individual to perform an action. The study of incentive structures is central to the study of all economic activities (both in terms of individual decision-making and in terms of co-operation and competition within a larger institutional structure). Economic analysis, then, of the differences between societies (and between different organizations within a society) largely amounts to characterizing the differences in incentive structures faced by individuals involved in these collective efforts. Ultimately, incentives aim to provide value for money and contribute to organizational success. As such the design of incentive systems is a key management activity.” - Wikipedia (James Clear)
Cooperation (Including Symbiosis)
Competition tends to describe most biological systems, but cooperation at various levels is just as important a dynamic. In fact, the cooperation of a bacterium and a simple cell probably created the first complex cell and all of the life we see around us. Without cooperation, no group survives, and the cooperation of groups gives rise to even more complex versions of organization. Cooperation and competition tend to coexist at multiple levels.
Tendency to Minimize Energy Output (Mental & Physical)
In a physical world governed by thermodynamics and competition for limited energy and resources, any biological organism that was wasteful with energy would be at a severe disadvantage for survival. Thus, we see in most instances that behavior is governed by a tendency to minimize energy usage when at all possible.
Adaptation
Species tend to adapt to their surroundings in order to survive, given the combination of their genetics and their environment – an always-unavoidable combination. However, adaptations made in an individual’s lifetime are not passed down genetically, as was once thought: Populations of species adapt through the process of evolution by natural selection, as the most-fit examples of the species replicate at an above-average rate.
Evolution by Natural Selection
Evolution by natural selection was once called “the greatest idea anyone ever had.” In the 19th century, Charles Darwin and Alfred Russel Wallace simultaneous realized that species evolve through random mutation and differential survival rates. If we call human intervention in animal-breeding an example of “artificial selection,” we can call Mother Nature deciding the success or failure of a particular mutation “natural selection.” Those best suited for survival tend to be preserved. But of course, conditions change. - Shane Parrish
“Natural selection is the differential survival and reproduction of individuals due to differences in phenotype. It is a key mechanism of evolution, the change in heritable traits of a population over time. Charles Darwin popularised the term “natural selection”, and compared it with artificial selection…Natural selection acts on the phenotype, or the observable characteristics of an organism, but the genetic (heritable) basis of any phenotype that gives a reproductive advantage may become more common in a population. Over time, this process can result in populations that specialise for particular ecological niches (microevolution) and may eventually result in speciation (the emergence of new species, macroevolution). In other words, natural selection is a key process in the evolution of a population. Natural selection can be contrasted with artificial selection, in which humans intentionally choose specific traits, whereas in natural selection there is no intentional choice.” - Wikipedia (James Clear)
“The differential survival and reproduction of individuals due to differences in phenotype. It is a key mechanism of evolution, the change in heritable traits of a population over time.” - Gabriel Weinberg
The Red Queen Effect (Co-evolutionary Arms Race)
The evolution-by-natural-selection model leads to something of an arms race among species competing for limited resources. When one species evolves an advantageous adaptation, a competing species must respond in kind or fail as a species. Standing pat can mean falling behind. This arms race is called the Red Queen Effect for the character in Alice in Wonderland who said, “Now, here, you see, it takes all the running you can do, to keep in the same place.”
Replication
A fundamental building block of diverse biological life is high-fidelity replication. The fundamental unit of replication seems to be the DNA molecule, which provides a blueprint for the offspring to be built from physical building blocks. There are a variety of replication methods, but most can be lumped into sexual and asexual.
Hierarchical and Other Organizing Instincts
Most complex biological organisms have an innate feel for how they should organize. While not all of them end up in hierarchical structures, many do, especially in the animal kingdom. Human beings like to think they are outside of this, but they feel the hierarchical instinct as strongly as any other organism.
Self-Preservation Instincts
Without a strong self-preservation instinct in an organism’s DNA, it would tend to disappear over time, thus eliminating that DNA. While cooperation is another important model, the self-preservation instinct is strong in all organisms and can cause violent, erratic, and/or destructive behavior for those around them.
Simple Physiological Reward-Seeking
All organisms feel pleasure and pain from simple chemical processes in their bodies which respond predictably to the outside world. Reward-seeking is an effective survival-promoting technique on average. However, those same pleasure receptors can be co-opted to cause destructive behavior, as with drug abuse.
Exaptation
Introduced by the biologist Steven Jay Gould, an exaptation refers to a trait developed for one purpose that is later used for another purpose. This is one way to explain the development of complex biological features like an eyeball; in a more primitive form, it may have been used for something else. Once it was there, and once it developed further, 3D sight became possible.
Extinction
The inability to survive can cause an extinction event, whereby an entire species ceases to compete and replicate effectively. Once its numbers have dwindled to a critically low level, an extinction can be unavoidable (and predictable) given the inability to effectively replicate in large enough numbers.
Ecosystems
An ecosystem describes any group of organisms coexisting with the natural world. Most ecosystems show diverse forms of life taking on different approaches to survival, with such pressures leading to varying behavior. Social systems can be seen in the same light as the physical ecosystems and many of the same conclusions can be made.
Niches
Most organisms find a niche: a method of competing and behaving for survival. Usually, a species will select a niche for which it is best adapted. The danger arises when multiple species begin competing for the same niche, which can cause an extinction – there can be only so many species doing the same thing before limited resources give out.
Dunbar’s Number
The primatologist Robin Dunbar observed through study that the number of individuals a primate can get to know and trust closely is related to the size of its neocortex. Extrapolating from his study of primates, Dunbar theorized that the Dunbar number for a human being is somewhere in the 100–250 range, which is supported by certain studies of human behavior and social networks. - Shane Parrish
Managing: “A suggested cognitive limit to the number of people with whom one can maintain stable social relationships..with a commonly used value of 150.” - Gabriel Weinberg
Opportunity Costs
Doing one thing means not being able to do another. We live in a world of trade-offs, and the concept of opportunity cost rules all. Most aptly summarized as “there is no such thing as a free lunch.” - Shane Parrish
“The value of the best alternative forgone where, given limited resources, a choice needs to be made between several mutually exclusive alternatives. Assuming the best choice is made, it is the ‘cost’ incurred by not enjoying the benefit that would have been had by taking the second best available choice.” (related: cost of capital) - Gabriel Weinberg
Creative Destruction
Coined by economist Joseph Schumpeter, the term “creative destruction” describes the capitalistic process at work in a functioning free-market system. Motivated by personal incentives (including but not limited to financial profit), entrepreneurs will push to best one another in a never-ending game of creative one-upmanship, in the process destroying old ideas and replacing them with newer technology. Beware getting left behind. - Shane Parrish
Competing: “Process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one.” (related: Software is Eating the World — “in many industries, new software ideas will result in the rise of new Silicon Valley-style start-ups that invade existing industries with impunity.”) - Gabriel Weinberg
Comparative Advantage
The Scottish economist David Ricardo had an unusual and non-intuitive insight: Two individuals, firms, or countries could benefit from trading with one another even if one of them was better at everything. Comparative advantage is best seen as an applied opportunity cost: If it has the opportunity to trade, an entity gives up free gains in productivity by not focusing on what it does best. - Shane Parrish
Competing: “An agent has a comparative advantage over another in producing a particular good if they can produce that good at a lower relative opportunity cost or autarky price, i.e. at a lower relative marginal cost prior to trade.” - Gabriel Weinberg
Business - Economics: “The theory of comparative advantage is an economic theory about the work gains from trade for individuals, firms, or nations that arise from differences in their factor endowments or technological progress. In an economic model, agents have a comparative advantage over others in producing a particular good if they can produce that good at a lower relative opportunity cost or autarky price, i.e. at a lower relative marginal cost prior to trade. One does not compare the monetary costs of production or even the resource costs (labor needed per unit of output) of production. Instead, one must compare the opportunity costs of producing goods across countries. The closely related law or principle of comparative advantage holds that under free trade, an agent will produce more of and consume less of a good for which they have a comparative advantage.” - Wikipedia (Gabriel Weinberg)
Specialization (Pin Factory)
Another Scottish economist, Adam Smith, highlighted the advantages gained in a free-market system by specialization. Rather than having a group of workers each producing an entire item from start to finish, Smith explained that it’s usually far more productive to have each of them specialize in one aspect of production. He also cautioned, however, that each worker might not enjoy such a life; this is a trade-off of the specialization model.
Seizing the Middle
In chess, the winning strategy is usually to seize control of the middle of the board, so as to maximize the potential moves that can be made and control the movement of the maximal number of pieces. The same strategy works profitably in business, as can be demonstrated by John D. Rockefeller’s control of the refinery business in the early days of the oil trade and Microsoft’s control of the operating system in the early days of the software trade.
Trademarks, Patents, and Copyrights
These three concepts, along with other related ones, protect the creative work produced by enterprising individuals, thus creating additional incentives for creativity and promoting the creative-destruction model of capitalism. Without these protections, information and creative workers have no defense against their work being freely distributed.
Double-Entry Bookkeeping
One of the marvels of modern capitalism has been the bookkeeping system introduced in Genoa in the 14th century. The double-entry system requires that every entry, such as income, also be entered into another corresponding account. Correct double-entry bookkeeping acts as a check on potential accounting errors and allows for accurate records and thus, more accurate behavior by the owner of a firm.
Utility (Marginal, Diminishing, Increasing)
The usefulness of additional units of any good tends to vary with scale. Marginal utility allows us to understand the value of one additional unit, and in most practical areas of life, that utility diminishes at some point. On the other hand, in some cases, additional units are subject to a “critical point” where the utility function jumps discretely up or down. As an example, giving water to a thirsty man has diminishing marginal utility with each additional unit, and can eventually kill him with enough units.
Bottlenecks
A bottleneck describes the place at which a flow (of a tangible or intangible) is stopped, thus holding it back from continuous movement. As with a clogged artery or a blocked drain, a bottleneck in production of any good or service can be small but have a disproportionate impact if it is in the critical path.
Prisoner’s Dilemma
The Prisoner’s Dilemma is a famous application of game theory in which two prisoners are both better off cooperating with each other, but if one of them cheats, the other is better off cheating. Thus the dilemma. This model shows up in economic life, in war, and in many other areas of practical human life. Though the prisoner’s dilemma theoretically leads to a poor result, in the real world, cooperation is nearly always possible and must be explored.
Bribery
Often ignored in mainstream economics, the concept of bribery is central to human systems: Given the chance, it is often easier to pay a certain agent to look the other way than to follow the rules. The enforcer of the rules is then neutralized. This principle/agent problem can be seen as a form of arbitrage.
Arbitrage
Given two markets selling an identical good, an arbitrage exists if the good can profitably be bought in one market and sold at a profit in the other. This model is simple on its face, but can present itself in disguised forms: The only gas station in a 50-mile radius is also an arbitrage as it can buy gasoline and sell it at the desired profit (temporarily) without interference. Nearly all arbitrage situations eventually disappear as they are discovered and exploited.
Supply and Demand
The basic equation of biological and economic life is one of limited supply of necessary goods and competition for those goods. Just as biological entities compete for limited usable energy, so too do economic entities compete for limited customer wealth and limited demand for their products. The point at which supply and demand for a given good are equal is called an equilibrium; however, in practical life, equilibrium points tend to be dynamic and changing, never static. - Shane Parrish
Competing: “An economic model of price determination in a market. It concludes that in a competitive market, the unit price for a particular good, or other traded item such as labor or liquid financial assets, will vary until it settles at a point where the quantity demanded (at the current price) will equal the quantity supplied (at the current price), resulting in an economic equilibrium for price and quantity transacted.” (related: perfect competition; arbitrage — “the practice of taking advantage of a price difference between two or more markets.”) - Gabriel Weinberg
Business and Economincs: “In microeconomics, supply and demand is an economic model of price determination in a market. It postulates that in a competitive market, the unit price for a particular good, or other traded item such as labor or liquid financial assets, will vary until it settles at a point where the quantity demanded (at the current price) will equal the quantity supplied (at the current price), resulting in an economic equilibrium for price and quantity transacted.” - Wikipedia (James Clear)
Scarcity
Game theory describes situations of conflict, limited resources, and competition. Given a certain situation and a limited amount of resources and time, what decisions are competitors likely to make, and which should they make? One important note is that traditional game theory may describe humans as more rational than they really are. Game theory is theory, after all. - Shane Parrish
Business - Economics: “Scarcity refers to the limited availability of a commodity, which may be in demand in the market. The concept of scarcity also includes an individual capacity to buy all or some of the commodities as per the available resources with that individual” - Wikipedia (James Clear)
Winner Take All Market
A market that tends towards one dominant player. (related: lock-in; monopoly; monopsony)
Two-sided Market
“Economic platforms having two distinct user groups that provide each other with network benefits.”
Barriers to Entry
“A cost that must be incurred by a new entrant into a market that incumbents don’t or haven’t had to incur.”
Price Elasticity
“The measurement of how responsive an economic variable is to a change in another. It gives answers to questions such as ‘If I lower the price of a product, how much more will sell?’” (related: Giffen good — “a product that people consume more of as the price rises and vice versa.”)
Market Power
“The ability of a firm to profitably raise the market price of a good or service over marginal cost.”
Conspicuous Consumption
“The spending of money on and the acquiring of luxury goods and services to publicly display economic power.” (related: Veblen goods — “types of luxury goods, such as expensive wines, jewelry, fashion-designer handbags, and luxury cars, which are in demand because of the high prices asked for them.”)
First-mover advantage vs First-mover disadvantage
“the advantage gained by the initial (“first-moving”) significant occupant of a market segment.” (related: Why now?)
Seeing the Front
One of the most valuable military tactics is the habit of “personally seeing the front” before making decisions – not always relying on advisors, maps, and reports, all of which can be either faulty or biased. The Map/Territory model illustrates the problem with not seeing the front, as does the incentive model. Leaders of any organization can generally benefit from seeing the front, as not only does it provide firsthand information, but it also tends to improve the quality of secondhand information.
Asymmetric Warfare
The asymmetry model leads to an application in warfare whereby one side seemingly “plays by different rules” than the other side due to circumstance. Generally, this model is applied by an insurgency with limited resources. Unable to out-muscle their opponents, asymmetric fighters use other tactics, as with terrorism creating fear that’s disproportionate to their actual destructive ability.
Two-Front War
The Second World War was a good example of a two-front war. Once Russia and Germany became enemies, Germany was forced to split its troops and send them to separate fronts, weakening their impact on either front. In practical life, opening a two-front war can often be a useful tactic, as can solving a two-front war or avoiding one, as in the example of an organization tamping down internal discord to focus on its competitors. - Shane Parrish
“A war in which fighting takes place on two geographically separate fronts.” - Gabriel Weinberg
Counterinsurgency
Though asymmetric insurgent warfare can be extremely effective, over time competitors have also developed counterinsurgency strategies. Recently and famously, General David Petraeus of the United States led the development of counterinsurgency plans that involved no additional force but substantial additional gains. Tit-for-tat warfare or competition will often lead to a feedback loop that demands insurgency and counterinsurgency.
Mutually Assured Destruction
Somewhat paradoxically, the stronger two opponents become, the less likely they may be to destroy one another. This process of mutually assured destruction occurs not just in warfare, as with the development of global nuclear warheads, but also in business, as with the avoidance of destructive price wars between competitors. However, in a fat-tailed world, it is also possible that mutually assured destruction scenarios simply make destruction more severe in the event of a mistake (pushing destruction into the “tails” of the distribution). - Shane Parrish
“In which a full-scale use of nuclear weapons by two or more opposing sides would cause the complete annihilation of both the attacker and the defender. It is based on the theory of deterrence, which holds that the threat of using strong weapons against the enemy prevents.” (related: Mexican standoff, Zugzwang) - Gabriel Weinberg
Guerilla warfare
“a form of irregular warfare in which a small group of combatants such as paramilitary personnel, armed civilians, or irregulars use military tactics including ambushes, sabotage, raids, petty warfare, hit-and-run tactics, and mobility to fight a larger and less-mobile traditional military.” (related: asymmetric warfare; “Punch above your weight.”)
Flypaper Theory
“The idea that it is desirable to draw enemies to a single area, where it is easier to kill them and they are far from one’s own vulnerabilities.” (related: honeypot)
Fighting the Last War
Using strategies and tactics that worked successfully in the past, but are no longer as useful.
Rumsfeld’s Rule
“You go to war with the Army you have. They’re not the Army you might want or wish to have at a later time.” (related: Joy’s law — “no matter who you are, most of the smartest people work for someone else.”; Effectuation)
Trojan Horse
“After a fruitless 10-year siege, the Greeks constructed a huge wooden horse, and hid a select force of men inside. The Greeks pretended to sail away, and the Trojans pulled the horse into their city as a victory trophy. That night the Greek force crept out of the horse and opened the gates for the rest of the Greek army, which had sailed back under cover of night. The Greeks entered and destroyed.”
Empty Fort Strategy
“Involves using reverse psychology (and luck) to deceive the enemy into thinking that an empty location is full of traps and ambushes, and therefore induce the enemy to retreat.” (related: Potemkin village?— “any construction (literal or figurative) built solely to deceive others into thinking that a situation is better than it really is.”; vaporware — “a product, typically computer hardware or software, that is announced to the general public but is never actually manufactured nor officially cancelled.”)
Exit Strategy
“A means of leaving one’s current situation, either after a predetermined objective has been achieved, or as a strategy to mitigate failure.”
Boots on the Ground
“The belief that military success can only be achieved through the direct physical presence of troops in a conflict area.”
Winning Hearts and Minds
“In which one side seeks to prevail not by the use of superior force, but by making emotional or intellectual appeals to sway supporters of the other side.”
Containment
“A military strategy to stop the expansion of an enemy. It is best known as the Cold War policy of the United States and its allies to prevent the spread of communism abroad.”
Appeasement
“A diplomatic policy of making political or material concessions to an enemy power in order to avoid conflict.” (related: Danegeld, extortion)
Winning a Battle but Losing the War
“A poor strategy that wins a lesser (or sub-) objective but overlooks and loses the true intended objective.” (related: sacrifice play)
Beachhead
“A temporary line created when a military unit reaches a landing beach by sea and begins to defend the area while other reinforcements help out until a unit large enough to begin advancing has arrived.”
Attrition warfare
“a military strategy in which a belligerent attempts to win a war by wearing down the enemy to the point of collapse through continuous losses in personnel and material.”
2 - 2 - Schelling’s Segregation Model
“In 1971, the American economist Thomas Schelling created an agent-based model that might help explain why segregation is so difficult to combat. His model of segregation showed that even when individuals (or “agents”) didn’t mind being surrounded or living by agents of a different race, they would still choose to segregate themselves from other agents over time! Although the model is quite simple, it gives a fascinating look at how individuals might self-segregate, even when they have no explicit desire to do so.” - Harding University Computer Science Department
2 - 4 - Peer Effects
“These sort of contagion phenomena that happened [inaudible] pure effects. That sometimes. The tail wags the dog. What do I mean by that. What I mean is that sometimes. The people at the end of distribution. The extremists. Are the ones that really drive what happens. And as a result. That means it’s gonna be incredibly difficult to predict what’s gonna go on. “ - Transcript from Scott Page Coursera
2 - 5 - The Standing Ovation Model
“Now this is a model that builds off the [inaudible] model it’s just really an extension. But it can allow us to sort of think about threshold based models of participation and pure effects in a little more subtle ways. Why standing ovations, those are kind of a funny thing to study. Well here’s why. Think about a standing ovation. When The performance ends, you don’t have a lot of time to decide whether you are going to stand up or not. You gotta make sort of a fairly quick judgment. You’re going to clap of course but then you gotta decide do I stand or do I not stand. And then after the standing ovation either starts or doesn’t start you gotta make another decision, do I stand up, do I follow these people, or do I you know stay sitting. So when you think about human behavior there’s going to be different models that we play with throughout the course about how humans act. One model will be that people are optimizing, that they make rational choices in all setting. When it comes [inaudible] of a standing ovations that is probably a difficult thing to do because it is all happening so fast. So instead, what people probably do is they follow rules. “- Transcript from Scott Page Coursera
2 - 6 - The Identification Problem - The Big Sort: Why the Clustering of Like-Minded America is Tearing Us Apart
“Synopsis of Big Sort: Bill Bishop claims that we are increasingly self-sorting ourselves into neighborhoods politically and only associating with like-minded political neighbors with all kinds of horrible consequences. Much of Bishop and Cushing’s evidence about the corrosive effect comes from psycho-sociological experiments like Asch’s where group pressure causes people to behave immorally (a la Lord of the Flies or the Stanford Prison Experiment), or to censure their own dissonant voice even when they originally believed those views to be correct. [Note: Fiorina has made quite a name for himself on how the political elites in America have become ever more polarized and the masses have over time sorted themselves out more reliably into political parties but the masses views’ have not become any more extreme, so obviously the Big Sort doesn’t square with his other research that uses ongoing surveys like the General Social Survey, the American National Election Studies, etc.] There is a wonderful cartoon that the New York Times did about the Big Sort.” -Social Capital Blog
3 2 Central Limit Theorem
“The central limit theorem (CLT) is a statistical theory that states that given a sufficiently large sample size from a population with a finite level of variance, the mean of all samples from the same population will be approximately equal to the mean of the population. Furthermore, all of the samples will follow an approximate normal distribution pattern, with all variances being approximately equal to the variance of the population divided by each sample’s size.” - Investopedia
3 3 Six Sigma
“Six Sigma (6?) is a set of techniques and tools for process improvement. It was introduced by engineers Bill Smith & Mikel J Harry while working at Motorola in 1986.[1][2] Jack Welch made it central to his business strategy at General Electric in 1995.
It seeks to improve the quality of the output of a process by identifying and removing the causes of defects and minimizing variability in manufacturing and business processes. It uses a set of quality management methods, mainly empirical, statistical methods, and creates a special infrastructure of people within the organization who are experts in these methods. Each Six Sigma project carried out within an organization follows a defined sequence of steps and has specific value targets, for example: reduce process cycle time, reduce pollution, reduce costs, increase customer satisfaction, and increase profits.” -Wikipededia
3 5 Cellular Automata
“A cellular automaton (pl. cellular automata, abbrev. CA) is a discrete model studied in computability theory, mathematics, physics, complexity science, theoretical biology and microstructure modeling. Cellular automata are also called cellular spaces, tessellation automata, homogeneous structures, cellular structures, tessellation structures, and iterative arrays.” Wikipedia
3 6 Preference Aggregation
“At the heart of social choice theory is the analysis of preference aggregation, understood as the aggregation of several individuals’ preference rankings of two or more social alternatives into a single, collective preference ranking (or choice) over these alternatives.” - Stanford Encyclopedia of Philosophy
4 2 Multi Criterion Decision Making
“Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making (both in daily life and in settings such as business, government and medicine). Conflicting criteria are typical in evaluating options: cost or price is usually one of the main criteria, and some measure of quality is typically another criterion, easily in conflict with the cost. In purchasing a car, cost, comfort, safety, and fuel economy may be some of the main criteria we consider – it is unusual that the cheapest car is the most comfortable and the safest one. In portfolio management, we are interested in getting high returns but at the same time reducing our risks, but the stocks that have the potential of bringing high returns typically also carry high risks of losing money. In a service industry, customer satisfaction and the cost of providing service are fundamental conflicting criteria” - Wikipedia
4 3 Spatial Choice Models-Model Thinking
“Spatial choice models originally started by thinking about geographic choice. There’s a guy named Harold Hoteling who’s an economist who thought about, imagine you’re on a beach and there’s an ice cream vendor, you know, 50 feet to your left and there’s another ice cream vendor 40 feet to your right. You made decide well, you know, since the one to my right is closer what I’ll do is I’ll go and, you know, buy my ice cream from the one that’s closer and I don’t have to walk as far. Well you can take that idea and you can apply it to attributes of a good.” - Transcript from Scott Page Coursera
4 4 Probability The Basics
“Probability is the measure of the likelihood that an event will occur.[1] Probability is quantified as a number between 0 and 1, where, loosely speaking,[2] 0 indicates impossibility and 1 indicates certainty.[3][4] The higher the probability of an event, the more likely it is that the event will occur. A simple example is the tossing of a fair (unbiased) coin. Since the coin is fair, the two outcomes (“heads” and “tails”) are both equally probable; the probability of “heads” equals the probability of “tails”; and since no other outcomes are possible, the probability of either “heads” or “tails” is 1/2 (which could also be written as 0.5 or 50%).” - Wikipedia
4 5 Decision Trees
“A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm.
Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning.” - Wikipedia (Scott Page)
“A decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility.” (related: expected value) - Gabriel Weinberg
4 6 Value of Information
“Value of Information (VoI) is a concept from decision analysis: how much answering a question allows a decision-maker to improve its decision. Like opportunity cost, it’s easy to define but often hard to internalize; and so instead of belaboring the definition let’s look at some examples.” -LessWrong
Synthesize the situation at hand.
- One of the most important decisions you can make is who you ask questions of.
- Don’t believe everything you hear.
- Everything looks bigger up close.
- New is overvalued relative to great.
- Don’t oversqueeze dots.
Synthesize the situation through time.
- Keep in mind both the rates of change and the levels of things, and the relationships between them.
- Be imprecise.
- Remember the 80/20 Rule and know what the key 20 percent is.
- Be an imperfectionist.
Navigate levels effectively.
- Use the terms “above the line” and “below the line” to establish which level a conversation is on.
- Remember that decisions need to be made at the appropriate level, but they should also be consistent across levels.
Make your decisions as expected value calculations.
- Raising the probability of being right is valuable no matter what your probability of being right already is.
- Knowing when not to bet is as important as knowing what bets are probably worth making.
- The best choices are the ones that have more pros than cons, not those that don’t have any cons at all.
Prioritize by weighing the value of additional information against the cost of not deciding.
- All of your “must-dos” must be above the bar before you do your “like-to-dos.”
- Chances are you won’t have time to deal with the unimportant things, which is better than not having time to deal with the important things.
- Don’t mistake possibilities for probabilities.
Business Case
“Captures the reasoning for initiating a project or task. It is often presented in a well-structured written document, but may also sometimes come in the form of a short verbal argument or presentation.” (related: why this now?)
Intuition
Personal experience coded into your personal neural network, which means your intuition is dangerous outside the bounds of your personal experience. (related: thinking fast vs thinking slow — “a dichotomy between two modes of thought: ‘System 1’ is fast, instinctive and emotional; ‘System 2’ is slower, more deliberative, and more logical.”)
Local vs Global Optimum
“A local optimum of an optimization problem is a solution that is optimal (either maximal or minimal) within a neighboring set of candidate solutions. This is in contrast to a global optimum, which is the optimal solution among all possible solutions, not just those in a particular neighborhood of values.”
Sunk Cost
“A cost that has already been incurred and cannot be recovered.” (related: “throwing good money after bad”, “in for a penny, in for a pound”)
Availability Bias
“People tend to heavily weigh their judgments toward more recent information, making new opinions biased toward that latest news.”
Loss Aversion
“People’s tendency to strongly prefer avoiding losses to acquiring gains.” (related: diminishing marginal utility) - Gabriel Weinberg
“In economics and decision theory, loss aversion refers to people’s tendency to prefer avoiding losses to acquiring equivalent gains: it’s better to not lose $5 than to find $5. Some studies have suggested that losses are twice as powerful, psychologically, as gains.
This leads to risk aversion when people evaluate an outcome comprising similar gains and losses; since people prefer avoiding losses to making gains.” - Wikipedia (James Clear)
Recognize that having an effective idea meritocracy requires that you understand the merit of each person’s ideas.
- If you can’t successfully do something, don’t think you can tell others how it should be done.
- Remember that everyone has opinions and they are often bad.
Find the most believable people possible who disagree with you and try to understand their reasoning.
- Think about people’s believability in order to assess the likelihood that their opinions are good.
- Remember that believable opinions are most likely to come from people 1) who have successfully accomplished the thing in question at least three times, and 2) who have great explanations of the cause-effect relationships that lead them to their conclusions.
- If someone hasn’t done something but has a theory that seems logical and can be stress-tested, then by all means test it.
- Don’t pay as much attention to people’s conclusions as to the reasoning that led them to their conclusions.
- Inexperienced people can have great ideas too, sometimes far better ones than more experienced people.
- Everyone should be up-front in expressing how confident they are in their thoughts.
Think about whether you are playing the role of a teacher, a student, or a peer and whether you should be teaching, asking questions, or debating.
- It’s more important that the student understand the teacher than that the teacher understand the student, though both are important.
- Recognize that while everyone has the right and responsibility to try to make sense of important things, they must do so with humility and radical open-mindedness.
Understand how people came by their opinions.
- If you ask someone a question, they will probably give you an answer, so think through to whom you should address your questions.
- Having everyone randomly probe everyone else is an unproductive waste of time.
- Beware of statements that begin with “I think that . . .”
- Assess believability by systematically capturing people’s track records over time.
Disagreeing must be done efficiently.
- Know when to stop debating and move on to agreeing about what should be done.
- Use believability weighting as a tool rather than a substitute for decision making by Responsible Parties.
- Since you don’t have the time to thoroughly examine everyone’s thinking yourself, choose your believable people wisely.
- When you’re responsible for a decision, compare the believability-weighted decision making of the crowd to what you believe.
Recognize that everyone has the right and responsibility to try to make sense of important things.
- Communications aimed at getting the best answer should involve the most relevant people.
- Communication aimed at educating or boosting cohesion should involve a broader set of people than would be needed if the aim were just getting the best answer.
- Recognize that you don’t need to make judgments about everything.
5 1 Thinking Electrons Modeling People
“Modeling people is tricky. Physicist Marie Gelmont once famously said, imagine how difficult physics would be. If electrons could think [laugh] so what did he mean human? What he meant was that you know if you take an electron or a carbon atom or even a water molecule it doesn’t think it doesn’t try to make sense of the world it doesn’t have any goals or objectives or anything like that no beliefs so it’s pretty straight forward to model how those things function when you look at people, people are much more complicated right? We’re purposeful, we’ve got goals we’ve got objectives we’ve got things we want to do, we’ve got belief structures, we’re messy. And because of that you just don’t quite know how we’re going to behave. Now on top of that we’re diverse, right? We want different things. We have different goals and objectives. So this combination of sort of purposeful, thinking actors who are different means that it can be really hard to understand what they do and how they act. “- Transcript from Scott Page Coursera
5 2 Rational Actor Models
“The rational actor model is based on rational choice theory. The model adopts the state as the primary unit of analysis, and inter-state relations (or international relations) as the context for analysis.” - Wikipedia
5 3 Behavioral Models-Model
“The behavioral approach to systems theory and control theory was initiated in the late-1970s by J. C. Willems as a result of resolving inconsistencies present in classical approaches based on state-space, transfer function, and convolution representations. This approach is also motivated by the aim of obtaining a general framework for system analysis and control that respects the underlying physics.” - Wikipedia
5 4 Rule Based Models
“Rule-based modeling is a modeling approach that uses a set of rules that indirectly specifies a mathematical model.” - Wikipedia
5 5 When Does Behavior Matter
“The rational behavior is a really good benchmark. But it’s also important to included biases in our model. Think about, are there biases that would be relevant. And it’s also important to think about what if we just write down a simple rule. And then if we compare these three things. Rationale behavior, bias. Right, and then simple rule. And we see, well, how much difference do we see in the outcome. If the difference is small, then we can say you can look our results seem to be sort of varied to behavior. If the difference is big, then what you gotta do is you gotta sit back and think. Okay which of these three makes the most sense. “- Transcript from Scott Page Coursera
Trust
Fundamentally, the modern world operates on trust. Familial trust is generally a given (otherwise we’d have a hell of a time surviving), but we also choose to trust chefs, clerks, drivers, factory workers, executives, and many others. A trusting system is one that tends to work most efficiently; the rewards of trust are extremely high.
Bias from Incentives
Highly responsive to incentives, humans have perhaps the most varied and hardest to understand set of incentives in the animal kingdom. This causes us to distort our thinking when it is in our own interest to do so. A wonderful example is a salesman truly believing that his product will improve the lives of its users. It’s not merely convenient that he sells the product; the fact of his selling the product causes a very real bias in his own thinking.
Pavlovian Mere Association
Ivan Pavlov very effectively demonstrated that animals can respond not just to direct incentives but also to associated objects; remember the famous dogs salivating at the ring of a bell. Human beings are much the same and can feel positive and negative emotion towards intangible objects, with the emotion coming from past associations rather than direct effects.
Tendency to Feel Envy & Jealousy
Humans have a tendency to feel envious of those receiving more than they are, and a desire “get what is theirs” in due course. The tendency towards envy is strong enough to drive otherwise irrational behavior, but is as old as humanity itself. Any system ignorant of envy effects will tend to self-immolate over time.
Tendency to Distort Due to Liking/Loving or Disliking/Hating
Based on past association, stereotyping, ideology, genetic influence, or direct experience, humans have a tendency to distort their thinking in favor of people or things that they like and against people or things they dislike. This tendency leads to overrating the things we like and underrating or broadly categorizing things we dislike, often missing crucial nuances in the process.
Denial
Anyone who has been alive long enough realizes that, as the saying goes, “denial is not just a river in Africa.” This is powerfully demonstrated in situations like war or drug abuse, where denial has powerful destructive effects but allows for behavioral inertia. Denying reality can be a coping mechanism, a survival mechanism, or a purposeful tactic.
Availability Heuristic
One of the most useful findings of modern psychology is what Daniel Kahneman calls the Availability Bias or Heuristic: We tend to most easily recall what is salient, important, frequent, and recent. The brain has its own energy-saving and inertial tendencies that we have little control over – the availability heuristic is likely one of them. Having a truly comprehensive memory would be debilitating. Some sub-examples of the availability heuristic include the Anchoring and Sunk Cost Tendencies.
Representativeness Heuristic
The three major psychological findings that fall under Representativeness, also defined by Kahneman and his partner Tversky, are:
Failure to Account for Base Rates
An unconscious failure to look at past odds in determining current or future behavior.
Tendency to Stereotype
The tendency to broadly generalize and categorize rather than look for specific nuance. Like availability, this is generally a necessary trait for energy-saving in the brain.
Failure to See False Conjunctions
Most famously demonstrated by the Linda Test, the same two psychologists showed that students chose more vividly described individuals as more likely to fit into a predefined category than individuals with broader, more inclusive, but less vivid descriptions, even if the vivid example was a mere subset of the more inclusive set. These specific examples are seen as more representative of the category than those with the broader but vaguer descriptions, in violation of logic and probability.
Social Proof (Safety in Numbers)
Human beings are one of many social species, along with bees, ants, and chimps, among many more. We have a DNA-level instinct to seek safety in numbers and will look for social guidance of our behavior. This instinct creates a cohesive sense of cooperation and culture which would not otherwise be possible, but also leads us to do foolish things if our group is doing them as well.
Narrative Instinct
Human beings have been appropriately called “the storytelling animal” because of our instinct to construct and seek meaning in narrative. It’s likely that long before we developed the ability to write or to create objects, we were telling stories and thinking in stories. Nearly all social organizations, from religious institutions to corporations to nation-states, run on constructions of the narrative instinct.
Curiosity Instinct
We like to call other species curious, but we are the most curious of all, an instinct which led us out of the savanna and led us to learn a great deal about the world around us, using that information to create the world in our collective minds. The curiosity instinct leads to unique human behavior and forms of organization like the scientific enterprise. Even before there were direct incentives to innovate, humans innovated out of curiosity.
Language Instinct
The psychologist Steven Pinker calls our DNA-level instinct to learn grammatically constructed language the Language Instinct. The idea that grammatical language is not a simple cultural artifact was first popularized by the linguist Noam Chomsky. As we saw with the narrative instinct, we use these instincts to create shared stories, as well as to gossip, solve problems, and fight, among other things. Grammatically ordered language theoretically carries infinite varying meaning.
First-Conclusion Bias
As Charlie Munger famously pointed out, the mind works a bit like a sperm and egg: the first idea gets in and then the mind shuts. Like many other tendencies, this is probably an energy-saving device. Our tendency to settle on first conclusions leads us to accept many erroneous results and cease asking questions; it can be countered with some simple and useful mental routines.
Tendency to Overgeneralize from Small Samples
It’s important for human beings to generalize; we need not see every instance to understand the general rule, and this works to our advantage. With generalizing, however, comes a subset of errors when we forget about the Law of Large Numbers and act as if it does not exist. We take a small number of instances and create a general category, even if we have no statistically sound basis for the conclusion.
Relative Satisfaction/Misery Tendencies
The envy tendency is probably the most obvious manifestation of the relative satisfaction tendency, but nearly all studies of human happiness show that it is related to the state of the person relative to either their past or their peers, not absolute. These relative tendencies cause us great misery or happiness in a very wide variety of objectively different situations and make us poor predictors of our own behavior and feelings.
Commitment & Consistency Bias
As psychologists have frequently and famously demonstrated, humans are subject to a bias towards keeping their prior commitments and staying consistent with our prior selves when possible. This trait is necessary for social cohesion: people who often change their conclusions and habits are often distrusted. Yet our bias towards staying consistent can become, as one wag put it, a “hobgoblin of foolish minds” – when it is combined with the first-conclusion bias, we end up landing on poor answers and standing pat in the face of great evidence.
Hindsight Bias
Once we know the outcome, it’s nearly impossible to turn back the clock mentally. Our narrative instinct leads us to reason that we knew it all along (whatever “it” is), when in fact we are often simply reasoning post-hoc with information not available to us before the event. The hindsight bias explains why it’s wise to keep a journal of important decisions for an unaltered record and to re-examine our beliefs when we convince ourselves that we knew it all along. - Shane Parrish
Managing: “The inclination, after an event has occurred, to see the event as having been predictable, despite there having been little or no objective basis for predicting it.” (related: Pollyanna principle?— “tendency for people to remember pleasant items more accurately than unpleasant ones”) - Gabriel Weinberg
Sensitivity to Fairness
Justice runs deep in our veins. In another illustration of our relative sense of well-being, we are careful arbiters of what is fair. Violations of fairness can be considered grounds for reciprocal action, or at least distrust. Yet fairness itself seems to be a moving target. What is seen as fair and just in one time and place may not be in another. Consider that slavery has been seen as perfectly natural and perfectly unnatural in alternating phases of human existence.
Tendency to Overestimate Consistency of Behavior (Fundamental Attribution Error)
We tend to over-ascribe the behavior of others to their innate traits rather than to situational factors, leading us to overestimate how consistent that behavior will be in the future. In such a situation, predicting behavior seems not very difficult. Of course, in practice this assumption is consistently demonstrated to be wrong, and we are consequently surprised when others do not act in accordance with the “innate” traits we’ve endowed them with.
Influence of Authority
The equally famous Stanford Prison Experiment and Milgram Experiments demonstrated what humans had learned practically many years before: the human bias towards being influenced by authority. In a dominance hierarchy such as ours, we tend to look to the leader for guidance on behavior, especially in situations of stress or uncertainty. Thus, authority figures have a responsibility to act well, whether they like it or not.
Influence of Stress (Including Breaking Points)
Stress causes both mental and physiological responses and tends to amplify the other biases. Almost all human mental biases become worse in the face of stress as the body goes into a fight-or-flight response, relying purely on instinct without the emergency brake of Daniel Kahneman’s “System 2” type of reasoning. Stress causes hasty decisions, immediacy, and a fallback to habit, thus giving rise to the elite soldiers’ motto: “In the thick of battle, you will not rise to the level of your expectations, but fall to the level of your training.”
Survivorship Bias
A major problem with historiography – our interpretation of the past – is that history is famously written by the victors. We do not see what Nassim Taleb calls the “silent grave” – the lottery ticket holders who did not win. Thus, we over-attribute success to things done by the successful agent rather than to randomness or luck, and we often learn false lessons by exclusively studying victors without seeing all of the accompanying losers who acted in the same way but were not lucky enough to succeed. - Shane Parrish
“The logical error of concentrating on the people or things that ‘survived’ some process and inadvertently overlooking those that did not because of their lack of visibility.” - Gabriel Weinberg
“Survivorship bias or survival bias is the logical error of concentrating on the people or things that made it past some selection process and overlooking those that did not, typically because of their lack of visibility. This can lead to false conclusions in several different ways. It is a form of selection bias.” - Wikipedia (James Clear)
Tendency to Want to Do Something (Fight/Flight, Intervention, Demonstration of Value, etc.)
We might term this Boredom Syndrome: Most humans have the tendency to need to act, even when their actions are not needed. We also tend to offer solutions even when we do not enough knowledge to solve the problem.
Understand the power that comes from knowing how you and others are wired.
We are born with attributes that can both help us and hurt us, depending on their application.
