Mini Mental Model Encyclopedia

“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.)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

"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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- Thucydides via 13 Mental Models Every Founder Should Know https://medium.com/the-mission/13-mental-models-every-founder-should-know-c4d44afdcdd

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide via https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful via https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- Philosopher Daniel Dennett's Book Intuition Pumps https://www.amazon.com/Intuition-Pumps-Other-Tools-Thinking/dp/1491518871

"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

Shane Parrish's Farnam Street Mental Model Guide via https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful via https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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'

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

Philosopher Daniel Dennett's Book Intuition Pumps

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.

Philosopher Daniel Dennett's Book Intuition Pumps

How to compose a successful critical commentary: 1. 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.” 2. You should list any points of agreement (especially if they are not matters of general or widespread agreement). 3. You should mention anything you have learned from your target. 4. 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).

Philosopher Daniel Dennett's Book Intuition Pumps

"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."

Philosopher Daniel Dennett's Book Intuition Pumps

"The process in which inconvenient facts are whisked under the rug by intellectually dishonest champions of one theory or another."

Philosopher Daniel Dennett's Book Intuition Pumps

"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.”"

Philosopher Daniel Dennett's Book Intuition Pumps

"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."

Philosopher Daniel Dennett's Book Intuition Pumps

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.

Philosopher Daniel Dennett's Book Intuition Pumps

"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.) "

Philosopher Daniel Dennett's Book Intuition Pumps

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.

Philosopher Daniel Dennett's Book Intuition Pumps

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.

Philosopher Daniel Dennett's Book Intuition Pumps

“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)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- James Clear Mental Models Overview https://jamesclear.com/mental-models

“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.”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“A wide range of cognitive biases that influence the responses of participants away from an accurate or truthful response.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“Changes that the act of observation will make on a phenomenon being observed.” (related: Schrödinger’s cat)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.

Shane Parrish's Farnam Street Mental Model Guide

"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." —Shane Parrish ---- "When you focus on improving the same product area, the amount of customer value created over time will diminish for every unit of effort. How it’s useful Assuming you are effectively iterating the product based on customer feedback and research, you will eventually hit a point where there’s just not that much you can do to make it better. It’s time for your team to move on and invest in something new." — Brandon Chu

Shane Parrish's Farnam Street Mental Model Guide - https://www.farnamstreetblog.com/mental-models/ ----- Product Management Mental Models for Everyone - https://blackboxofpm.com/product-management-mental-models-for-everyone-31e7828cb50b

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.

Shane Parrish's Farnam Street Mental Model Guide

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).

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

"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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Philosopher Daniel Dennett's Book Intuition Pumps https://www.amazon.com/Intuition-Pumps-Other-Tools-Thinking/dp/1491518871

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.

Shane Parrish's Farnam Street Mental Model Guide

"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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- James Clear Mental Models Overview https://jamesclear.com/mental-models https://rationalpov.gitbooks.io/mental-model/content/discipline_engineering,backup_systemredundancy.html

"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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- James Clear Mental Models Overview https://jamesclear.com/mental-models

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.

Shane Parrish's Farnam Street Mental Model Guide

"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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ ---  Robert Metcalfe via 13 Mental Models Every Founder Should Know https://medium.com/the-mission/13-mental-models-every-founder-should-know-c4d44afdcdd --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

"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)

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- James Clear Mental Models Overview https://jamesclear.com/mental-models

"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)

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- James Clear Mental Models Overview https://jamesclear.com/mental-models

"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)

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- James Clear Mental Models Overview https://jamesclear.com/mental-models

"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 )

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d" --- James Clear Mental Models Overview https://jamesclear.com/mental-models

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 (/kəˈtælɪsɪs/) 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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ ---- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- James Clear Mental Models Overview https://jamesclear.com/mental-models https://en.wikipedia.org/wiki/Catalysis

"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)

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d" --- James Clear Mental Models Overview https://jamesclear.com/mental-models

"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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d"

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.

Shane Parrish's Farnam Street Mental Model Guide

“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)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- James Clear Mental Models Overview https://jamesclear.com/mental-models"

“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)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

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)

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d" --- James Clear Mental Models Overview https://jamesclear.com/mental-models

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- James Clear Mental Models Overview https://jamesclear.com/mental-models --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.”

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d"

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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)

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- James Clear Mental Models Overview https://jamesclear.com/mental-models

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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)

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- James Clear Mental Models Overview https://jamesclear.com/mental-models

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)

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- James Clear Mental Models Overview https://jamesclear.com/mental-models

A market that tends towards one dominant player. (related: lock-in; monopoly; monopsony)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“Economic platforms having two distinct user groups that provide each other with network benefits.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“A cost that must be incurred by a new entrant into a market that incumbents don’t or haven’t had to incur.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“The ability of a firm to profitably raise the market price of a good or service over marginal cost.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“the advantage gained by the initial (“first-moving”) significant occupant of a market segment.” (related: Why now?)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

“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.”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

Using strategies and tactics that worked successfully in the past, but are no longer as useful.

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“A means of leaving one’s current situation, either after a predetermined objective has been achieved, or as a strategy to mitigate failure.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“The belief that military success can only be achieved through the direct physical presence of troops in a conflict area.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“A diplomatic policy of making political or material concessions to an enemy power in order to avoid conflict.” (related: Danegeld, extortion)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“A poor strategy that wins a lesser (or sub-) objective but overlooks and loses the true intended objective.” (related: sacrifice play)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"Six Sigma (6σ) 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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course https://www.youtube.com/watch?v=H8n7SRF_3SI&index=22&list=PLfeNPtL-aoavLTWo_UMtQgneBpnmyyqH- --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

"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

Scott Page Model Thinking MOOC Course

Ray Dalio's Book Principles

1. One of the most important decisions you can make is who you ask questions of. 2. Don’t believe everything you hear. 3. Everything looks bigger up close. 4. New is overvalued relative to great. 5. Don’t oversqueeze dots.

Ray Dalio's Book Principles

1. Keep in mind both the rates of change and the levels of things, and the relationships between them. 2. Be imprecise. 3. Remember the 80/20 Rule and know what the key 20 percent is. 4. Be an imperfectionist.

Ray Dalio's Book Principles

1.Use the terms “above the line” and “below the line” to establish which level a conversation is on. 2. Remember that decisions need to be made at the appropriate level, but they should also be consistent across levels.

Ray Dalio's Book Principles

Ray Dalio's Book Principles

1. Raising the probability of being right is valuable no matter what your probability of being right already is. 2. Knowing when not to bet is as important as knowing what bets are probably worth making. 3. The best choices are the ones that have more pros than cons, not those that don’t have any cons at all. ---- Predicting the future is imperfect. Instead, all decisions create probabilities of multiple future outcomes. The probability-weighted sum of these outcomes is the expected value of a decision. When considering impact of a project, map out all possible outcomes and assign probabilities. Outcome variability typically includes the probability it takes longer than expected and the probability that it fails to solve the customer problem. Once you lay out all the outcomes, do a probability-weighted sum of the value of the outcomes and you’ll have a better picture on the return you will get on the investment. — Brandon Chu

Ray Dalio's Book Principles - https://www.amazon.com/dp/B071CTK28D/ref=chrt_bk_rd_nf_4_ci_lp ---- Product Management Mental Models for Everyone - https://blackboxofpm.com/product-management-mental-models-for-everyone-31e7828cb50b

1. All of your “must-dos” must be above the bar before you do your “like-to-dos.” 2. 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. 3. Don’t mistake possibilities for probabilities.

Ray Dalio's Book Principles

Ray Dalio's Book Principles

Ray Dalio's Book Principles

Ray Dalio's Book Principles

Ray Dalio's Book Principles

Ray Dalio's Book Principles

“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?)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

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.”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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.” —Gabriel Weinberg ------ "Related to diminishing returns, the local maxima is the point where incremental improvements creates no customer value at all, forcing you to make a step change in product capabilities. How it’s useful This mental model is tightly related to diminishing returns, with the addition of hitting a limit where it literally makes no material difference to keep improving something. Iteration now serves no purpose, and and the only way to progress is to innovate. This concept was recently popularized by Eugene Wei’s viral post Invisible Asymptotes, which covers an example like this that Amazon foresaw which led them to create Prime." — Brandon Chu

Gabriel Weinberg's Mental Models I Find Repeatedly Useful - https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d ----- Product Management Mental Models for Everyone - https://blackboxofpm.com/product-management-mental-models-for-everyone-31e7828cb50b

“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”)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“People tend to heavily weigh their judgments toward more recent information, making new opinions biased toward that latest news.”

Gabriel Weinberg's Mental Models I Find Repeatedly Useful

“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)

Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- James Clear Mental Models Overview https://jamesclear.com/mental-models https://en.wikipedia.org/wiki/Loss_aversion

1. If you can’t successfully do something, don’t think you can tell others how it should be done. 2. Remember that everyone has opinions and they are often bad.

Ray Dalio's Book Principles

1. Think about people’s believability in order to assess the likelihood that their opinions are good. 2. 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. 3. If someone hasn’t done something but has a theory that seems logical and can be stress-tested, then by all means test it. 4. Don’t pay as much attention to people’s conclusions as to the reasoning that led them to their conclusions. 5. Inexperienced people can have great ideas too, sometimes far better ones than more experienced people. 6. Everyone should be up-front in expressing how confident they are in their thoughts.

Ray Dalio's Book Principles

1. It’s more important that the student understand the teacher than that the teacher understand the student, though both are important. 2. 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.

Ray Dalio's Book Principles

1. If you ask someone a question, they will probably give you an answer, so think through to whom you should address your questions. 2. Having everyone randomly probe everyone else is an unproductive waste of time. 3. Beware of statements that begin with “I think that . . .” 4. Assess believability by systematically capturing people’s track records over time.

Ray Dalio's Book Principles

1. Know when to stop debating and move on to agreeing about what should be done. 2. Use believability weighting as a tool rather than a substitute for decision making by Responsible Parties. 3. Since you don’t have the time to thoroughly examine everyone’s thinking yourself, choose your believable people wisely. 4. When you’re responsible for a decision, compare the believability-weighted decision making of the crowd to what you believe.

Ray Dalio's Book Principles

1. Communications aimed at getting the best answer should involve the most relevant people. 2. 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. 3. Recognize that you don’t need to make judgments about everything.

Ray Dalio's Book Principles

Ray Dalio's Book Principles

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

"Rule-based modeling is a modeling approach that uses a set of rules that indirectly specifies a mathematical model." - Wikipedia

Scott Page Model Thinking MOOC Course

"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

Scott Page Model Thinking MOOC Course

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

The three major psychological findings that fall under Representativeness, also defined by Kahneman and his partner Tversky, are:

Shane Parrish's Farnam Street Mental Model Guide

An unconscious failure to look at past odds in determining current or future behavior.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.

Shane Parrish's Farnam Street Mental Model Guide

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.”

Shane Parrish's Farnam Street Mental Model Guide

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)

Shane Parrish's Farnam Street Mental Model Guide https://www.farnamstreetblog.com/mental-models/ --- Gabriel Weinberg's Mental Models I Find Repeatedly Useful https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d --- James Clear Mental Models Overview https://jamesclear.com/mental-models https://en.wikipedia.org/wiki/Survivorship_bias

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.

Shane Parrish's Farnam Street Mental Model Guide

We are born with attributes that can both help us and hurt us, depending on their application.

Ray Dalio's Book Principles

Ray Dalio's Book Principles

1.Realize that the conscious mind is in a battle with the subconscious mind. 2. Know that the most constant struggle is between feeling and thinking. 3. Reconcile your feelings and your thinking. 4. Choose your habits well. 5. Train your “lower-level you” with kindness and persistence to build the right habits. 6. Understand the differences between right-brained and left-brained thinking. 7. Understand how much the brain can and cannot change.

Ray Dalio's Book Principles

1.Introversion vs. extroversion. 2. Intuiting vs. sensing. 3. Thinking vs. feeling. 4. Planning vs. perceiving. 5. Creators vs. refiners vs. advancers vs. executors vs. flexors. 6. Focusing on tasks vs. focusing on goals. 7. Workplace Personality Inventory. 8. Shapers are people who can go from visualization to actualization.

Ray Dalio's Book Principles

Manage yourself and orchestrate others to get what you want.

Ray Dalio's Book Principles

"Linear models describe a continuous response variable as a function of one or more predictor variables. They can help you understand and predict the behavior of complex systems or analyze experimental, financial, and biological data. Linear regression is a statistical method used to create a linear model." - MathWorks

Scott Page Model Thinking MOOC Course

"A special case of categorical modeling is logistic regression. You have to use this model when the dependent variable is ordinal. A page devoted to this problem also comes up shortly. You could also turn simple models like these around and analyze them as ANOVAs, but you shouldn't."- Sportsci.org

Scott Page Model Thinking MOOC Course

"Using the linear models, you can draw a line through data and use that line to explain some of the variation in the data. Now typically the world isn't gonna be perfectly linear. There's going to be lots of extra variation left over, but there's a question of how much of that variation did the line explain. In addition to explaining the variation, the line tells us something about the relationship between our independent variable, x and our dependent variable, y. In particular, we learn the sine on x, like does y increase in x or decrease in x, and we also learn something about the magnitude, so how much does. Each one unit increase of x increased the value of y. So what this linear model can do is help us understand something about data we see in the real world."- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"How do you draw the best possible line through the data? ... it's a lot of data out there. One thing you can do is you can fit that data to linear models. What linear models will do is they'll explain some percentage of the variation. Maybe a lot, maybe a little. These linear models will also tell us the sign and magnitude of coefficients. So it'll tell us whether a variable. It's got a positive effect but it's got a negative effect. And also tell a sort of how big that effect is, and that allows us to make policy choices. You know, investing in things like teacher quality as opposed to class size because they have a larger effect. This is what I call big coefficient thinking." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"The R-squared of the regression is the fraction of the variation in your dependent variable that is accounted for (or predicted by) your independent variables. (In regression with a single independent variable, it is the same as the square of the correlation between your dependent and independent variable.)" - Princeton University Library

Scott Page Model Thinking MOOC Course

"The world may be nonlinear, and we've got techniques that help us sort of understand linear functions. So here's the first thing we can do. The first thing we can do is we can just approximate our nonlinear function with a linear function so we've got this nonlinear function here right, but we're just gonna do a three linear function to approximate it. So that's the best possible approximation. And so what we can do is we can say I have a model. So in this case I may have a model that says this is my functional form, this is what should happen. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"The big coefficient: If we have a simple linear regression model, we have some equation like Y = a1 x1 + a2 x2 + b, right? And x1 and x2 are called the independent variables, and y's the dependant variable. So, for example, Y might be sales of a product. And x1 might be advertising in magazines and x2 might be advertising in television. Now we can look at these two coefficients, a1 and a2 and figure out which one's bigger. And what that's telling us is we get sort of more bang for the buck from advertising on magazines or from advertising on television. If it's television, if a2 is bigger than a1, then that's where we spend our money. So the idea is you put your assets, you put your resources on the variables that have the bigger coefficients. So this big coefficient thinking has led to something that people like to call Evidence Based blank. So there's Evidence Based Medicine. What you do is you look at all sorts of different treatments that have been tried on patients..."- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"The tipping point is an expression used in epidemiology that was taken by Malcolm Gladwell, a New York Times writer, and applied to other areas of life—including business—in his 2000 book “The Tipping Point”. The subtitle, “How Little Things Can Make a Big Difference”, explains more clearly what the whole thing is about. In epidemiology the tipping point is that moment when a small change tips the balance of a system and brings about a large change; for example, when the normal spread of influenza throughout a population suddenly turns into an epidemic. In recent years the language of epidemiology has spread (like a virus?) within business. Managers talk about viral marketing (see article), the infectious enthusiasm of their teams, and “outbreaks” of corporate greed—and even, as was reported once about JetBlue, an American low-cost airline, an “outbreak of passenger abuse”. A lot of this language owes its spread to the influence of the internet, where viruses are common and where dormant information can sometimes erupt suddenly and infect us all." - Economics

Scott Page Model Thinking MOOC Course

"Percolation theory deals with fluid flow (or any other similar process) in random media. If the medium is a set of regular lattice points, then there are two main types of percolation: A site percolation considers the lattice vertices as the relevant entities; a bond percolation considers the lattice edges as the relevant entities. These two models are examples of discrete percolation theory, an umbrella term used to describe any percolation model which takes place on a regular point lattice or any other discrete set, and while they're most certainly the most-studied of the discrete models, others such as AB percolation and mixed percolation do exist and are reasonably well-studied in their own right." - WolframWorld

Scott Page Model Thinking MOOC Course

"In the diffusion model, everybody just gets it. There's no, you know, sort of getting cured. So this thing of this is diffusion of information through a system or disease that everybody's just gonna get. Alright? So the diffusion method sorta works as follows. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"the SIS model, for "susceptible, infected and then susceptible". That is, you're susceptible to some disease, then you get infected, and then after you get infected you're cured, but then you can become susceptible again if the disease is mutated in some way, like a flu virus. There's also something called the SIR model, where after you become infected then you're recovered, then there's no chance of getting the disease again. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"There are contextual tips where the environment changes. Once the environment changes, then the system is likely to move from one state to another once somebody lights the match. There's tips within class, where you move from one equilibrium to a new equilibrium. And there's tips between class, where a sy-, where a system tips from an equilibrium to, you know, a much more complex state, or a periodic state. So that's a simple taxonomy of tipping points. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"So one way to think about tipping points in the measure we're going to introduce is gonna depend on that idea. That the uncertainty goes away. Initially, there was some uncertainty. It could go left or right, but after the tip, we know where it's gonna go. So we're gonna measure tipsiness by reductions in uncertainty. So, to get there we first need a measure of uncertainty. Way to think about that is you want to think about changes in outcomes. " - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"One of the surprising results of that model of economic growth is going to be that there are limits, that without innovation, growth stops. So we will move from that simple model to something called a solo growth model. The solo growth model allows for there to be innovation and shows how innovation has this sort of multiplier effect on our collective well-being and why innovation is so important. And then we'll talk a little bit about some extensions, in particular we'll talk about once we've got this model how do we use it to think about why some countries. Successful in other countries are, and really what, oh, enables. Growth to continue over time. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"Exponential growth is exhibited when the rate of change—the change per instant or unit of time—of the value of a mathematical function is proportional to the function's current value, resulting in its value at any time being an exponential function of time, i.e., a function in which the time value is the exponent. Exponential decay occurs in the same way when the growth rate is negative. In the case of a discrete domain of definition with equal intervals, it is also called geometric growth or geometric decay, the function values forming a geometric progression. In either exponential growth or exponential decay, the ratio of the rate of change of the quantity to its current size remains constant over time." - Wikipedia

Scott Page Model Thinking MOOC Course

"if we write down a Simple Model of Growth - Economic Growth that involves investing money in new machines. That there are limits to growth. That the model is going to max out at this point, when the number of machines lost to depreciation is exactly offset by the number of machines that we invested in the previous period. If we start with no machines, growth is going to happen really really fast initially, but then it's going to fall off when it reaches this equilibrium level. So to get sustained growth, that's going to require new technologies - new innovations. And that's where we are going next. We're going to construct Solow's Growth Model which includes this Innovation Parameter. " - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"we just took in a very simple growth model and in that growth model we saw that well, growth stopped, right. Once we got to 144 machines and an output of 120, we no longer got any growth. So we use that very simple model to get at. A really important fact, that without innovation, if technology stays fixed, growth will stop. Now, sure the labor supply could get bigger, we could have more workers or something like that. But holding the amount of labor fixed and holding that technology fixed, if we've got a fixed savings rate, and a fixed rate of depreciation, there's no more growth at some point. We're gonna go up, up, up, up, up, and then stop. Well. That hasn't been human experience right." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"One type of growth, what we're seeing in China now and what we saw in Japan post war. And what we saw in Europe and the United States post war, is growth that occurs through capital accumulation. Another type of growth, is what we're, which is what we see in the United States and Japan and Europe now, but not in China, occurs from technological advances, not from buildup of capital. And as you advance technology and you increase that A term, then it makes sense to. Buy more capital, but different types of capital and that's what drives growth. " - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"We also learned that absent innovation growth tails off right it just stops, so we needs a constant driver of innovation. And, the we also saw [inaudible] in this last lecture that's not so easy. It'd be easy to say that all we need is innovation, well to maintain that innovation you need secure property rights. You need people who have incentives to invest in things like machines and also invest in new technologies. And so to get that you need a strong central government. But the central government can be so strong that it starts extracting stuff. But if it extracts stuff, that is essentially the same effect as lowering the technology. And at the third, and third, that government can't necessarily protect industry. Now sometimes it can. There's cases where it's gonna make sense to protect industries, but. One of the things that's going to drive growth to innovation is this process of creative destruction. So the model tells us that sometimes, we may have to, you know throw out our vinyl records and move to cassettes, and then throw out those cassettes and move to c.d.'s, and then throw out those c.d.'s and you just listen to digital music. There's going to be these processes of creative destruction that drive the growth and they're representative of innovation, of what makes us all better off. Okay. Thank you."- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

" The big idea is this: I have some solution from one problem, you have a solution from a different problem, and sometimes I can take your solution and combine it with my solution, and come up with something even better. So, the thing about sophisticated products— like a house, an automobile, or even a computer— that consists of all sorts of solutions to sub-problems. And we are going to see how by recombining solutions to sub-problems we get ever better solutions, and that is really a big driver of innovation. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"hat a perspective is going to be is it’s going to be a representation of all possible solutions. So it’s some encoding of the set of possible solutions to the problem. Once we have that encoding of the set of possible solutions, then we can create our landscape by just assigning a value to each one of those solutions. And that will give us a landscape picture like you saw before. Now most of us are familiar with perspectives, even though we don’t know it. Let me give some examples. Remember when we took seventh grade math? We learned about how to represent a point, how to plot points. And we typically learned two ways to do it. The first way was Cartesian coordinates. So given a point, we would represent it by and an X and a Y value in space. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"A heuristic technique (/hjuːˈrɪstɪk/; Ancient Greek: εὑρίσκω, "find" or "discover"), often called simply a heuristic, is any approach to problem solving, learning, or discovery that employs a practical method not guaranteed to be optimal or perfect, but sufficient for the immediate goals. Where finding an optimal solution is impossible or impractical, heuristic methods can be used to speed up the process of finding a satisfactory solution. Heuristics can be mental shortcuts that ease the cognitive load of making a decision. Examples of this method include using a rule of thumb, an educated guess, an intuitive judgment, guesstimate, stereotyping, profiling, or common sense." - Wikipedia

Scott Page Model Thinking MOOC Course

"The team can only get stuck at a solution that's a local optima for everyone on the team. That means the team has to be better than the people in it. So what we want, right, you want people with different local optima. You want people to get stuck in different places. Well how do we get it? We don't. We've already looked at this twice, right? We looked at it first perspective perspectives. So if you coat it this way and I coat it this way, then we're going to get stuck in different places. We also want people with different heuristics. If I look in this direction and this direction, and you look in this direction and this direction, and we add us together, we look in all four of those directions. So what we want, is we want diverse perspectives, and we want diverse heuristics. And that diversity will give us different local optima, and those different local optima will mean that we take the intersections, and we end up with better points. That's sort of the big idea."

Scott Page Model Thinking MOOC Course

"Recombination is incredibly powerful and if we have a few solutions. Or futuristic. We can combine those to create evermore and that may be the real driving force behind innovation in the economy, is that when we come up with a solution we can then recombine it with all sorts of other solutions and that leads to ever and ever more innovation." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

Ray Dalio's Book Principles

Create great decision-making machines by thinking through the criteria you are using to make decisions while you are making them.

Ray Dalio's Book Principles

1. Put yourself in the position of pain for a while so that you gain a richer understanding of what you’re designing for. 2. Visualize alternative machines and their outcomes, and then choose. 3. Consider second- and third-order consequences, not just first-order ones. 4. Use standing meetings to help your organization run like a Swiss clock. 5. Remember that a good machine takes into account the fact that people are imperfect.

Ray Dalio's Book Principles

Understand the power of the “cleansing storm.”

Ray Dalio's Book Principles

1. Build your organization from the top down. 2. Remember that everyone must be overseen by a believable person who has high standards. 3. Make sure the people at the top of each pyramid have the skills and focus to manage their direct reports and a deep understanding of their jobs. 4. In designing your organization, remember that the 5-Step Process is the path to success and that different people are good at different steps. 5. Don’t build the organization to fit the people. 6. Keep scale in mind. 7. Organize departments and sub-departments around the most logical groupings based on “gravitational pull.” 7. Make departments as self-sufficient as possible so that they have control over the resources they need to achieve their goals. 8. Ensure that the ratios of senior managers to junior managers and of junior managers to their reports are limited to preserve quality communication and mutual understanding. 9. Consider succession and training in your design. 10. Don’t just pay attention to your job; pay attention to how your job will be done if you are no longer around. 11. Use “double-do” rather than “double-check” to make sure mission-critical tasks are done correctly. 12. Use consultants wisely and watch out for consultant addiction.

Ray Dalio's Book Principles

1. Involve the person who is the point of the pyramid when encountering cross-departmental or cross-sub-departmental issues. 2. Don’t do work for people in another department or grab people from another department to do work for you unless you speak to the person responsible for overseeing the other department. 3. Watch out for “department slip.”

Ray Dalio's Book Principles

1. Don’t expect people to recognize and compensate for their own blind spots. 2. Consider the clover-leaf design.

Ray Dalio's Book Principles

1. Don’t put the expedient ahead of the strategic. 2. Think about both the big picture and the granular details, and understand the connections between them.

Ray Dalio's Book Principles

1.Investigate and let people know you are going to investigate. 2. Remember that there is no sense in having laws unless you have policemen (auditors). 3. Beware of rubber-stamping. 4. Recognize that people who make purchases on your behalf probably will not spend your money wisely. 5. Use “public hangings” to deter bad behavior.

Ray Dalio's Book Principles

1. Assign responsibilities based on workflow design and people’s abilities, not job titles. 2. Constantly think about how to produce leverage. 3. Recognize that it is far better to find a few smart people and give them the best technology than to have a greater number of ordinary people who are less well equipped. 4. Use leveragers.

Ray Dalio's Book Principles

Ray Dalio's Book Principles

"In probability theory, a Markov model is a stochastic model used to model randomly changing systems.[1] It is assumed that future states depend only on the current state, not on the events that occurred before it (that is, it assumes the Markov property). Generally, this assumption enables reasoning and computation with the model that would otherwise be intractable. For this reason, in the fields of predictive modelling and probabilistic forecasting, it is desirable for a given model to exhibit the Markov property." - Wikipedia

Scott Page Model Thinking MOOC Course

"For example, in the case of the alert and bored students. People are moving from alert to bored. But if I think in terms of probabilities, that probability is staying fixed. That probability is staying fixed at 5/9. People are moving around, but the probability's staying fixed. That's why this is sometimes called a statistical equilibrium, 'cause the statistic p, the probability of someone being alert, is the thing that doesn't change. Okay, pretty involved, right? What we did is, we wrote down the Markov transition matrix. And we showed how using that matrix, we could solve for an equilibrium. And we saw, at least in the simple example of alert and bored students, that the process went to an equilibrium, and it was fairly straightforward to solve for. What we want to do next is we want to do [a] slightly more sophisticated model that involves multiple states instead of just two, involves three states, and we'll see how that process also converges to an equilibrium. " - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"To explain this model its' best to give the example of countries. Countries that can be free, partly free or run by dictators (not free). Start from a 2 state democracy model -> 5% of democracies switch to dictatorship and 20% the opposite. Trend towards freedom, but only 2/3 will be free unless the transition probabilities change. You can get a line chart or a bar chart to compare model and actual, and they are very similar! And line chart patterns look very similar!!" - Model Thinking Section 10: Markov Models

Scott Page Model Thinking MOOC Course

" Markov convergence theorem that says the process is going to go to a unique equilibrium. If you rule out simple cycles, and just assume finite states, fixed probabilities, can get from any state to any other, then you get an equilibrium. So this is the Markov convergence theorem. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"Markov process is a fixed set of states, fixed transition probabilities. You can get from any one state to any other, and then you get an equilbrium. So that equilibrium doesn't depend on where you start, it doesn't depend on interventions. And it doesn't depend on history in any way. The model is really powerful. And so if you wanna argue history matters. Or if you wanna argue interventions matter. If someone gonna argue that this isn't a transition, that this isn't a Markov process. Or that you've gotta argue that you're changing the transition probabilities. Now that isn't impossible. "

Scott Page Model Thinking MOOC Course

"In the theory of ordinary differential equations (ODEs), Lyapunov functions are scalar functions that may be used to prove the stability of an equilibrium of an ODE. Named after the Russian mathematician Aleksandr Mikhailovich Lyapunov, Lyapunov functions (also called the Lyapunov’s second method for stability) are important to stability theory of dynamical systems and control theory. A similar concept appears in the theory of general state space Markov chains, usually under the name Foster–Lyapunov functions." - Wikipedia

Scott Page Model Thinking MOOC Course

"Simple model is, there's a min, if the process moves, it goes down by some amount each time, therefore the process has to stop. We use that model to say, let's think about how a city organizes itself. " -Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"We've got that, without externalities, or with only positive externalities in the case of finding a maximum, what you're gonna get is that, it's easy to construct a Lyapunov function, and boom, you get there. The system's gonna stop. But if there's these negative externalities, I'm making myself happier but I'm gonna make other people less happy, then the system could continue to churn, and we may not be able to say whether or not the system's gonna go to equilibrium or whether it's gonna be complex. But we do have some intuitions. And those intuitions suggest that markets, simple markets trading goods should go to equilibrium, should constantly improve. People choosing routes should constantly improve. But things like international alliances or coalitions within political parties, or possibly even dating, that these things may be more complex, and certainly that's how it appears out there in the real world."-Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"What we learn is that it's at least possible to put a Lyapunov function on a process and have it stop at somewhere less than the optimal point. Doesn't have to stop at the optimal point, it could stop below. That's what we're seeing here. So we've answered two important questions. The first one is: Okay, we know it goes to equilibrium, can we say how fast? And the answer is yes. And the better bound we get on k, and the better bound we get on the max, the more accurately we can put a restriction on how fast, how long it's going take. So, we can put a tighter bound on how long it's going to take, if we can estimate k accurately, and if we can estimate the maximum value accurately. We also learned that it can stop a lot faster than that, because of the fact that the process may not get to that optimum value." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"when you think about a model, when you think about a process like the Lyapunov process, right? Lyapunov functions. What you've got is, you can say, hey, there some cases like the case of chairs, a pure exchange market, this thing works great. And we can just can say, boom, it's gonna stop, we're fine. There's other things like the office process, that unless you know a lot about the nature of the externalities, you can't tell. It could be, oh yeah this thing's gonna go right to equilibrium. Or it could be that, whoa it's gonna churn a long time. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"By looking at Lyapunov functions and comparing it to some of our other models, like Markov processes and the Langton model, we begin to see how having multiple models in our heads enables us to understand some of the richness we see out there in the world, and actually have deeper understandings of the processes we see. To understand, like, this process is going into equilibrium because it's a Markov process, and it's a stochastic equilibrium. And this process, an exchange market, is going to equilibrium because of the fact that it's a Lyapunov function and happiness is going up. So what you get is different processes in that equilibrium for very different reasons. And having different tools for understanding why equilibrium exists is [a] very useful thing for making sense of the world."- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"What do we mean by culture? Well, typically when you think about culture, you mean differences between countries, differences between groups of interacting people. So people from Japan act differently than people from Germany, and people from Germany act and believe and behave differently than people from El Salvador. So think about just differences between countries. Now in order to, for there to be differences Between the people within a country or nation state or even a small group, there have to be similarities within. So it means that there have to be similar actions within a group. And that's where the coordination game is gonna enter. And in addition, when we think about cultural behavior, we think of it being "interesting". I mean, interesting sort of, [inaudible] what I mean is, is that it can be suboptimal in a way. It can be, if you sat down and efficiently said, what should these people be doing? Maybe what we're doing doesn't make sense. And that'll be true of people from every nation or group. We say, look at the behavior and think, that seems different than how I would do it, or different than what seems maybe the most efficient way to do it. So by culture behavior, we're gonna mean behavior as well that maybe doesn't look optimal from an outsider's perspective, but possibly viewed within that culture, it makes a lot of sense. " - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

" The reason we care about culture, and here's a quote from Ken Arrow, who's a Nobel Prize winning economist, is when you think about how the economy works, how political systems work, how society works, it's all mediated through these social exchanges, so as Arrow says in this quote, that a lot of economic backwardness can be explained by lack of mutual confidence, so lack of trust. So one of the things that we've seen in cultures is different levels of trust. And different levels of trust have huge implications for how well political, economic, social, and religious institutions are gonna perform in terms of meeting the needs of the citizens." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"Pure coordination games - games in which players have identical preferences over the set of possible outcomes. Focal points, even when they arise as framing effects based on the labelling of options, are intuitively obvious choices, and experimental evidence shows that decision makers often coordinate successfully by choosing them. " - Journal of Economics Strategy

Scott Page Model Thinking MOOC Course

"what Axelrod's model gives us, which is really sort of fascinating, is, he makes this assumption that says: We've all got these traits. We look to our neighbors. If they're like us, we tend to interact with them. If they're not like us, we tend not to. And what he ends up getting is these distinct cultures with thick boundaries. And these thick boundaries means vast differences between the cultures. Now the thick boundaries emerge because of the fact that if there weren't a thick boundary, then what would happen is, I would interact with that person and would become more similar, and the boundary would disappear. So Axelrod's model shows how in a social space, we can get distinct cultures on multi dimensions, and those boundaries can be self-reinforcing. People don't interact across the boundaries, and the cultures remain disparate. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"There's two people, they meet, they each have this vector of actions or beliefs or attitudes, whatever you want to call them. And when the leader and follower meet, they look at the second dimension, let's say the follower says, well you're a three, I'm a one, I'll switch that to a three. That's what coordination is, you switch your action. You put the ketchup where your friends put the ketchup. What would consistency be? Well, consistency would just be this: you look at yourself, now these values, 5, 3, 1, 4, have meaning. Five is close to five, four is close to four. And you look and you think, I'm five on the first, I'm one on the second. And that doesn't make any sense, so you switch and become five on both. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

1. Fail well. 2. Don’t feel bad about your mistakes or those of others. Love them!

Ray Dalio's Book Principles

Get over “blame” and “credit” and get on with “accurate” and “inaccurate.”

Ray Dalio's Book Principles

Ray Dalio's Book Principles

1. Be self-reflective and make sure your people are self-reflective. 2. Know that nobody can see themselves objectively. 3. Teach and reinforce the merits of mistake-based learning.

Ray Dalio's Book Principles

Ray Dalio's Book Principles

"Path dependence is the idea that decisions we are faced with depend on past knowledge trajectory and decisions made, and are thus limited by the current competence base. In other words, history matters for current decision-making situations and has a strong influence on strategic planning." -Financial Times

Scott Page Model Thinking MOOC Course

"An urn model is either a set of probabilities that describe events within an urn problem, or it is a probability distribution, or a family of such distributions, of random variables associated with urn problems." - Wikipedia

Scott Page Model Thinking MOOC Course

"One of the simplest models in probability theory. A description of an urn model is as follows: Consider some vessel — an urn — with black and white balls. One ball is drawn at random from the urn, and then it is returned to the urn together with cc balls of the same colour as the ball drawn and dd balls of the other colour. After mixing the balls in the urn, the procedure is repeated a certain number of times. It is assumed that initially the urn contains a>0a>0 white and b>0b>0 black balls. The numbers cc and dd, the parameters of the urn model, may also be negative." - Encycopedia of Mathmatics

Scott Page Model Thinking MOOC Course

" when we talk about path dependence, what we're talking about is the sequence of previous events influencing not only outcome in this period, but possibly the long run equilibrium. So our definition of path dependence is that the outcome probabilities depend on the sequences of past outcomes. So in the case of a path dependent outcome where you see even the outcome depends on it."- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"We said that one thing that people often equate with path dependence is increasing returns and we've shown that although maybe empirically the case that a lot of path dependence does come from increasing returns, logically they're completely separate. You can have path dependence without increasing returns, you can have increasing returns and not get path dependence. We also talked about how one big cause of path dependence may be externalities. Inner dependencies between choices, especially big choices like public projects, and those externalities, whether they're positive or negative. Can create that dependence. But the negative [inaudible] may have a larger effect. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"A tipping point was a single instance in time where, where that long, long equilibrium was gonna be suddenly changed drastically. So think about path depended. Path dependent means what happens along the way. As you move along that path, how does that effect where we're likely to end up. So each step may have a small effect, but it's the accumulation of those steps that has the difference. With tipping points, everything sort of moves along in expected ways but not getting a lot of information. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

" One is, the internet has allowed us to make all sorts of network connections with people, and to give us graphs of those networks. We're just more aware that networks exist. Another thing is that we get more and more data on networks. We're getting to see the importance of networks for all sorts of things, Whether it's scientific innovation, whether it's the spread of ideas, Whether it's the polarization of critical thought, And whether it's the rise of. With a decrease in smoking with a rise in social trends, You can see these effects through networks using new techniques. What we want to do in this set of lectures is understand a little bit about how networks work and why they're so important. So first thing I just want to convince you the networks have become a hot topic. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"We can think of networks as having nodes, edges, degrees, path length, and connected in a cluster coefficient. So this is a language for describing different network structures....When you look at the graphs or network, there's structure to graphs. We could measure degree which is on average how many nodes is another node connected to. We could talk about path length, which is how far is it from one node to another node. We could talk about connectedness, is the whole graph connected. And we can talk about clustering coefficient, which is how many triangles, of the possible triangles, how many of those are filled in. Now these are statistical measures."- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

" The network structure's gonna be something that emerges through these micro-level interactions.The first one's gonna be random connections, where each node and randomly decided to connect to other nodes. The second one is gonna be a small worlds model. And the is, is gonna work as follows. Each person is gonna have some friends that are, sort of, belong to a clique. They're sort of nearby. And then some friends that are random, that they randomly connect to. So we're gonna start out by having people connected to just people near them. And then assume that they sort of rewire, in a way, and randomly connect to some people who are further away in social space. ?Cause this is what a lot of social networks look like. And the last thing we're gonna do is we're gonna look at something called a preferential attachment network. And this has been used to describe the internet. And the world wide web. And the idea here is the following. It's that you're more likely to connect to nodes that are more connected. So, that's true certainly in the world wide web." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"What are the functionalities of this sort of network? Look, here's an interesting functionality. Suppose I think about random node failures. So suppose nodes on the internet are gonna fail randomly. Well most nodes are connected to very few. Most nodes are over here. So that means if you have random failure, this node is gonna be incredibly robust. So no one said, hey, let's. Make connections in such a way that makes the internet robust, but the fact that it emerges from the structure of the network. What about targeted failures? What if you want to shut down internet? What if you want to target failure, then you go after these, lots and lots of connections. So although the internet is really robust in handling failure but it's not at all robust to targeted failure. That's a functionality that emerges from the preferential [inaudible] rule. Nobody built them in. They just happened. So what have we learned? We learned that it's sort of fun to talk about networks. There's pictures but we can really unpack it in a formal way by constructing models and networks. Cause models and networks can focus on the logic. How does the network form. The structure. What are the statistical properties within networks? And then finally the functionality. What does the network do? Right. Does the network robust to random failures or is it robust to strategic failures? Does it give us six degrees of separation or 400 degrees of separation? Is it connected or non-connected? So there's all these functionalities that emerge from the network structure. And the network structure in turn is a result of. The individual logic for how people make connections, or how firms make connections, or how. " - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"A random walk is a mathematical object, known as a stochastic or random process, that describes a path that consists of a succession of random steps on some mathematical space such as the integers. An elementary example of a random walk is the random walk on the integer number line, {\displaystyle \mathbb {Z} } \mathbb {Z} , which starts at 0 and at each step moves +1 or −1 with equal probability. Other examples include the path traced by a molecule as it travels in a liquid or a gas, the search path of a foraging animal, the price of a fluctuating stock and the financial status of a gambler can all be approximated by random walk models, even though they may not be truly random in reality. As illustrated by those examples, random walks have applications to many scientific fields including ecology, psychology, computer science, physics, chemistry, biology as well as economics. Random walks explain the observed behaviors of many processes in these fields, and thus serve as a fundamental model for the recorded stochastic activity. As a more mathematical application, the value of pi can be approximated by the usage of random walk in agent-based modelling environment.[1][2] The term random walk was first introduced by Karl Pearson in 1905." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"If I'm writing a model of people, I don't wanna say, I know what these people are gonna do. Instead, I might say, well, you know, they're probably gonna do this, but who knows. You know, they're people. They're crazy. They might do anything. So we put in a little bit of an error term, All sorts of reasons why things may not go as we expect. There can be noise, there can be error, there can be capriciousness, there can be uncertainty, there can be complexity in the underlying process. So when we think about these models, these random models that we're gonna study, there's all sorts of things that can come into play to make the outcome not be what we expect, but to include little error term." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"In some cases you can think of outcomes as being combinations of skill and luck, and you can determine how much skill and how much luck by looking at variations in outcomes. Is there a lot of flipping, or is there sort of consistent winners? We also then got from this very simple model, a paradoxical result. And a paradoxical result is, is that when you get all high skill people competing against one another, even when it's a low luck environment, luck will play a large role because of the paradoxical skill. Alright, so that's a luck and skill model, now we're going to move on to a model of random walks. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"We can often think of. An outcome is being a sequence of random events. And if an outcome of sequence of random events, what we're gonna expect to see, is we're gonna expect to see an expect value of zero. But we're gonna see some big winners and some big losers. And we can't then necessarily infer just because someone?s been successful in the past, But fairly successful in the future. So we start with two random walkers and one who happened to go up and one who happen to goes down, and then we think, right, who in heaven's sake are we gonna place our bets on. Well, this one's just as likely to go down as this one is to go up. You don't know anything. So what we really want try and figure out in these situations is, is something a random walk? Or is it not? Is there some reason to believe that there is, that this person's going up for a reason. And this person's going down for a reason, or is the data consistent with things being purely random? And if it is, we should expect some regression in the mean, we should expect the two of them to perform about the same. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"A Random Walk Down Wall Street, written by Burton Gordon Malkiel, a Princeton economist, is an influential book on the subject of stock markets which popularized the random walk hypothesis. Malkiel argues that asset prices typically exhibit signs of random walk and that one cannot consistently outperform market averages. The book is frequently cited by those in favor of the efficient-market hypothesis. As of 2015, there have been eleven editions and over 1.5 million copies sold."- Wikipedia

Scott Page Model Thinking MOOC Course

"Here's the idea. The idea is that our random walk model your value depended on every single shock. All the way through, in a finite memory random walk, your value only depends on the previous five shocks, the previous seven shocks. Let me show you. So, the value of something at time T instead of being all of the shocks, instead of starting at zero, and adding all that up to T just includes the previous five periods. So you think of there being a window like this and that window slides along over time. As time passes, you sort of just take the last five things that have occurred."- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"A Blotto game, Colonel Blotto game, or divide-a-dollar game is a type of two-person zero-sum game in which the players are tasked to simultaneously distribute limited resources over several objects (or battlefields). In the classic version of the game, the player devoting the most resources to a battlefield wins that battlefield, and the gain (or payoff) is then equal to the total number of battlefields won." - Wikipedia

Scott Page Model Thinking MOOC Course

"If you're playing a mixed strategy, If you're playing a equilibrium strategy, then there isn't any strategic ability. We can just cross this out and it's all just going to come down to luck. So against really smart players, Blotto may end up equal numbers of troops, Blotto's probably luck. We have maybe one player who is smarter than the other, or one player with more troops than the other. Then Blotto starts becoming more skilled. But again, the interesting thing about Blotto. Anything can be beaten. You don't need all your troops, and it really comes down to, Where is that other person gonna put their troops. So, what you want to do is not be understood. You want to be confusing to the other person so you want to random off. So, it's an interesting g ame. Alright so, that's the basic Blotto. Where we're gonna go next is we're going to think a little bit more deeply about this idea of one side having an advantage and see what that means for the nature of competition. We're also gonna talk about why Blotto has become interesting again."- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"We've learned that Blotto, which was developed for warfare for putting troops on fronts, applies to a whole bunch of different stuff. It applies for the Electoral College, to terrorism, to trials, to sports, even hiring decisions. And we can get insights from Blotto to all those different environments. We've already seen from Blotto that any position can be beaten by somebody else. We've also seen that you don't need all your troops to win. What we're gonna do in the next lecture is see how much of an advantage it is to really have more troops. And what you should do. So, if you're at a disadvantage, if you don't have all those troops. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"The advantage of being stronger really depends on there being, you know, not as many fronts for over the troops. And then, we've seen if we go to a Multiplayer Blotto game, that we're likely to get cycles where one player beats two, two beats three, and then three can beat one or something like that, so we get these interesting cycles. We don't get sort of a consistent winner. So what Blotto does, if we have a situation, a competitive situation that looks like Blotto, we have some understanding of what the structure of winners should look like, and that's different than what we've seen in our other models." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"There's a sense in which the winner of the presidential election is luck, because it comes down to economic shocks going their way. And at the other extent, we ca n also say, look, another way to think about these presidential elections, though, is it's this elaborate game of blotto. They're each trying to figure out where to allocate their resources, where to spend their time, where to spend their money, trying to convince voters, And except not only electoral college, but to win different factions of voters. Cuz you can also make a Blotto game playing out on factions of voters. What you get from those two lenses, and of course the other two lenses, is just a much richer understanding of the nature of political competition. It's gonna make you better able to predict what's gonna happen, also better understand what's going on and better able to think about how do you design institutions to pick a president. Again, which is one of the things we wanna do modeling for."- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"Collective action refers to action taken together by a group of people whose goal is to enhance their status and achieve a common objective.[1] It is enacted by a representative of the group.[2] It is a term that has formulations and theories in many areas of the social sciences including psychology, sociology, anthropology, political science and economics." - Wikipedia

Scott Page Model Thinking MOOC Course

"A whole bunch of ways in which we can get cooperation [inaudible] dilemma. It can be repeated, direct reciprocity; it c ould be reputation, indirect reciprocity. >> Yeah. It can be a network effect. It can be group selection, where groups fight against each other, and so the groups that cooperate are likely to win. There can be kin selection, where what happens is that I cooperate with people who are like me. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"The term "collective action problem" describes the situation in which multiple individuals would all benefit from a certain action, but has an associated cost making it implausible that any individual can or will undertake and solve it alone." - Wikipedia

Scott Page Model Thinking MOOC Course

"When you think about the mechanisms you need to induce in this setting you gotta focus a lot more attention on this person than you do on this person, because the person at the head of the stream has a larger influence than people downstream [inaudible]. So, again, not quite the same as just rotating cattle on the common, and also, not the same as harvesting lobster. So, the particulars matter. In each one of these cases, Hence Ostrom says no panacea. So what we've seen in this simple lecture is that we can write down these mathematical models and say, here's a collective action problem, here's a common pool resource problem, here's a prisoner's dilemma. And by bringing that model to bear in a real life situation, we identify the nature of the problem. Once we've identified the nature of the problem, then we can use our expertise at a particular situation, embrace the particulars, take thicker descriptions of what's going on and then construct institutions and incentives that help us solve those problems. Overcome the collective action problem; solve the common pool resource problem, get cooperation in the prisoner's dilemma. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"Mechanism design the standard way, and the standard way is to assume that people are rational. So we're gonna sort of lay out the basics of mechanism design assuming rational agents. But after we do that we'll talk through what if people suffered from physiological biases or were slightly irrational Or what if it were the case that people just followed simple rules would our same results still follow. So we're gonna to have a dialogue using mechanisms design as a framework for thinking again about how we model people. Okay, so that's an outline of what we're going to do. What we're going to do first is just add some of the basics of mechanism design, talk about hidden action information, move on to options, and then conclude with some discussion of public good games. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"When you think about designing mechanisms in effect what we are doing, we are designing incentive structures so that we get the sort of outcomes we want. Now to get those outcomes often what we're trying to do is we're trying to induce people into taking the right kinds of effort. So, for example, if I'm an employer, what I'd like to do is I'd like to write a contract so that people actually put forth a lot of effort in their work as opposed to slacking off. Alternatively, if I'm auctioning something off, what I'd like people to do is reveal their information. I like them to reveal how much they value something. So, another feature that we want when we construct mechanisms is revelation of information. So, when I think about mechanism design, two of the core problems are dealing with these hidden actions and dealing with hidden information. So, how do we write mechanisms or incentive structures that overcome those two problems? ..." - Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course

"we can write down models of auctions and we can develop some really profound results saying that it doesn't matter how you auction things off provided some conditions are met. So that's really nice. It sort of frees us up to think about other things. And it frees us up to think about how are people are actually going to behave. How much information do they have? How sophisticated are they? How many of them are there? And that can then, then we can use those criteria to decide which auctions we're going to use. As opposed to spending our time thinking about, well this auction is better than this auction on purely rational grounds. So we talked about what, why do we model. But why do we assume even rational actors? Remember, I said, benchmarks are good things. Remember I said Roger Myerson says, the one who's got the revenue equivalent theorum, that, assuming rational behavior's often a very good benchmark. Well, we saw that was the case here in options, because we see. If people are rational, doesn't matter what mechanism you use. Once we relax that assumption, then the mechanism may matter. But, now we know what criteria to use to think about choosing among auction mechanisms. "- Transcript from Scott Page Coursera

Scott Page Model Thinking MOOC Course