The basic idea of intuition is simple there are two models of thinking.
System 1: Intuitive thinking, Quick, spontaneous, emotional, depends upon simple mental rules of thumb (heuristics) and thinking biases (Cognitive biases) that result in impression, feelings, and inclinations.
System 2: Thinking is rational thinking, slow declarative, and systematic — based on considered evaluations results in logical conclusions.
The goal of this book was to recognize the systematic errors that system1 makes and avoid them especially when the stakes are high.
Heuristics and biases
There are several potential errors in judgment that people can make when overly rely on system 1.
What you see is all there is (WYSIAT)
Our system 1 only works on activated ides. People jump into conclusions on the biceps of limited information.
Priming
Exposure to an idea triggers System 1’s associative machine and primes us to think about related ideas.
Cognitive Ease
Things that are more familiar or easier to comprehend seem to be more true than things that are novel or require hard thought. If we hear a lie often, we believe it mostly.
Coherent Stories
We are more likely to believe something if it’s easy to fit into a coherent story. We confuse causality with correlation and make more out of coincidence than is statistically warranted.
Confirmation Bias
We tend to search for and find confirming evidence for a belief while overlooking counter-examples.
Halo Effect
We tend to like or dislike everything about a person. Even without direct experience.
Substitution
We replace a hard question with a more comfortable one. When asked about how happy we are with our life, we answer the question “What is my mood right now?”
The Law of Small Numbers
Small samples are more prone to extreme outcomes than large ones, but we tend to lend the outcomes of small samples more credence than statistically warranted.
Overconfidence
We tend to suppress ambiguity and doubt by constructing coherent stories from scraps of data. One way to make better decisions is to just be less confident.
Anchoring Effect
Making incorrect calculations due to earlier gathered numbers, even if those numbers don’t have anything to do with the estimate you’re trying to arrive at.
Availability Heuristic and the Cascades
We rely on immediate examples that come to our mind when evaluating a specific topic, concept, method, or decision. We overreact to a minor problem simply because we hear a disproportionate number of negative news stories than positive ones. A recent plane crash makes us believe that air travel is more vulnerable than car travel.
Representativeness
We make judgments based on profiling or stereotyping, instead of probability, base rate, or sampling sizes.
Conjugation Fallacy
We choose a plausible story over a probable story. Consider the Linda Experiment: Linda is single, outspoken, and very bright, and as a student, was deeply concerned with issues of discrimination and social justice. Which is more probable? (1) Linda is a bank teller, or (2) Linda is a bank teller active in the feminist movement. The correct answer is (1), and don’t feel too bad if you got it wrong since 85% of Stanford’s Graduate School of Business students also flunked this test. Statistically, there are fewer feminist female bank tellers than female bank tellers.
Overlooking Statistics
Given statistical data and an individual story, we tend to connect more value to the story than the data.
Overlooking Luck
The tendency to attach causal ideas to fluctuation in random processes. When we remove these causal stories and consider small statistics, we observe regularities like regression to the mean.
Overconfidence
The Narrative Fallacy
We create flawed explanatory stories of the past that shape our views of the world and expectations of the future.
The Hindsight Illusion
Our intuitions and premonitions feel more true after the fact. Hindsight is 20/20.
The Illusion of Validity
We cling with confidence to our opinions, predictions, and points of view even in the face of counter-evidence. Confidence is not a measure of accuracy.
Ignoring Formulas
We overlook statistical information and favor intuition over formulas. Always rely on algorithms for important decisions when available over your subjective feelings, hunches, or intuition.
Trusting Expert Intuition
Trust experts when the environment is sufficiently regular to be predictable and the expert has learned these regularities through prolonged exposure.
The Planning Fallacy
We take on risky projects with the best-case scenario in mind, without considering the outside view of others who have engaged in similar projects in the past. A good way around this fallacy is to do a premortem: before you start, think of all the ways your project can fail.
The Optimistic Bias
We believe that we are at a lesser risk of experiencing a negative event compared to others. A way to make better decisions to be less optimistic.
Theory-Induced Blindness
Once we have accepted a theory and used it as a tool in our thinking, it is extraordinarily difficult to notice its flaws. If we come upon an observation that does not seem to fit the model, we assume that there must be a perfectly good explanation that we are somehow missing.
Endowment Effect
An object we own and use is a lot more valuable than an object we don’t own and use.
Choices
Omitting Subjectivity
Bernoulli proposed money had fixed utility. But he failed to consider a person’s reference point. A million dollars is worth a lot to a poor person, but nothing to a billionaire.
Loss aversion
We dislike losing more than we like winning. A loss of Rs.100 is worse than a gain of Rs.100.
Prospect Theory
It improves upon Bernoulli’s Utility Theory by accounting for loss aversion (greater slope on the loss side) and also for a subjective reference point. we think in terms of expected utility relative to the reference point rather than the outcome.
Possibility Effect, Certainty Effect, and the Fourfold Pattern
When people facing a gamble losses look lager the gains.
The Expectation Principle
As per the last two heuristics, we can see that the decision weights that we assign to outcomes are not identical to the probabilities of these outcomes. We contradict the Expectation Principle.
Overestimating the likelihood of Rare Events:
We choose the alternative in a decision that is described with explicit vividness, repetition, and higher relative frequency. Availability Cascade and Cognitive Ease play a huge role in this.
Thinking Narrowly
We are so risk-averse that we avoid all gambles, even thought some gambles are on our side and by avoiding them we lose money.
The Disposition Effect
We tend to sell stocks whose price has increased while keeping ones that have dropped in value.
The Sunk Cost Fallacy
We continue to increase investment in a decision based on the cumulative prior investment (the sunk cost) despite new contradictory evidence.
Fear of Regret
We avoid making decisions that lead to regret, without realizing how intensely those feeling of regret will be. It hurts less than we think.
Ignoring Joint Evaluations
Joint evaluations highlight a feature that was not noticeable in single evaluations but is recognized as a decisive when detected. Who deserves more compensation? A person robbed in their local grocery store, or a person robbed in a store they almost never visit. In joint evaluation, we can see that the location should have no effect on the compensation, but not so much when we consider the two cases individually.
Framing Effect
We react to a particular choice in different ways depending on its presentation and framing of context and communications.
The Two Selves
Our Two Selves
We have an Experiencing Self and a Remembering Self. The latter trumps the former.
The Peak End Rule
We value experience by its peak and how it ended.
Duration Neglect
The duration of experience doesn’t seem as important as the memory of the experience.
Affective Forecasting
Forecasting our own happiness in the future. We are particularly bad at this.
Focusing Illusion
When we’re asked to evaluate a decision, like life satisfaction or preference. we focus on only one thing.
