Entry Point Thinking
A heuristic for problem-solving that involves deliberately considering different starting points or perspectives to address a problem, rather than tackling it head-on in the obvious way.
THE REFERENCE LIBRARY
A growing collection of ideas for understanding the world — and your own thinking.
A heuristic for problem-solving that involves deliberately considering different starting points or perspectives to address a problem, rather than tackling it head-on in the obvious way.
Your surroundings can shape habits, beliefs, and behavior. Noticing those influences can help you decide which to retain and which to change.
Envy is a useless sin that brings only pain and no pleasure, leading to misery. Charlie Munger advises against envy and resentment, citing historical examples and suggesting the Disraeli compromise as a coping mechanism.
Envy can fuel resentment when someone else has something we want. The passage proposes competition for scarce resources as an evolutionary explanation and argues, from the author’s reading, that psychology textbooks give envy too little attention.
Epicurus treats freedom from bodily pain and mental distress as central to a pleasurable life. Simple living, friendship, and attention to the consequences of choices can support that tranquility.
Taleb presents epilogism as the empirical skeptics’ way of using experience and custom to guide action without turning historical accounts into grand causal theories. His emphasis is on learning cautiously from the past and using it to challenge claims rather than confidently reverse-engineering events.
Taleb and Avital Pilpel describe a regress in risk modeling: data is used to estimate a distribution, while assumptions about that distribution help determine whether the data is sufficient. They argue that this dependence is especially troubling for rare events.
Epiphenomena are causal illusions where the observation of a correlation leads to the mistaken belief that one factor causes another, often ignoring the possibility of a common cause or reverse causation.
Taleb questions the inference that more formal education necessarily causes greater national wealth. He argues that wealth can also finance education and uses historical country comparisons to challenge a simple one-way causal story.
Epistemic arrogance means overestimating what you know and understating uncertainty. Taleb describes estimates made with intended 98% confidence that miss the true value 15-30% of the time, illustrating how ranges can be much too narrow even when people are free to choose them.
Humans have a built-in tendency to overestimate their knowledge of the future, leading to systematic failures in prediction. This bias, often called epistemic arrogance, causes us to underestimate the role of unexpected events (Black Swans) and to overconfidently predict outcomes.
Taleb calls his imagined society an epistemocracy: leaders acknowledge their ignorance and remain willing to change their minds. He contrasts that ideal with the appeal of leaders who project certainty.
Epithets are derogatory labels used in discourse, signaling that an issue is being viewed as a fight between people rather than ideas, and that identity may be biasing judgment.
A technique for finding patterns in texts by extracting letters at fixed intervals, often leading to claims of hidden messages; the resulting patterns are usually due to chance, exemplifying cognitive biases like apophenia and confirmation bias.
Equilibrium describes a balance in which the quantities being modeled remain steady. Some systems return toward that balance after a disturbance; others do not. Household and biological examples show how continual adjustments can maintain roughly stable conditions.
Taleb contrasts economic equilibrium with the physical equilibrium of an inactive system. Living organisms maintain their organization through ongoing exchanges of energy and matter. He uses this contrast to argue that suppressing all variation can harm complex systems.
The equity premium puzzle asks why historical stock returns have exceeded bond returns by more than standard models readily explain. Taleb raises survivorship bias and rare disasters as reasons to question how that history is interpreted.
Equivalence is the principle that things can be equal in outcome or function without being identical, highlighting that there are multiple paths to achieve the same result.
Equivocation occurs when an argument relies on a word or phrase changing meaning between its premises and conclusion. Defining the term consistently can expose the gap in the reasoning.
Ergodicity is the property that over time, randomness is eliminated, and the long-term average of a single system converges to the ensemble average. This concept challenges the reliability of past track records, as survivorship bias can mislead us into thinking past success predicts future performance.
When irreversible ruin is possible, the ensemble average (over many individuals at one time) diverges from the time average (over one individual over time). Without a logarithmic transformation, the time average inevitably leads to ruin, challenging standard decision theory and emphasizing the need for the precautionary principle.
A system archetype where actors lower their goals repeatedly after failing to achieve them, leading to a gradual decline in performance standards.
Error models explain how unreliability in confidence judgments can create apparent overconfidence even when underlying judgments are unbiased, but they cannot fully account for systematic biases like over- and underconfidence in all tasks.
Error-correcting codes allow reliable communication over noisy channels by adding redundancy. The Hamming code, discovered by Richard Hamming, uses a geometric structure based on the Fano plane to correct single-bit errors efficiently.
A dynamic where two parties each see their welfare as depending on relative advantage, leading to a vicious spiral of aggressive actions that exceed either side's desires.
Galef challenges the advice to escape an echo chamber simply by listening to opposing views. The excerpt states her objection but does not include its supporting argument or an alternative approach.
In action science, espoused theory is what we say we believe; theory-in-use is what our actions reveal. Recognizing the gap between them is a crucial reflective skill for personal and organizational learning.
It is not possible to be a good thinker and a poor questioner. Questions drive thinking forward; only when answers generate further questions does thought continue as inquiry.
The essentializing fallacy occurs when one claims that because something was a certain way at one point, it will always be that way, often relying on stereotypes or the notion of fixed essences without evidence.
Some organizational risks can be estimated from recurring events and historical records; others require additional evidence and judgment. Banasiewicz proposes combining information sources through the 3E framework to assess likelihood and impact, while treating the results as estimates rather than certainties.
The etymological fallacy is the mistaken belief that a word's historical origin (etymon) determines its current meaning, ignoring the natural evolution of language. It is often used to defend offensive terms or make arguments based on outdated definitions.
A euphemism is a delicate, indirect, inoffensive, or vague word or phrase used to replace one that is unpleasant, blunt, offensive, or graphic. It creates emotional distance and is fallacious when intentionally used to conceal truth and obscure meaning, enabling people to avoid reality.
Plato's dialogue Euthyphro illustrates Socrates' method of questioning to reveal that people lack clear definitions of concepts they use, such as piety.
The evaluability principle explains how the precision and evaluability of attributes influence judgments, particularly in joint versus separate evaluations. Attributes that are hard to evaluate alone become more impactful when compared directly.
The evaluability hypothesis explains preference reversals between assessing options separately and comparing them together. An attribute that is hard to assess alone, such as the number of entries in a dictionary, can carry more weight when another option provides a comparison.
The evaluability principle holds that the weight of an attribute in judgment or choice depends on how easily its value can be translated into an affective impression. Even important attributes may be ignored if they lack precise affective meaning.
Evaluate the expected business impact of solving a problem and compare it to the effort required. Determine if the problem is worth solving before committing resources.
The final step in a structured problem-solving process, where you assess whether the implemented solution worked and consider what could be done differently if it didn't.
When evaluating potential solutions, use criteria that are clear, decisive, and goal-promoting. Avoid ambiguous, non-decisive, or misaligned criteria that lead to poor decisions driven by emotion or inertia.
A framework for critically evaluating written reasoning by examining eight elements: purpose, question, information, concepts, assumptions, inferences, point of view, and implications.
A framework for conducting evaluations, focusing on four critical areas: defining scope and objectives, ensuring timeliness and intentionality, employing rigorous methodology, and effectively communicating findings. It emphasizes clarity, stakeholder agreement, and actionable outcomes.
Before evaluating norms and standards, define the purpose, scope, method, timetable and intended use of the findings. Plan how to consult stakeholders, protect impartiality and select evaluators with the skills needed for the work.
The evaluation session occurs after brainstorming, where ideas are sifted to extract useful ones by picking directly applicable solutions, extracting functional kernels from flawed ideas, and identifying new approaches or information gaps.
After a lateral thinking session, ideas are sorted into three lists: ideas of immediate usefulness, areas for further exploration, and new approaches to the problem. This evaluation requires creative effort to extract value from ideas that might otherwise be discarded.
Limits give a precise meaning to convergent infinite sums and recurring decimals. The historical discussion connects debates about infinitesimals and Zeno’s paradox with the equality 0.999... = 1.
Prediction fails in Extremistan because it misses rare, large-impact events; cumulative errors matter more than frequency of correctness, and forecasters often cluster near each other rather than near the actual outcome.
When repeated fixes fail, examine how the surrounding system produces the problem. Changes in location, incentives, handoffs, or operating conditions may explain results that look like a defect in one component.
When faced with a complex real-world problem, find a simpler everyday situation that shares its structure. This makes the problem easier to understand and allows you to apply intuition from the familiar case to the larger issue.
We can address daily challenges such as changing behavior, dealing with inaccurate information, and building trust by adjusting feedback loops—both in personal and societal contexts.
Our perceptions, judgments, and beliefs are not direct readouts of reality but are inferences heavily influenced by schemas, stereotypes, priming, framing, and heuristics like representativeness and availability. Recognizing this can lead to more accurate thinking and decision-making.
Large commissions can create conflicts between a seller’s rewards and a customer’s interests. Munger argues that weak controls make misconduct easier to rationalise, and that repeated cheating can become a group norm.
Evidence is information from facts, observations, experiments, and experiences that helps determine what is likely true or false. It is foundational to scientific reasoning and objective decision-making, requiring testability, falsification, and a willingness to challenge assumptions.
Evidence pooling combines information from several sources while examining its quality, overlap, and consistency. This approach first reviews evidence within each type, then considers how the different types bear on the decision together.
A valid implication makes a conclusion follow when its premise is true. Evidence can change how plausible a claim is without proving it, and selected confirming examples do not establish a universal statement.
Evidence-based management uses best available evidence to reduce biases and improve decision-making under uncertainty. However, applying the medical model of evidence-based practice to management is limited due to the academic-practice gap and lack of standardized education and credentialing.
Evidence-based management (EBM) is a decision-making framework that involves systematically acquiring, appraising, aggregating, and applying the best available evidence from multiple sources, including scientific literature, organizational data, practitioner experience, and stakeholder values.
The Evidence-Based Movement advocates for using objective evidence in decision-making, particularly in professional fields like medicine and management, to overcome barriers such as information overload and ingrained beliefs that cause variability in outcomes.
Evidence-based practice combines relevant research with professional expertise and the circumstances of a decision. Systematic reviews and meta-analyses help assess and summarize research, but managers must also consider whether findings apply to their organization and arrive in time to be useful.
Banasiewicz’s evidence-driven approach combines operational data, research, and other evidence to inform management decisions. It emphasizes computation and simulation as ways to examine current conditions and test possible actions.
A mental model for evaluating the strength and dependability of evidence, recognizing that not all evidence is equally compelling and that overreliance on any single type (subjective reasoning, data analytics, or scientific research) can lead to poor decisions. It emphasizes the need to assess and reconcile multiple pieces of evidence within a probabilistic thinking framework.