Thinking In Bets

I enjoyed this as it's a lens widening read.

Must read, enlightening and very enjoying piece of art. Bet on this book, there is no chance to lose.. well you just might lose some wrong, bad and outdated ideas you may have about risk, betting and desiton making.

This book is about how to make better decisions, from the trivial to the most consequential, in all endeavors of life: personal, business, political/economic forecasting, gambling, etc. It explains how to think about potential decision options, given that most entail varying degrees of risky or uncertain outcomes. Without attempting to bog the reader down in the mathematics of probability theory, the core of most textbook approaches to decision making, it clearly demonstrates how to incorporate probabilistic uncertainty into our decision-making thought processes. Since most decisions we make lead to outcomes which have an element of probabilistic uncertainty, the book's approach is relevant to all walks of life. Although Duke does not frame it this way, I think a brief explanation of two fundamentally different types of situations captured by the tool of probabilistic reasoning may be helpful. This dichotomy leads to what have been termed Objective and Subjective probabilities. Objective probabilities are those associated with outcomes that are truly random with specific known numerical probabilities governing various occurrences. For these, no amount of thinking or information on the part of those of us observing the situation can improve on understanding inherent randomness of the underlying activity leading to some outcome, i.e., the known probabilities are the best we can do in anticipating the ultimate outcome of the event. In other words, we can't improve on the odds of various outcomes however smart we may be. The best examples for this type of probability are things happening in the world of quantum mechanics, e.g., predicting the time at which a radioactive element or a neutron will decay. A close second for most practical purposes would be the outcome of the spin of a roulette wheel or the outcome of a fair roll of a pair of dice. Objective probabilities are set by the laws of nature, and, once known, the actual outcomes of a large number of repetitive observations of the same situation will lead to a predictable distribution of outcomes. Subjective probabilities, on the other hand, are probabilities we assign to various outcomes when faced with decisions leading to uncertain outcomes. They are not fixed or absolute numbers driven by the laws of nature. We may assign a numerical value to a particular outcome, e.g., a 70% chance the Patriots will win the Super Bowl against the Eagles, or, they may be qualitative rankings of possible outcomes, e.g., highly likely, pretty likely, not sure, very unlikely, etc. Three key things about Subjective probabilities are: 1. Different people thinking about the same event will usually have different estimates of the probabilistic outcomes. Subjective probabilities are not facts. They are opinions. 2. The information/knowledge the decision maker has about the situation will affect their probability estimates of different outcomes. 3. Good decision makers in many particular endeavors like poker or investing will usually, i.e., more frequently but not always, have better success in predicting uncertain outcomes than will poor decision makers. During the first couple of hundred years that mathematicians tried to develop the field of probability, they were generally focused on thinking about things they believed were governed by Objective probabilities. Even the game of poker was thought of in this way for years. Early in the 20th century, thinkers began to crystallize the idea of Subjective probabilities as distinctly different from Objective probabilities. John Maynard Keynes attempted to develop a full blown theory with his 1921 book "A Treatise On Probability". Although it had some excellent ideas, it did not succeed in laying out a firm mathematical basis for Subjective probability. This took the Italian mathematician, Bruno de Finetti, to define a mathematically rigorous treatment of Subjective probability in his 1937 book. And, thinking in bets was core to his approach. By the 1950's, de Finetti's approach became the basis for aspects of economics , game theory, and decision making under uncertainty. The latter pertains to virtually all decision making we encounter in daily life. So, what does Subjective probability have to do with bets. In short, everything. When we make a bet, we do so with a view of the chances of winning, either a qualitative view, or a quantitative view, i.e., a probability. A bet is the manifestation of one's personal estimate of the Subjective probability of the outcome you are favoring. The beauty of Duke's book is that it explains with lots of examples of how to apply Subjective probabilistic thinking in all sorts of situations without having to worry about the sound basis of the underlying mathematics. Poker is a great example of a situation in which a Subjective probabilistic assessment is critical, since trying to gauge how others will behave in playing a hand is truly a subjective, rather than objective, assessment. Thus her poker and human psychology background really do mark her as expert in teaching smart decision making for a broad audience. Since information and knowledge are key to making sound estimates of Subjective probabilities, Duke spends a lot of time on how to build a broad information base pertaining to prospective decisions, and how to guard against biases we naturally have that can cause us to resist relevant information that may rub us wrong. She implies that for lots of decisions, one can do better simply by stepping back and thinking about the pro's and con's, rather than just going on an impulse. Oftentimes we have relevant information in our head, if only we would think about it. Get external inputs as well, e.g., friends or Google. Information is key and being open to inputs that may conflict with your beliefs will improve your decision quality in the long run. Thus,the book is suitable for both the mathematically inclined and the mathematically averse. Although the math is absent, some may find some of the concepts a bit difficult or, on the surface, repetitive, as evidenced by some of the reviews posted here on Amazon. Stated differently, it may be difficult sometimes to appreciate the applicability of the advice to settings that go beyond the specific example used preceding her current point, but a little thought brings it home. No doubt, a few readers of the book will 'get it' and some won't, though they may still find some of the stories entertaining. None-the-less, I highly recommend it as worthwhile for both personal improvement, as well as supplemental reading in almost any graduate school curriculum.

One of the greatest book I have ever read about thinking in probabilities. MUST read

Key Concepts and Frameworks 1. Uncertainty and Decision Quality: • Acknowledge that the world is inherently uncertain, and outcomes are influenced by a mix of luck and skill. • Great decisions don’t guarantee good outcomes but increase the probability of success. • Improving decision quality requires recognizing uncertainty, evaluating probabilities, and preparing for alternative futures. 2. Cognitive Biases: • Motivated Reasoning: We protect our beliefs by seeking confirming evidence and discrediting contradictory information. • Self-Serving Bias: Success is attributed to skill, while failures are blamed on luck or external factors. • Inside Bias: Overconfidence in our knowledge and underestimation of what we don’t know distort judgment. • Resulting: Judging decisions based solely on outcomes rather than the quality of the process. 3. Skepticism and Truth-Seeking: • Skepticism focuses on asking, Why might this not be true? rather than Why is this true? • Engage in exploratory thought by considering alternative hypotheses, testing opposing viewpoints, and evaluating beliefs critically. • Avoid biases by encouraging diversity of opinion and fostering accountability within decision-making groups. Practical Tools and Techniques 1. Scenario Planning: • Map out potential futures, assign probabilities, and prepare strategic responses for various outcomes. • Benefits include acknowledging uncertainty, preparing for responses, reducing unproductive regret, and avoiding biases like resulting and inside bias. 2. Backcasting and Premortems: • Backcasting: Work backward from a desired goal to identify actions and strategies that could lead to success. • Premortems: Imagine failure, then identify reasons it might occur. Use this to proactively address potential obstacles. • Combining these methods—mental contrasting—improves the likelihood of achieving goals. 3. 10-10-10 Strategy: • Consider the consequences of a decision in 10 minutes, 10 months, and 10 years to counteract temporal discounting and promote long-term thinking. 4. Outcome-Blind Analysis: • Deconstruct decisions before knowing the outcomes to avoid bias. • Create decision trees and focus on improving processes rather than judging by results alone. 5. Pre-Commitments: • Use contracts or accountability mechanisms to pause for deliberation during emotionally charged moments. • Pre-commitment ensures focus on long-term goals and prevents impulsive choices. Improving Decision-Making: • Develop habits around accurate self-critique, admitting mistakes, and giving credit to others. • Focus on factors within your control while letting go of those outside your influence. • Build self-correcting epistemic communities that prioritize accuracy, truth-seeking, and diverse perspectives. Key Takeaways: • Decisions are bets on the future, made with incomplete information and influenced by randomness. • Success comes from improving decision processes, not guaranteeing outcomes. • By combining tools like backcasting, premortems, scenario planning, and accountability structures, you can increase the quality of your decisions and reduce cognitive biases.