Risk Savvy: How to Make Good Decisions

This is one of the wisest books I've ever read. The main point is that for known (truly predictable) risks, complex rules are best. Otherwise, you should rely on simple "rules of thumb" (ROTs) to navigate the complexity of the real world, which has numerous "unknown unknowns". Most things in the real world can't be modeled accurately at all and complex (but useless) mathematical models can easily lead you astray.Here's a brief summary of the book:Chapters 1+2 makes the distinction between known risks vs. uncertainty in the real world. The author describes the "turkey illusion" in which a turkey assumes a farmer will feed it daily (based on past experience) because it doesn't know about Thanksgiving. Gigerenzer provides a brief primer on statistics and the distinction between relative and absolute risks. (Something may raise your relative risk by 3x but if the absolute risk only increases from 1 in 100,000 to 3 in 100,000 then it's just statistical noise!) The author recommends using "natural frequencies" in order to make statistics as intuitive as possible.Chapter 5 discusses the financial collapse of 2008 and how NONE of the economic models predicted it because these "toy" models can only deal with known risks, NOT the real world. A simple ROT for investments is to diversify as much as possible, i.e. "don't put all of your eggs into a single basket". In Chapter 8, the author recommends "choosing a partner that your peers find desirable". He then simplifies it even further to "marry someone you love" (the ultimate gut-feeling). Chapters 9-10 warns about medical screening because all tests in the real world have limitations and false positives are common.One major omission in the book are ROTs for science- below are 6 useful ones:1) All models are wrong-some models are useful.Science is really about building models that make useful predictions. Useful models give "correct" answers over a certain range (and break down outside of that range) and don't necessarily describe reality (whatever that is). Physics and engineering have many useful models but biology does NOT because the latter is simply too complex to model accurately. Economics and climatology are 2 other fields that lack useful models.2) Ignore "tiny" effects (good and bad).This means ignoring most health headlines, which are full of tiny risks (in absolute terms) and NOT taking heavily marketed but ineffective drugs (e.g. only 1 person out of 100 who takes a statin actually benefits and yet statins are among the most commonly prescribed drugs!).3) ~50% of science/medicine is wrong (but be neutral, not cynical).The public vastly overestimates what science truly understands. (Most people would be surprised to learn that no one really knows why animals sleep; or how tylenol works or why ice is slippery, etc.) Medicine has made great strides in treating wounds/injuries and infectious diseases. Medicine has been FAR less successful in nutrition, cancer, mental conditions, chronic disease, etc. so some current treatments are actually making patients worse.4) If real experts exist, then absolutely, you should listen to them.But be wary of "specialists", who are often wrong and even unaware they're merely guessing. Most fields only have specialists. A specialist may know 100x what you know about a subject- but if you know 0.1% and they know 10% then they still don't know enough to be blindly trusted and in fact may be more biased than a neutral outsider.5) With enough assumptions, you can justify anything.You should be skeptical of alternate, contrary theories. But you should be equally skeptical of the "consensus" (which is all too often based on dogma and group-think) if it's NOT based on solid experimental evidence. Science is becoming increasingly useless like "art" (diminishing returns). Some fields have no practical value and are dominated by guesses that can never be confirmed. Many open issues in science/medicine are due to "unknown unknowns" that may even be beyond our comprehension.6) You can identify pseudo-science by how its proponents respond to criticism.This ROT alone is all you need in order to recognize that something like CO2 hysteria is junk-science.

We are all plagued by the cognitive deficiencies that come with being human. Some biases are unavoidable and biologically ingrained while others are the product of not being familiarized with the land of statistics. Risk Savvy tackles several topics with a primary focus on understanding statistics in terms of relative frequency. In particular medical science is at the core of much of the book and the author focuses how to better communicate medical risks to patients. Besides this topic there are other ideas touched upon including psychology or rare event risk as well as risks in the financial system. Risky Savvy introduces the reader to ideas of Bayesian inference in an intuitive manner and gives good policy advice for the medical profession.The book is split into three parts of which the real contents are contained within the first two sections with the last being some policy advice. The first section is titled- the Psychology of Risk. It starts by describing how commonly used forecasts like the likelihood of rain are understood differently by various members of the population and how this misunderstanding comes from being unfamiliar with what sets the probabilities used in common dialogue refer to. The need for people to articulate what probability is being used for specifically is at the core of a lot of misunderstanding and misinformation. The author cites using studies that when people are instructed better about the class of events the probability is on common misunderstandings can all but disappear. The author also discusses how we can often mis-assess risks when we are faced with events we are unfamiliar. In particular the author goes through the effective statistics of events like 9-11 on behavior (increased driving relative to flying) which are at their core irrational given the risks of dying on the road are substantially higher than flying. The author gives tangible examples to the reader so that they can understand which kinds of reasoning failures many of us naturally make when making decisions.The second part is the core of the book. The author discusses a lot of different topics including insurance selling, romance and biostatistics. Each topic gives examples of how we make decisions and how we can make errors. Appreciating our gut instincts is a topic of focus and the author highlights how we should rely on using our gut instincts with respect to making multidimensional executive decisions. He discusses how the fear of getting things wrong leads to institutional decay and a lack of innovation. The author also discusses gut instinct with respect to romance and marriage. He starts the topic by using Darwin's method of dual entry book keeping for figuring out whether to get married or not but then discusses how in reality our gut instincts really tend to drive these decisions. The core of the section for me was on biostatistics. The author spends a lot of time discussing misunderstanding and poor phrasing in the medical profession. There are good policy suggestions and the reader gets a good sense of intuitively what Bayesian reasoning entails. The author also discusses the banking system and how the banking system is plagued by moral hazard and how the fundamental misalignment of interests in a leveraged limited liability system can lead to instability.The author ends with some solution suggestions to the fact that education systems of today focus too little on probabilistic reasoning. The suggestions for the medical industry seem very beneficial as the simple visuals the author constructs give a very intuitive perspective on relative frequency. The suggestions for finance is a bit weaker though the author does articulate well how many financial narratives that defend the industry are unconvincing. The author also discusses social aspects of the internet and how online interaction has resulted in isolation for some parts of society, this part didn't really fit into the rest of the book. All in all Risk Savvy gives the reader an introduction to how we make mistakes when reasoning in situations with risk. The failures in reasoning are different for different events- for disaster its misunderstanding tail probabilities, for medical science it is misunderstanding Bayesian statistics and relative frequency and for finance it is misunderstanding the nature of distributions in economic systems, namely they should not be assumed normal and there are many unknown unkowns. I enjoyed reading it and is a worthwhile addition to the literature on behavioral science.

the book takes the read into inquiry around what do you need to know when making good decisions? Like when a stat relating to a percentage of persons being impacted by a study, what exactly was measured, then how do you then properly apply the information to yours elf or your situations. The examples of how stats have been misapplied was very stark and troubling that emphasized the need to properly understand the measurement and application. As well the book took the reader on a great journey of using your gut and intuition in decision making. Overall a great and useful book.

O livro foi escrito utilizando de uma abordagem muitas vezes do contra. Com dados consistentes, o autor critica a realização de alguns tipos de exames médicos, fala sobre saúde de uma forma mais generalizada e principalmente critica o senso de risco que possuímos. Das más interpretações de informações sobre medicamentos feitas por médicos às distorções que fazemos nos cálculos de probabilidades de novas ocorrências de eventos raros de forte impacto. O autor faz também, uma proposta de uso de heurísticas para rápida tomada de decisão em situações variadas que envolvem alta complexidade e grande incerteza. Diferente de quase toda literatura disponível por aí, a abordagem com uma perspectiva diferenciada faz valer a pena a leitura.

Worth reading just for the explanation of how to interpret medical tests. And there is a lot more interesting stuff.

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