Book Reviews

Book review: Reinventing Philanthropy: A Framework for More Effective Giving, by Eric Friedman.

This book will spread the ideas behind effective altruism to a modestly wider set of donors than other efforts I’m aware of. It understates how much the effective altruism movement differs from traditional charity and how hard it is to implement, but given the shortage of books on this subject any addition is valuable. It focuses on how to ask good questions about philanthropy rather than attempting to find good answers.

The author provides a list of objections he’s heard to maximizing the effectiveness of charity, a majority of which seem to boil down to the “diversification of nonprofit goals would be drastically reduced”, leading to many existing benefits being canceled. He tries to argue that people have extremely diverse goals which would result in an extremely diverse set of charities. He later argues that the subjectivity of determining the effectiveness of charities will maintain that diversity. Neither of these arguments seem remotely plausible. When individuals explicitly compare how they value their own pleasure, life expectancy, dignity, freedom, etc., I don’t see more than a handful of different goals. How could it be much different for recipients of charity? There exist charities whose value can’t easily be compared to GiveWell’s recommended ones (stopping nuclear war?), but they seem to get a small fraction of the money that goes to charities that GiveWell has decent reasons for rejecting.

So I conclude that widespread adoption of effective giving would drastically reduce the diversity of charitable goals (limited mostly by the fact that spending large amount on a single goal is subject to diminishing returns). The only plausible explanation I see for peoples’ discomfort with that is that people are attached to beliefs which are inconsistent with treating all potential recipients as equally deserving.

He’s reluctant to criticize “well-intentioned” donors who use traditional emotional reasoning. I prefer to think of them as normally-intentioned (i.e. acting on a mix of selfish and altruistic motives).

I still have some concerns that asking average donors to objectively maximize the impact of their donations would backfire by reducing the emotional benefit they get from giving more than it increases the effectiveness of their giving. But since I don’t expect more than a few percent of the population to be analytical enough to accept the arguments in this book, this doesn’t seem like an important concern.

He tries to argue that effective giving can increase the emotional benefit we get from giving. This mostly seems to depend on getting more warm fuzzy feelings from helping more people. But as far as I can tell, those feelings are very insensitive to the number of people helped. I haven’t noticed any improved feelings as I alter my giving to increase its impact, and the literature on scope insensitivity suggests that’s typical.

He wants donors to treat potentially deserving recipients as equally deserving regardless of how far away they are, but he fails to include people who are distant in time. He might have good reasons for not wanting to donate to people of the distant future, but not analyzing those reasons risks making the same kind of mistake he criticizes donors for making about distant continents.

War

Book review: War in Human Civilization by Azar Gat.

This ambitious book has some valuable insights into what influences the frequency of wars, but is sufficiently long-winded that I wasn’t willing to read much more than half of it (I skipped part 2).

Part 1 describes the evolutionary pressures which lead to war, most of which ought to be fairly obvious.

One point that seemed new to me in that section was the observation that for much of the human past, group selection was almost equivalent to kin selection because tribes were fairly close kin.

Part 3 describes how the industrial revolution altered the nature of war.

The best section of the book contains strong criticisms of the belief that democracy makes war unlikely (at least with other democracies).

Part of the reason for the myth that democracies don’t fight each other was people relying on a database of wars that only covers the period starting in 1815. That helped people overlook many wars between democracies in ancient Greece, the 1812 war between the US and Britain, etc.

A more tenable claim is that something associated with modern democracies is deterring war.

But in spite of number of countries involved and the number of years in which we can imagine some of them fighting, there’s little reason to consider the available evidence for the past century to be much more than one data point. There was a good deal of cultural homogeneity across democracies in that period. And those democracies were part of an alliance that was unified by the threat of communism.

He suggests some alternate explanations for modern peace that are only loosely connected to democracy, including:

  • increased wealth makes people more risk averse
  • war has become less profitable
  • young males are a smaller fraction of the population
  • increased availability of sex made men less desperate to get sex by raping the enemy (“Make love, not war” wasn’t just a slogan)

He has an interesting idea about why trade wasn’t very effective at preventing wars between wealthy nations up to 1945 – there was an expectation that the world would be partitioned into a few large empires with free trade within but limited trade between empires. Being part of a large empire was expected to imply greater wealth than a small empire. After 1945, the expectation that trade would be global meant that small nations appeared viable.

Another potentially important historical change was that before the 1500s, power was an effective way of gaining wealth, but wealth was not very effective at generating power. After the 1500s, wealth became important to being powerful, and military power became less effective at acquiring wealth.

Book review: The Origins of Political Order: From Prehuman Times to the French Revolution, by Francis Fukuyama.

This ambitious attempt to explain the rise of civilization (especially the rule of law) is partly successful.

The most important idea in the book is that the Catholic church (in the Gregorian Reforms) played a critical role in creating important institutions.

The church differed from religions in other cultures in that it was sufficiently organized to influence political policy, but not strong enough to become a state. This lead it to acquire resources by creating rules that enabled people to leave property to the church (often via wills, which hardly existed before then). This turned what had been resources belonging to some abstract group (families or ancestors) into things owned by individuals, and created rules for transferring those resources.

In the process, it also weakened the extended family, which was essential to having a state that impartially promoted the welfare of a society that was larger than a family.

He also provides a moderately good description of China’s earlier partial adoption of something similar in its merit-selected bureaucracy.

I recommend reading the first 7 chapters plus chapter 16. The rest of the book contains more ordinary history, including some not-too-convincing explanations of why northwest Europe did better than the rest of Christianity.

Book review: Radical Abundance: How a Revolution in Nanotechnology Will Change Civilization, by K. Eric Drexler.

Radical Abundance is more cautious than his prior books, and targeted at a very nontechnical audience. It accurately describes many likely ways in which technology will create orders of magnitude more material wealth.

Much of it repackages old ideas, and it focuses too much on the history of nanotechnology.

He defines the subject of the book to be atomically precise manufacturing (APM), and doesn’t consider nanobots to have much relevance to the book.

One new idea that I liked is that rare elements will become unimportant to manufacturing. In particular, solar energy can be made entirely out of relatively common elements (unlike current photovoltaics). Alas, he doesn’t provide enough detail for me to figure out how confident I should be about that.

He predicts that progress toward APM will accelerate someday, but doesn’t provide convincing arguments. I don’t recall him pointing out the likelihood that investment in APM companies will increase dramatically when VCs realize that a few years of effort will produce commercial products.

He doesn’t do a good jobs of documenting his claims that APM has advanced far. I’m pretty sure that the million atom DNA scaffolds he mentions have as much programmable complexity as he hints, but if I only relied on this book to analyze that I’d suspect that those structures were simpler and filled with redundancy.

He wants us to believe that APM will largely eliminate pollution, and that waste heat will “have little adverse impact”. I’m disappointed that he doesn’t quantify the global impact of increasing waste heat. Why does he seem to disagree with Rob Freitas about this?

Book review: The Motivation Hacker, by Nick Winter.

This is a productivity book that might improve some peoples’ motivation.

It provides an entertaining summary (with clear examples) of how to use tools such as precommitment to accomplish an absurd number of goals.

But it mostly fails at explaining how to feel enthusiastic about doing so.

The section on Goal Picking Exercises exemplifies the problems I have with the book. The most realistic sounding exercise had me rank a bunch of goals by how much the goal excites me times the probability of success divided by the time required. I found that the variations in the last two terms overwhelmed the excitement term, leaving me with the advice that I should focus on the least exciting goals. (Modest changes to the arbitrary scale of excitement might change that conclusion).

Which leaves me wondering whether I should focus on goals that I’m likely to achieve soon but which I have trouble caring about, or whether I should focus on longer term goals such as mind uploading (where I might spend years on subgoals which turn out to be mistaken).

The author doesn’t seem to have gotten enough out of his experience to motivate me to imitate the way he picks goals.

Paleofantasy

Book review: Paleofantasy: What Evolution Really Tells Us about Sex, Diet, and How We Live, by Marlene Zuk

This book refutes some myths about what would happen if we adopted the lifestyle of some imaginary hunter-gather ancestor who some imagine was perfectly adapted to his environment.

I’m a bit disappointed that it isn’t as provocative as the hype around it suggested. It mostly just points out that there’s no single environment that we’re adapted to, plus uncertainty about what our ancestors’ lifestyle was.

She spends a good deal of the book demonstrating what ought to be the well-known fact that we’re still evolving and have partly adapted to an agricultural lifestyle. A more surprising point is that we still have problems stemming from not yet having fully evolved to be land animals rather than fish (e.g. hiccups).

She provides a reference to a study disputing the widely held belief that the transition from hunter-gatherer to farmer made people less healthy.

She cites evidence that humans haven’t evolved much adaptation to specific diets, and do about equally well on a wide variety of diets involving wild foods, so that looking at plant to animal ratios in hunter-gather diets isn’t useful.

Her practical lifestyle advice is mostly consistent with an informed guess about how we can imitate our ancestors’ lifestyle (e.g. eat less processed food), and mainly serves to counteract some of the overconfident claims of the less thoughtful paleo lifestyle promoters.

Book review: Why Nations Fail: The Origins of Power, Prosperity, and Poverty, by Daron Acemoglu and James Robinson.

This book claims that “extractive institutions” prevent nations from becoming wealthy, and “inclusive institutions” favor wealth creation. It is full of anecdotes that occasionally have some relevance to their thesis. (The footnotes hint that they’ve written something more rigorous elsewhere).

The stereotypical extractive institutions certainly do harm that the stereotypical inclusive institutions don’t. But they describe those concepts in ways that do a mediocre job of generalizing to non-stereotypical governments.

They define “extractive institutions” broadly to include regions that don’t have “sufficiently centralized and pluralistic” political institutions. That enables them to classify regions such as Somalia as extractive without having to identify anything that would fit the normal meaning of extractive.

Their description of Somalia as having an “almost constant state of warfare” is strange. Their only attempt to quantify this warfare is a reference to a 1955 incident where 74 people were killed (if that’s a memorable incident, it would suggest war kills few people there; do they ignore the early 90’s because it was an aberration?). Wikipedia lists Somalia’s most recently reported homicide rate as 1.5 per 100,000 (compare to 14.5 for their favorite African nation Botswana, and 4.2 for the U.S.).

They don’t discuss the success of Dubai and Hong Kong because those governments don’t come very close to fitting their stereotype of a pluralistic and centralized nation.

They describe Mao’s China as “highly extractive”, but it looks to me more like ignorant destruction than an attempt at extracting anything. They say China’s current growth is unsustainable, somewhat like the Soviet Union (but they hedge and say it might succeed by becoming inclusive as South Korea did). Whereas I predict that China’s relatively decentralized planning will be enough to sustain modest growth, but it will be held back somewhat by the limits to the rule of law.

They do a good (but hardly novel) job of explaining why elites often fear that increased prosperity would threaten their position.

They correctly criticize some weak alternative explanations of poverty such as laziness. But they say little about explanations that partly overlap with theirs, such as Fukuyama’s Trust (a bit odd given that the book contains a blurb from Fukuyama). Fukuyama doesn’t seem to discuss Africa much, but the effects of slave trade seem to have large long-lasting consequences on social capital.

For a good introduction to some more thoughtful explanations of national growth such as the rule of law and the scientific method, see William Bernstein’s The Birth of Plenty.

Why Nations Fail may be useful for correcting myths among people who are averse to math, but for people who are already familiar with this subject, it will just add a few anecdotes without adding much insight.

Book review: Error and the Growth of Experimental Knowledge by Deborah Mayo.

This book provides a fairly thoughtful theory of how scientists work, drawing on
Popper and Kuhn while improving on them. It also tries to describe a quasi-frequentist philosophy (called Error Statistics, abbreviated as ES) which poses a more serious challenge to the Bayesian Way than I’d seen before.

Mayo’s attacks on Bayesians are focused more on subjective Bayesians than objective Bayesians, and they show some real problems with the subjectivists willingness to treat arbitrary priors as valid. The criticisms that apply to objective Bayesians (such as E.T. Jaynes) helped me understand why frequentism is taken seriously, but didn’t convince me to change my view that the Bayesian interpretation is more rigorous than the alternatives.

Mayo shows that much of the disagreement stems from differing goals. ES is designed for scientists whose main job is generating better evidence via new experiments. ES uses statistics for generating severe tests of hypotheses. Bayesians take evidence as a given and don’t think experiments deserve special status within probability theory.

The most important difference between these two philosophies is how they treat experiments with “stopping rules” (e.g. tossing a coin until it produces a pre-specified pattern instead of doing a pre-specified number of tosses). Each philosophy tells us to analyze the results in ways that seem bizarre to people who only understand the other philosophy. This subject is sufficiently confusing that I’ll write a separate post about it after reading other discussions of it.

She constructs a superficially serious disagreement where Bayesians say that evidence increases the probability of a hypothesis while ES says the evidence provides no support for the (Gellerized) hypothesis. Objective Bayesians seem to handle this via priors which reflect the use of old evidence. Marcus Hutter has a description of a general solution in his paper On Universal Prediction and Bayesian Confirmation, but I’m concerned that Bayesians may be more prone to mistakes in implementing such an approach than people who use ES.

Mayo occasionally dismisses the Bayesian Way as wrong due to what look to me like differing uses of concepts such as evidence. The Bayesian notion of very weak evidence seems wrong given her assumption that concept scientific evidence is the “right” concept. This kind of confusion makes me wish Bayesians had invented a different word for the non-prior information that gets fed into Bayes Theorem.

One interesting and apparently valid criticism Mayo makes is that Bayesians treat the evidence that they feed into Bayes Theorem as if it had a probability of one, contrary to the usual Bayesian mantra that all data have a probability and the use of zero or one as a probability is suspect. This is clearly just an approximation for ease of use. Does it cause problems in practice? I haven’t seen a good answer to this.

Mayo claims that ES can apportion blame for an anomalous test result (does it disprove the hypothesis? or did an instrument malfunction?) without dealing with prior probabilities. For example, in the classic 1919 eclipse test of relativity, supporters of Newton’s theory agreed with supporters of relativity about which data to accept and which to reject, whereas Bayesians would have disagreed about the probabilities to assign to the evidence. If I understand her correctly, this also means that if the data had shown light being deflected at a 90 degree angle to what both theories predict, ES scientists wouldn’t look any harder for instrument malfunctions.

Mayo complains that when different experimenters reach different conclusions (due to differing experimental results) “Lindley says all the information resides in an agent’s posterior probability”. This may be true in the unrealistic case where each one perfectly incorporates all relevant evidence into their priors. But a much better Bayesian way to handle differing experimental results is to find all the information created by experiments in the likelihood ratios that they produce.

Many of the disagreements could be resolved by observing which approach to statistics produced better results. The best Mayo can do seems to be when she mentions an obscure claim by Pierce that Bayesian methods had a consistently poor track record in (19th century?) archaeology. I’m disappointed that I haven’t seen a good comparison of more recent uses of the competing approaches.

Book review: How to Measure Anything, by Douglas Hubbard.

I procrastinated about reading this book because it appeared to be only relevant to a narrow type of business problem. But it is much more ambitious, and aims to convince us that anything that matters can be measured. It should be a good antidote to people who give up on measuring important values on grounds such as it’s too hard or too subjective (i.e. it teaches people to do Fermi estimates).

A key part of this is to use a sensible definition of the word measurement:

A quantitatively expressed reduction of uncertainty based on one or more observations

.

He urges us to focus on figuring out what observations are most valuable, because there are large variations in the value of different pieces of information. If we focus on valuable observations, the first few observations are much more valuable than subsequent ones.

He emphasizes the importance of calibration training which, in addition to combating overconfidence, makes it hard for people to claim they don’t know how to assign numbers to possible observations.

He succeeds in convincing me that anything that matters to a business can be measured. There are a few goals for which his approach doesn’t seem useful (e.g. going to heaven), but they’re rarer than our intuition tells us. Even vague-sounding concepts such as customer satisfaction can either be observed (possible with large errors) via customer behavior or surveys, or they don’t matter.

It will help me avoid the temptation of making Quantified-Self types measurements to show off how good I am at quantifying things, and focus instead on being proud to get valuable information out of a minimal number of observations.

Book review: Food and Western Disease: Health and nutrition from an evolutionary perspective, by Staffan Lindeberg.

This book provides evidence that many causes of death in developed nations are due to a lifestyle that is different from hunter-gatherer lifestyles.

His studies of existing hunter-gatherer societies show moderately good evidence that cardiovascular disease is rare, that aging doesn’t cause significant dementia, and shows weaker evidence of less cancer.

He has some vaguely plausible reasons for focusing on diet as the main lifestyle difference. I’m disappointed that he doesn’t mention intermittent fasting as a factor worth investigating (is it obvious from his experience that some hunter-gatherer societies don’t do this?).

He uses this evidence to advocate a mostly paleo diet, although with less fat than is often associated with that label.

Much of the book is devoted to surveying the evidence about other proposed dietary improvements, mostly concluding they don’t do much (or in the case of calorie restriction, might work by causing a more paleo-like diet).

I don’t have a lot of confidence in his ability to interpret the evidence.

He gives the impression that Omega-3 consumption has little effect on health, citing papers such as this review, whose abstract includes:

showed no strong evidence of reduced risk of total mortality (relative risk 0.87, 95% confidence interval 0.73 to 1.03)

I’d call that evidence for a moderately important benefit of Omega-3, and I consider it strong evidence in comparison to typical dietary studies, although it’s weak compared to the evidence that other scientific fields aim for.

One response from nutrition experts says:

The null conclusion of the Cochrane report rests entirely upon inclusion of one trial, DART 2.

A quick glance at recent publications from another author he cites (Mozaffarian) got me this:

Considerable research supports cardiovascular benefits of consuming omega-3 PUFA, also known as (n-3) PUFA, from fish or fish oil.

Excessive skepticism is probably better than hype, but it will discourage many people from reading it. Plus the style is somewhere in between a reference book and a book that I’d read from start to end.