Good Calories, Bad Calories: Fats, Carbs, and the Controversial Science of Diet and Health

Good Calories, Bad Calories: Fats, Carbs, and the Controversial Science of Diet and Health by Gary Taubes

The author of Good Calories, Bad Calories is strongly in the "carbs are bad" camp, however, he presents his argument with a fairly open mind. He believes there is adequate science out there to support the low-carb diets. However, it has been suppressed. 

There are multiple reasons for this suppression. There are some researchers that have received money from companies that pedal sugary food. This leads them to favor sugar (as opposed to fat.) There was also a loss of key German nutrition research after the world wars. Scientists have jumped to conclusions after limited studies. Then they have seen repetition of their initial hypothesis. Government policy was put in place before the science was settled. This advocacy for low-fat diets ended up biasing future work. Science disciplines are also very narrow and don't communicate well, limiting the view of what he sees as the obvious solution.

The criticisms of science are all valid. The advocacy for low-carb diet is also fairly convincing. However, with the thoroughness, you could easily advocate for just about any diet. He goes for the Occam's Razoer argument. Carbs are the simple solution, so they must be true. However, he also ties it with the argument for hormones and genetics. If it is our body that is controlling weight gain it why bother with what we eat? How is it that exercise doesn't matter?  

There are also challenges about grouping things together. Are all carbs bad? Are the groupings appropriate? What are the causes and effects? Do people really eat because they or predisposed to get fat?

Nutrition is complex. People have been getting fatter recently. Modern processed junk food seems closely correlated. But is it causation? Or is there an external factor? 

The book is a good exploration of low carb diets by a science writer. Will we ever have a solution to diet that maximizes health while also preserving the environment and economy?

Irrational Exuberance: Revised and Expanded Third Edition

The stock market is difficult to understand. People try to create explanations as to why they can beat the market, but are almost always wrong. There are many bad tendencies. People will chase past trends, hoping not to miss out. People can also be nudged by small things - even if they do not realize it is happening. In Irrational Exuberance, Shiller uses numbers and anecdotes to explain why the markets are not very explainable. Stocks will often be more closely related to others in the same country than to others in the same industry.

There is a tendency to focus heavily on nominal returns. However, if inflation is higher than the return, the purchasing power of the investment will decrease over time. People often think of houses being a great investment because they are held for so long and have a great nominal gain. The real after-inflation gain is not so rosy. There is a lot of space available to build new housing, but not necessarily where it is most desired.

Stock markets respond to news, but not in a predictable manner. The 1929 stock market crash seemed to occur in a team when no significant new news was reported. There may have been many small items that finally cascaded to put things over the edge. There could also have been feedback loops that made things worse. It is difficult to understand the details of what went on. (But many people tried!)

The Powerhouse: Inside the Invention of a Battery to Save the World

The lowly battery is perhaps the most important and most neglected technology of today. Small and efficient batteries underpin most of our modern technology. However, we rarely pay attention to battery guys. In the US, they tend to be mostly immigrants drawn from a few related disciplines, such as physics, chemistry and material science. Powerhouse focuses on a group of them, primarily associated with Argonne Laboratories in the Chicago suburbs and a battery startup Envia. There is the conflict between the corporate and the scientific world. There are pioneers like "Goodenough" who made great advancements, yet never profited. Then there are those at Envia who did make some small advancements, but oversold their world and were exposed as fraudsters. Battery science is a tricky business. Some things look good in the lab, but then have bad properties (like a significant fade of capacity or density over time or a issues scaling.) There is also the case of GM vs. Tesla. GM kept hoping for the great increase in battery technology that would help them sell an electric car. Tesla just decided to go with what was there and make a great car. Tesla's strategy has paid off. It has also helped lead to improvements in battery technology. Build a market and the science will eventually come.

The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It

The Quants is the story of some of the key players in the rise of algorithmic trading and the rise of hedge funds. These were people with backgrounds primarily in fields like Math that parlayed their skills into creating complicated models of the financial world to help make obscene riches on wall street. Their models supposedly reduced risk to manageable levels while producing outsize returns. However, they tended to rest on a backbone of people reacting rationally (adhering to Fama's Efficient Markets Hypothesis.) Alas, they often failed to account for some of the "black swans" and human behavior. This lead to catastrophic failure and the great recession of 2007.
The characters in the book come across as much more analytical than those in a book like "Liar's Poker". They are, after all, the nerds rather than the "jocks" of the trading desks. They often glory in the numbers, regardless of what the numbers are attached to. Some were leaders of big companies (like Citadel), while others were more content to exercise their might behind the scenes. Many got there start with gambling, using card counting or other tricks to help beat the odds. Wall Street is viewed as the "biggest casino" out there. (Though many also enjoy a regular game of poker.) When times were good, they made great amounts of money. And when they were not good? Well, there were quite a few companies that went belly up. The book carries on past the great recession crash, and then seems to end suddenly as our "heroes" are exploring new ways to make money.

The Signal and the Noise: Why So Many Predictions Fail--but Some Don't

We spend a hug amount of money and computational power on predicting weather, yet we still complain about inaccurate weather forecasts. In spite of this, weather forecasting is one of the "success stories". We have much more accurate forecasts than we did prior to the computational advances. However, beyond a week, weather forecasts fare no better than guesswork. Small changes in variables can significantly alter the long term prognosis. People can also cause kinks in the operations. Commercial weather forecasts have a tendency to overestimate precipitation. (They would rather have someone pleasantly surprised by a sunny day than have an activity ruined by rain.) There was also a case of flooding in North Dakota where an accurate river level prediction was made. However, only the average number was shared rather than the range. The river crested within the range, which happened to be just above the flooding level (and above the average level predicted.)
Baseball provides a rich source of data about many players. It also provides many opportunities for inaccurate predictions about players. Successful teams use a mixture of scouting and statistical analysis to find the best players for the money.
There are a number of biases in the data analysis and predictions we see. Bold predictions are most likely to get press coverage, but are least likely to be right. It is almost always possible to find a significant pattern in the "noise", but that doesn't do much good for predicting future signals. People also tend to be really bad at understanding what data means. Furthermore, news coverage tends to focus on the outliers, even though they tend to be the most inaccurate.
Coverage of global warming provides a cautionary example. There is scientific consensus on the negative impact of human activities on the earth's climate. However, consensus does not necessarily mean good science. Rather than being a balanced average of different opinions, a consensus tends to be dominated by the loudest or most forceful voice. For climate change, the initial view was simply that a greenhouse effect existed and that human activity contributed to increasing in gases. After this point, things got wonky. Discussion switched to global warming, with precise numbers given for warming predictions. When these tended to overstate the warming, the predictions were revised down and models were calibrated. However, the more extreme predictions were the ones that received more press coverage. This would distort the public's view of the situation and give greater credence to the opponents. The response to global warming involves politics, and politics is concerned with the short term impacts, not the long term results. Thus, the noise ends up being twisted towards short term purpose, while the signal is left in the scientific circles.
Predicting terrorism is a lot like predicting earthquakes. We know it is likely to happen, with the minor activities being more frequent than the high-body-count ones. However, we are not good at knowing the specifics. The September 11, 2001 attacks were "unknown unknowns". They were just not something we expected or thought to expect. This made prediction difficult. Terrorism does tend to follow a power-law distribution giving us an idea that a terror attack might be due, but no more than that. (Ironically, Israel seems to buck the power law trend. They permit small-scale attacks to happen, but focus efforts on limiting the more damaging large scale attacks.)
The real problem with predictions is people. The sensational tends to be more appealing than well-thought out. A single pronouncement is given more weight than one couched in uncertainty - even though the uncertain one is much more truthful. People also tend to value "loyalty", giving more credit to those that stick by their guns, even though a willingness to change predictions in face of data makes for more valuable predictions. What are we to do?

The Power of Habit: Why We Do What We Do in Life and Business

I had thought I wrote about this book earlier. I guess I just have a habit of delaying. Hopefully this book will get me out of the bad habits.

The book is grounded in the science of how habits influence and control our lives. Even after severe brain trauma, some habits can remain, allowing us to perform tasks without thinking. These "automatic" behaviors are a result of the habits that we have developed. Typically, the behavior starts out as a planned action until it is gradually repeated enough to become an ingrained habit. These habits are often difficult to control or change. Sometimes the only way to alter damaging habits is to run "indirection". An alcoholic may seek alcohol after a stimulus. The drinking is the habitual activity used to produce the response. To rewire the brain an alternate activity needs to be habitually substituted for the negative one in order to provide the appropriate response. Often faith in a higher power is needed to help fully rewire the brain from addictive behavior.

Habits can also be beneficial. Professional football players perform better when they let their well-trained habits guide them rather than trying to over-analyze the situations. We can all create positive habits in our life to help us to achieve our goals.

While the title of the book includes "business", that appears to be habitually tagged on to drive sales. This is a book geared primarily towards the individual seeking to improve their life and fill it with good habits.