Noise: A Flaw in Human Judgment

Noise is a random deviation from the norm. This differs from bias, which is a uniform differentiation. They both lead to bad results. Noise in different directions does not necessarily cancel out, but is additive. (If you end up 10 feet north of the target once, and 10 feet south the other time, you are equally inaccurate both times.) Eliminating noise and eliminating bias are key to making good decisions.

A challenge with many decisions is that we don't know what the "correct" answer is. Job interviews and prison sentencing are particular cases where there are bad amounts of "noise". Some small nuances in behavior can help. A number of distinct observations is likely to more accurately lead to the correct outcome. However, that only works if they are truly independent. When people meet together to talk, there is a desire to have consensus. Thus people are likely to alter their opinions to meet the first stated view. This can often lead to settling on a more extreme view. Independently collected feedback can provide a better outcome. In interviews, it also helps if interviewers have a distinct area to focus on rather than a general feel.

Computer algorithms can help with noise. They tend to apply rules much more accurately and reduce noise. Many times they are better than humans. However, this can sometimes be seen as negative, especially if there is not an equal distribution throughout society. There can also be challenges of handling rare outcomes. (A rare outcome that is missed by computers will get a lot of publicity, even if there were a great many more successes.)

People want perfection. However, they don't want the sacrifices to get it. People will complain about wildly different sentences for similar crimes. But then they will complain about fixed sentences guidelines that take out judicial discretion. Do we mandate rules or simply have guidelines? Noise can be nice in leading to different outcomes. However, most often it just leads to things being worse than expected.

Thinking Fast and Slow

Thinking Fast and Slow is Nobel Prize-winner Daniel Kahneman's very accessible work about how we think. He anthropomorphizes the quick, impulsive "System One" and the slow, methodical "System Two" as the two parts of our thinking process. System One will often provide us with our "gut" reactions without us seeming to process it. People who are trained with much experience in certain situations will often find System One guiding their reactions, seemingly without them understanding why. (An example was a firefighter who told everyone to evacuate just before a collapse.) System Two is a much slower process and what we use for detailed thinking. Of particular interest was his description of collaboration with his "opponent" Gary Klein and a publication of "A Failure to Disagree". It was interesting to see how two opposing sides could come to realize they agree on a lot.
Kahneman's work has helped to explain a lot of areas where the "rational agent" of economics fails to follow the rules. People often respond to situations based on their given baseline. It tends to be much more painful for people to "lose" than it is beneficial for them to "win". Using this knowledge, many odd behaviors can be explained. Even when we know about a given situation, our initial instinct is often to do it in our "gut" way.

The Undoing Project

Amos Tversky and Daniel Kahneman were both born in Israel and later studied psychology there. Beyond that, they seemed to have little in common. Kahneman lived in France during World War II and had experiences running from Nazis. He tended to be more to himself, while Tversky seemed to know everything and be more social. Once they met, they found they had a great meeting of the minds and were able to achieve more together. They wrote a number of influential papers in their time together. They gradually drifted apart as Tversky received more public recognition. However, he died of cancer, and it was Kahneman that later received the Nobel prize.
Michael Lewis starts The Undoing Project by providing anecdotes of showing the fallacy of human judgement. In sports, picking the right players can have a serious impact on the success of a franchise. However, scouts are prone to use their gut, often missing out on great players. Using data can help avoid some of the human fallacies - but even the data requires some human judgement. The narrative then dives in to the biography of the psychologists.
Both Kahneman and Tversky had a rebellious streak. They didn't fully trust common theories - especially full rationality. People are prone to many biases that allow them to be fooled. When discussing a past event, people often engage in hindsight bias, exaggerating their perceived odds that the event would have occurred. When choosing among multiple items, it is not uncommon for people to prefer A to B, B to C and C to A, seemingly contradicting basic logic. Due to endowment and sunk costs, people are more likely to hold on to something they already have - even though they would never purchase it. The fear of loss is more powerful than the desire for gain. Even if two outcomes are the same, most people would much rather avoid the outcome with loss rather than one with a gain.
The title comes from one of their final works together. What does it take to mentally "undo" something. People experience much more grief if they appear close to gaining something than if they were nowhere near. Missing a winning lottery number by one digit would be traumatic, while missing it by 5 would barely be noticed. However, both cases have the identical outcome of no win. In one, it was just easier to visualize moving over. When undoing events, we often look at the most proximate, easy to visualize causes, even if they are not the most probable.
Knowledge of inbuilt human biases can be used to help improve decision making. However, these same biases can also be used to manipulate people.