This is a summary of the book titled “Decisions about Decisions” written by Cass R Sunstein and published by Cambridge UP in 2023. He studies how people think and proposes a set of useful decision-making strategies, including schemes that eliminate routine decisions, digs out relevant information, corrects unconscious biases and frees up by delegating to experts or algorithms. Since decision making involves emotions, it must be engineered to be straightforward. Information plays a complex role in decision making. Sometimes our beliefs are based on our decision to believe. Computer-based algorithms is ever-increasing second order decision making.

Decision-making can evoke strong emotions, which influence judgment. People have devised strategies to mitigate the emotional stress of making decisions, such as "second-order" strategies. These strategies include leaving the choice up to chance, setting rules that predetermine options, and breaking problems into smaller steps. Experts in economics, politics, and psychology view decision-making as a straightforward process, but also use second-order strategies to overcome obstacles.

There are three main types of second-order strategies: "high-low" strategies, which involve establishing protocols for routine issues, "low-low" strategies, which minimize the burdens faced throughout the decision-making process, "low-high" strategies, which delegate the choice to someone else, and "high-high" strategies, which produce high burdens both during preparation and decision-making.

Information plays a complex role in decision-making, as people often avoid irrelevant or potentially useful information. Decision-makers assess information's instrumental value, which enhances autonomy or power, and its "affective value," which evokes positive emotions.

People seek information for curiosity and to make life richer and more meaningful. Emotional reactions to good and bad news influence their decision to find news credible. People make internal predictions about the impact of new information on their feelings, but these predictions can be influenced by bias and cognitive quirks. People believe some ideas because they make them feel good, while others avoid information that contradicts their beliefs. People's willingness to hear bad news depends on whether they believe it can improve their condition. Many beliefs stem from a decision to believe, either consciously or unconsciously. Climate change illustrates the complex relationship between information and belief, with people responding differently to new information. Research on acceptance of beliefs about climate change demonstrates how people with different beliefs respond to new information, with those who strongly believe in anthropocentric climate change employing strategies of "asymmetrical updating."

Climate change is a growing threat, with people who strongly believe in its danger more accepting of bad news. Those less certain about its dangers use an "opposite asymmetry" and modify their beliefs when they encounter good news. A moderate belief in climate change gives the same weight to both good and bad news. People change their beliefs when the outcome of a new belief holds more value for them than the payoff for clinging to an old belief. Holding certain beliefs can lead to external and internal outcomes, either positive or negative. External outcomes include tangible consequences like financial rewards, while internal outcomes are cognitive or affective consequences. Policymakers should consider all possible outcomes when predicting or influencing people's beliefs. Fact-based efforts to counter "fake news" may fail as correcting inaccurate information threatens people's sense of well-being.

Consumer decisions are influenced by social dynamics, with people choosing products for both their inherent value and social value. Social goods include events consumed in groups or private, while exclusivity goods increase in value if only a limited number of people can enjoy them. Governments often promote and fund solidarity goods that enhance societal well-being, such as educational programming, sports teams, and public resources.

Using computer-based algorithms is a growing "second-order" decision-making strategy, but it can lead to prediction problems. Algorithms can be more effective than human beings at forecasting future conditions, but current offense bias can affect judgment. Algorithms can help judges avoid acting based on this bias.

Experts' judgment can falter due to availability bias, as they often rely on recent comparable situations, leading to mental shortcuts rather than thorough consideration of relevant statistics.

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