Real-World Probability Books: Society

Tetlock, Philip E. Expert Political Judgment: How Good Is It? How Can We Know? Princeton University Press, 2007.

To quote two reviews:

This book is a rather dry description of good research into the forecasting abilities of people who are regarded as political experts. It is unusually fair and unbiased.

Tetlock shows conclusively two key points. First, the best experts in making political estimates and forecasts are no more accurate than fairly simple mathematical models of their estimative processes. This is yet another confirmation of what Robyn Dawes termed "the robust beauty of simple linear models." The inability of human experts to out-perform models based on their expertise has been demonstrated in over one hundred fields of expertise over fifty years of research; one of the most robust findings in social science. Political experts are no exception.

Secondly, Tetlock demonstrates that experts who know something about a number of related topics (foxes) predict better than experts who know a great deal about one thing (hedgehogs). Generalist knowledge adds to accuracy.

For my STAT 157 course the Methodological Appendix is a nice resource. For everyone, Chapter 4 contains a wondeful categorization of excuses that experts make when their predictions turn out to be wrong.

Tetlock, Philip E. and Gardner, Dan. Superforecasting: The Art and Science of Prediction. Crown, 2015.

See my review.

Kucharski, Adam. The Rules of Contagion: Why Things Spread--And Why They Stop. Basic Books, 2020.

Essentially no math, but a somewhat more scholarly (compared to Gladwell) style of stories relating literal epidemics and their analogs for the spread of opinions, preferences, or practices, and nowadays fake news or cat videos. See my brief review or my long review for AMS Notices.

Gladwell, Malcolm. The Tipping Point: How little things can make a big difference. Little, Brown 2000.

Fascinating collection of stories on the theme of how small changes in human society/behavior can make a big difference, in contexts of crime, fashion, rumors, etc. No explicit math, but the "Endnotes" refer to more scholarly work. Good source for reading projects.

Taleb, Nassim Nicholas. The Black Swan: The impact of the highly improbable. Random House, 2007.

Here is my rather long review.

Brenner, Reuven and Brenner, Gabrielle and Brown, Aaron. A World of Chance: Betting on religion, games, Wall Street. Cambridge University Press, 2008.

See my review.

Sandel, Michael J. The Tyranny of Merit: What's Become of the Common Good? Farrar, Straus and Giroux, 2020.

Far removed from quantatitave probability, but on the theme that luck makes true meritocracy impossible and undesirable. See my review.

Ball, Philip. Critical Mass: How one thing leads to another. Farrar, Straus and Giroux, 2004.

The theme is statistical physics style models of interacting agents -- "how patterns of behavior emerge from the statistical melee of many individuals doing their own idiosyncratic thing: helping or swindling each other, cooperating or conflicting, following the crowd or blazing heir own trail". Contains verbal descriptions of around ten specific models (e.g. for vehicle and pedestrian traffic; for alliance formation or cultural dissemination; for peer pressure effect on criminality; for company size being determined by individual employees income-leisure preferences). And contains summaries of classical theories. Easy to read, as befits a professional science writer. But (to my taste) too much grandiose theorizing and too much credulity regarding significance or impact of these models.

Miller, John H. and Page, Scott E. Complex Adaptive Systems: An introduction to computational models of social life. Princeton University Press, 2007.

Useful descriptions of a range of mathematical models, some involving probability (though not as primary emphasis).

Watts, Duncan J. Six Degrees. The science of a connected age. W.W. Norton, 2003.

Presents general background to social networks - how ideas, information or epidemics spread between people. Gives brief indications of some math models in this field, so a good source for reading projects. But exaggerates the significance of this kind of analysis.

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