[This post was originally published on Stephen Few's Perceptual Edge blog in April, 2016.]
In recent decades, one of the most well-supported findings from research in various sub-disciplines of psychology, philosophy, and economics is that we all commit elementary reasoning errors on an alarmingly regular basis. We attribute the actions of others to their fundamental personalities and values, but our own actions to the circumstances in which we find ourselves in the moment. We draw highly confident conclusions based on tiny scraps of information. We conflate correlation with causation. We see patterns where none exist and miss very obvious patterns that don’t fit with our assumptions about how the world works.
Even “expert reasoners” such as trained statisticians, logicians, and economists routinely make basic logical missteps, particularly when confronted with problems that were rare or non-existent until a few centuries ago, such as those involving statistics, evidence, and quantified probabilities. Our brains simply haven’t had time to evolve to think about these new types of problems intuitively, and we’re paying a high price for this evolutionary lag. The consequences of mistakes, such as placing anecdotal experience above the results of controlled experiments, range from annoying to horrific. In fields such as medicine and foreign policy, such mistakes have certainly cost millions of lives and, when reasoning about contemporary problems such as climate change, the stakes may be even higher.
As people who analyze data as part of our jobs or passions (or, ideally, both), we have perhaps more opportunities than most to make such reasoning errors, since we so frequently work with large data sets, statistics, quantitative relationships, and other concepts and entities that our brains haven’t yet evolved to process intuitively.
In his wonderful 2015 book, Mindware: Tools for Smart Thinking, Richard Nisbett uses more reserved language, pitching this “thinking manual” mainly as a guide to help individuals make better decisions or, at least, fewer reasoning errors in their day-to-day lives. I think that this undersells the importance of the concepts in this book, but this more personal appeal probably means that this crucial book will be read by more people, so Nisbett’s misplaced humility can be forgiven.
Mindware consists of roughly 100 “smart thinking” concepts, drawn from a variety of disciplines. Nesbitt includes only concepts that can be easily taught and understood, and that are useful in situations that arise frequently in modern, everyday life. “Summing up” sections at the end of each chapter usefully summarize key concepts to increase retention. Although Nesbitt is a psychologist, he draws heavily on fields such as statistics, microeconomics, epistemology, and Eastern dialectical reasoning, in addition to psychological research fields such as cognitive biases, behavioral economics, and positive psychology.
The resulting “greatest hits” of reasoning tools is an eclectic but extremely practical collection, covering concepts as varied as the sunk cost fallacy, confirmation bias, the law of large numbers, the endowment effect, and multiple regression analysis, among many others. For anyone who’s not yet familiar with most of these terms, however, Mindware may not be the gentlest way to be introduced to them, and first tackling a few books by Malcolm Gladwell, the Heath brothers, or Jonah Lehrer (despite the unfortunate plagiarism infractions) may serve as a more accessible introduction. Readers of Daniel Kahneman, Daniel Ariely, or Gerd Gigerenzer will find themselves in familiar territory fairly often, but will still almost certainly come away with valuable new “tools for smart thinking,” as I did.
Being aware of the nature and prevalence of reasoning mistakes doesn’t guarantee that we won’t make them ourselves, however, and Nisbett admits that he catches himself making them with disquieting regularity. He cites research that suggests, however, that knowledge of thinking errors does reduce the risk of committing them. Possibly more importantly, it seems clear that knowledge of these errors makes it considerably more likely that we’ll spot them when they’re committed by others, and that we’ll be better equipped to discuss and address them when we see them. Because those others are so often high-profile journalists, politicians, domain experts, and captains of industry, this knowledge has the potential to make a big difference in the world, and Mindware should be on as many personal and academic reading lists as possible.