Book review: Calling Bullshit

When I led the redevelopment of our Bachelor of Management Studies with Honours degree back in 2018 (see more here), one of the key innovations was to introduce a number of general management 'transferable skills' papers across the final two years. One of those papers was titled "Using Data for Decisions", and the intention was not to have students working directly with data, but rather to have them asking questions about data and about analyses that others have conducted. Those are core skills for a modern manager, who often does not do their own analysis (at least in medium to large firms). The lecturers of that paper have since taken it in a different direction (making students do more work with data), but if we had held close to the original ideal, then Carl Bergstrom and Jevin West's book Calling Bullshit would no doubt have been a key reading.

Interestingly, the genesis of the book was a very popular college course of the same title, which Bergstrom and West teach at the University of Washington. In the Preface, they note their intention for the book:

We hope it will show you that you do not need to be a professional statistician or econometrician or data scientist to think critically about quantitative arguments, nor do you need extensive data sets and weeks of effort to see through bullshit.

So, you can see that this aligns with my original vision of the BMS(Hons) Using Data for Decisions paper. Of course, the book isn't just about data, it is about bullshit. Why? Bergstrom and West explain that:

The world is awash with bullshit, and we're drowning in it.

Politicians are unconstrained by facts. Science is conducted by press release. Silicon Valley startups elevate bullshit to high art. Colleges and universities reward bullshit over analytic thought... Bullshit pollutes our world by misleading people about specific issues, and it undermines out ability to trust information in general.

Bergstrom and West define bullshit as:

Bullshit involves language, statistical figures, data graphics, and other forms of presentation intended to persuade or impress an audience by distracting, overwhelming, or intimidating them with a blatant disregard for trust, logical coherence, or what information is actually being conveyed.

Fully the first ten chapters of the book (out of eleven) are essentially devoted to alerting the reader to bullshit, and (hopefully) teaching them how to spot it. Along the way, Bergstrom and West teach you about the difference between correlation and causation, selection bias, data visualisation ducks, glass slippers, and the problems associated with big data. Many of these ideas (and the examples they use) will not be new to people who are widely read in this area, but the collection of these together in one place is highly useful. They also offer one of the best explanations of what a p-value is (and what it isn't) that I have read in a popular book.

It is not until the final chapter that Bergstrom and West turn their attention to how they propose that we should refute bullshit, because of course it is not enough simply to call bullshit unless you are prepared to back up your calls and stand by them. This was the only part of the book that lacked extensive examples that would have helped to illustrate the 'dos' and 'don'ts' of calling bullshit.

I really enjoyed this book, and it is clear why the Calling Bullshit course at the University of Washington is so popular. Bergstrom and West write in a way that is easy to read, and they don't bury us in jargon (even when describing big data). And that is part of the point they are trying to make - you don't need to understand the technical language in order to think critically about quantitative claims that are being made. If you want to add a critical edge to your thinking about the array of infographics, research claims, and statistics that we are bombarded with on social media (and traditional media), then I highly recommend this book.