Despite the pop title, “Calling Bullshit: The Art of Skepticism in a Data-Driven World” is actually a tough-minded guide to spot, deconstruct and refute misinformation, fake news, and false data that abound in our society. To me, the materials and ideas covered in the book can also serve as an educational resource for epidemiology students.
Coming from a non-English speaking background, I have always thought that ‘bullshit’ is a kind of foul language. And, I was somewhat shocked to see the word in the book’s title. However, it turns out that this interesting word is well accepted in scientific and philosophical discourse. Harry G. Frankfurt is perhaps the most important philosopher who has laid the theoretical foundation for the study of bullshit. In his bestseller treatise, On Bullshit, Professor Frankfurst does not exactly define what bullshit is, but he considers that bullshit is a by-product of public life where “people are frequently impelled — whether by their own propensities or by the demands of others — to speak extensively about matters of which they are to some degree ignorant.” Bullshitting is different from lying: liars know the truth but engage in a conscious act of deception, bullshiters don’t care about the truth and don’t consciously deceive. Frankfurt observes that bullshit is “one of the most salient features of our culture”.
In Calling Bullshit, Bergstrom and West go further and provide an operational definition of bullshit as follows: “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 truth, logical coherence, or what information is actually being conveyed.” (Page 40).
So, ‘bullshit’ in this context seems like ‘nonsense’ or ‘falsehood’ to me.
In any case, based on that operational definition, the authors dive into a dense and thoughtful examination of the nature of bullshit (Chapter 3), causal inference (Chapter 4), and the fragility of science (Chapter 9). The authors draw background knowledge from many academic fields such as medical sciences, biology, statistics, social science, psychology, and language to cover issues relating to the interpretation of…