Carl T. Bergstrom and Jevin West from the University of Washington have developed a course (not yet offered or endorsed by the university), “Calling Bullshit in the Age of Big Data” designed to help students identify “language intended to persuade by impressing and overwhelming a reader or listener, with a blatant disregard for truth and logical coherence.”
While bullshit may reach its apogee in the political sphere, this isn’t a course on political bullshit. Instead, we will focus on bullshit that comes clad in the trappings of scholarly discourse. Traditionally, such highbrow nonsense has come couched in big words and fancy rhetoric, but more and more we see it presented instead in the guise of big data and fancy algorithms — and these quantitative, statistical, and computational forms of bullshit are those that we will be addressing in the present course.
Of course an advertisement is trying to sell you something, but do you know whether the TED talk you watched last night is also bullshit — and if so, can you explain why? Can you see the problem with the latest New York Times or Washington Post article fawning over some startup’s big data analytics? Can you tell when a clinical trial reported in the New England Journal or JAMA is trustworthy, and when it is just a veiled press release for some big pharma company?
Our aim in this course is to teach you how to think critically about the data and models that constitute evidence in the social and natural sciences.
Here are the learning objectives:
After taking the course, you should be able to:
- Remain vigilant for bullshit contaminating your information diet.
- Recognize said bullshit whenever and wherever you encounter it.
- Figure out for yourself precisely why a particular bit of bullshit is bullshit.
- Provide a statistician or fellow scientist with a technical explanation of why a claim is bullshit.
- Provide your crystals-and-homeopathy aunt or casually racist uncle with an accessible and persuasive explanation of why a claim is bullshit.
We will be astonished if these skills do not turn out to be among the most useful and most broadly applicable of those that you acquire during the course of your college education.