“The amount of energy needed to refute bullshit is an order of magnitude bigger than [that needed] to produce it.”
7 years since the quote was uttered by Italian software engineer Alberto Brandolini, this has only gotten worse. If there’s one thing that I’m taking away from Calling Bullshit, it is despair for the severity it paints. When read in the context of this piece on Facebook, as financial incentives run amok, the problem feels insurmountable.
Misinformation is the ailment of our age. As the concept enters our collective lexicon, much has been discussed around all forms of media but little done or could be done. While this book deals with topics of tortured logic and willful twistings of information, it runs behind the current phenomena of patently made up stuff. Even the authors, credentialed as they are, could not predict the influence of QAnon and events around the January 6 insurrection.
Back to the book. It reads well and presents like a thick binder of case studies on how information is used to mislead. The examples were plentiful and succinct to the point. If you are familiar with the work of Edward Tufte or other data visualization writers, you will be familiar with many of the examples presented in the book.
The book opens with a historical view of how information technologies evolve and the authors present their case for optimism (if somewhat tepid). The next chapter provides a definition of Bullshit, which is a little more scientific in its uses than my occasional exclamation:
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.
The later chapters are organized around specific topics: causality, numbers, selection bias, data visualization, big data and machine learning, and science. They are useful lenses to view the various techniques (if you can even call it that) that misinformation authors use to bring illegitimate authority to their arguments. For example, examining Machine Learning models as black boxes (I mean, they are black boxes even to the model authors) provides a useful way to critically engage with the discussion without being overwhelmed by the technical arguments (i.e., hand wave AI). In the last two chapters, the authors Bergstrom and West concludes with a few mental tools to help readers spot and refute Bullshit.
In this post truth world, it is hard to run away from the feeling of needing to process information with a fact checker running constantly. Despite the authors’ best intentions, this is an exhausting way to live. I’m not sure if there’s a solution; over time people will adapt to this new information environment. Things will happen.
Calling Bullshit is a useful documentation of the misinformation environment in the last few decades. However, this is far from over and it leaves me wondering what more is in store.