Are you tired of seeing and hearing bullshit? Me, too! And so are a lot of other people. We can do something about it. We can fight back. We can call-out bullshit, and we can help our friends and families spot it and call it out, too.
Bullshit: very easy to create, very hard to clean up.
Neil Postman, in his 1969 speech “Bullshit and the Art of Crap Detection” (included below), states his Third Law as:
“At any given time, the chief source of bullshit with which you have to contend is yourself.”
It’s crucial that we constantly evaluate the information we choose to believe and share.
Neil Postman and Carl Sagan helped us tune-up our crap detectors 50 years ago:
Book available through all booksellers.
Seeing through the illusions of a fabricated world:
Professors – and professional BS-spotters – Jevin West and Carl T. Bergstrom have created a college course (which we can access for free!) and written a book to help us all spot bullshit, call bullshit, and avoid becoming the victim of bullshit. Below is their presentation of a set of instructional essays on various aspects of bullshit detection and refutation. Many of the examples they draw upon are classic examples that others have brought to light in their articles, essays, blogs, and other sources.
Tools and Tricks:
Data graphics tell stories. Fairly subtle choices on the part of their creators can influence the stories they tell, sometimes in misleading fashion. We look at how the ranges shown on axes can be misleading, and explore the classic issue of when the y-axis of a graph needs to include zero.
Any scientific paper can be wrong, but you greatly decrease the chances of being misled if you know how to distinguish legitimate articles from untrustworthy ones. We discuss how to draw this distinction, and along the way provide a brief overview of how the scientific publication process works.
Many data graphics, including bar charts and pie charts, use the sizes of shaded areas to represent data values. We describe what we call the principle of proportional ink: in such charts, the amount of ink used to represent a value should be directly proportional the value itself. Unfortunately, this principle is commonly violated. We explore a number of examples.
Recent developments in artificial intelligence have made it possible to rapidly generate photorealistic images of people who don’t even exist. While these are indistinguishable from real faces at a glance, you can learn to tell the difference with just a bit of practice.
A free publication describing the current state of the science of misinformation and its debunking. Available in 12 languages on the website. You can read the English version above, and the Spanish version to the left.
They certainly don’t tell all sides but they present many sides!
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