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Stephen Colbert and Philosophy - Aaron Allen Schiller [21]

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have to worry about the truth. Such careful thought bogs Colbert down, leading to his utter disregard for science. Rather than value the scientific method for facing biases, Colbert terms scientists “fanatical” because they “put their blind faith in empirical observation” (I Am America, p. 191).

Colbert interviews Janna Levin, a novelist who relies on science:

COLBERT: You’ve written a book, A Madman Dreams of Turing Machines. Now this is science. But it’s also a novel.

LEVIN: Yes.

COLBERT: So you admit that most science is fiction.32

This all or nothing thinking is technically called the fallacy of composition . In this fallacy, rather than pursue any interest in informing yourself, you leap from a fact about a single part to an overgeneralization about the entire whole. Because the science is embedded in a work of fiction, Colbert assumes that all of science must be fiction. The error he makes is to blur the science and fiction within the book and then leap to blur science and fiction outside of the book.

Eventually, however, he actually asks after the truth:

COLBERT: Why is there something, rather than nothing?

LEVIN: We actually don’t know.

COLBERT: Hah, I stumped a theoretical physicist. And all it took was the hardest question in the world. I got a bucket full of them.33

Rather than seek understanding, Colbert is disdainful that he could make an intellectual admit ignorance—on the assumption that smart people don’t say “I don’t know.” This illustrates the logical fallacy of an appeal to ignorance, where you assume that just because something can’t be proven false, it must be true, or in this case, just because something can’t be proven true, it must be false. But then Colbert admits it’s the hardest question in the world, giving himself credit for stumping his guest. Interestingly, however, when he says there’s more where that came from, implying he could further stump anyone, he actually reveals that we’re all ignorant and that there are many unanswered questions.

In another instance of an all or nothing dismissal, Colbert attempts to “nail” Australian scientist Tim Flannery, author of The Weather Makers:

COLBERT: Our president is going to take action on this as soon as all the science is in. That’s what he said. Is all the science in, sir? All of it. Simple question: yes or no. Is ALL the science in? ALL of it!

FLANNERY: Certainty is a rare thing in this world. You know, we educate our kids with no certain outcome. We buy certain stocks and bonds without a certain outcome. We live in a world of probabilities. And the scientific probabilities are that we are having a big impact on this climate of ours. So I don’t think you can wait for certainty. You’ll be dead before you can get it.34

What Colbert’s character misses is the fact of “non-allness,” a term in general semantics for the idea that one can never know everything about anything. This fact flies in the face of our intuition that science determines “truth.” In reality, scientists only ever determine what is “probable.” By contrast, Colbert only thinks it’s possible to know everything because it’s only to himself that he ever looks for the truth. If instead we think critically, we realize that answers are often neither absolutely certain nor totally unknowable, but exist on a continuum, along shades of gray, from highly unlikely to highly likely.

Systematically Anti-Systematic: He Said, She Said, Enough Said


Systematic:

• alertness to opportunities for critical thinking

• routinely justifying reasoning in terms of standards and contextual factors used

Interviewing Philip Zimbardo, the psychologist behind the classic Stanford prison experiment and author of The Lucifer Effect: How Good People Turn Evil, Colbert quibbles:

COLBERT: How do you know what authority is unjust or not? I mean, you do what people tell you to do who are in power and then you have to trust that that’s the right thing to do. What else is society based on?

ZIMBARDO: It’s based on being mindful and doing critical

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