17. Informal Fallacies - Presumption Part 5

 

Summary

This final session of Allan Di Donato's tour through the informal fallacies completes the third major category, the fallacies of presumption, and zooms in on those that arise in inductive reasoning. The unifying theme is missing evidence: each of these fallacies tries to draw a conclusion from no real evidence at all. Because induction never yields certainty (and, some argue, never strictly yields truth), an inference built on no genuine evidence can only land on the truth by accident. Four "ultimate" fallacies round out the series.

1. Hypothesis Contrary to Fact

A hypothesis contrary to fact is an argument shaped like a "what if" game: it treats a hypothetical scenario as though it were a fact in order to support a conclusion. The pattern is "things would be this way if such-and-such were the case," but the trouble is that such-and-such is not the case, so the imagined situation carries no weight. People conjure up unobservable evidence or possible scenarios that would conveniently disprove an opponent or prop up their own view, yet unobservable evidence is not evidence, and there is no reason to accept unsubstantiated imaginary scenarios. A sound argument has to be about how things actually are in the real world.

This is also called an ad hoc hypothesis (from the Latin "to this," meaning "for this purpose"), because the hypothesis is invented purely to rescue a theory or to argue against someone else. Di Donato's examples include: "If Hitler had never invaded Russia, the Nazis would have won World War II"; "If you had taken that automotive repair course after high school, you'd be financially stable now"; the 9/11 conspiracy claim that the government staged the attacks and pays off the news networks; and the suggestion that there is no archaeological evidence for the Book of Mormon because God wants us to accept it on faith. In each case, the inventor of the scenario insulates a belief from any real-world test.

2. Fake Precision

Fake precision occurs when someone tosses out numbers or statistics that look too exact to be trustworthy. Statistics are already easy to frame and manipulate, but citing precise figures is especially problematic: some polls force a simple yes/no answer when the real situation is far more complicated, and a sample poll may be biased, meaning it is not truly representative.

His leading example is a poll claiming "most Americans believe the U.S. should pull all troops out of Afghanistan," when the question actually asked only whether troops should be withdrawn "sooner or later." That wording lets pollsters twist the data into apparent unqualified support for ending the war. Other examples are the mouthwash advertisement asserting that "over 100 million Americans have bad breath" (how could such a study even be conducted?) and the suspiciously exact claim that a president's policies "saved 10.3 million people from losing their jobs."

3. Appeal to Probability (the Gambler's Fallacy)

The appeal to probability, also known as the gambler's fallacy, is the assumption that because something can happen, it therefore will or did happen. Di Donato stresses the key distinctions: possibility does not imply probability, and probability is not necessity. Having the potential to occur does not mean an event actually occurs. He illustrates this with the famous "so you're telling me there's a chance" film clip, where a one-in-a-million chance is heard as encouragement. More serious examples include the claim that amino acids could happen to fall into the precise order needed to build proteins and cells (nothing in their nature drives them to do so), and the gambler's conviction that "since I keep losing on this slot machine, the odds are I'll eventually win if I keep playing."

4. Confirmation Bias

The series closes with confirmation bias, the tendency to seek only evidence that confirms one's own position while ignoring whatever contradicts it, accepting uncritically anything that fits one's presuppositions. Di Donato pictures everyone as having a "skeptic dial": we turn it down when gathering support for our own view and crank it all the way up when facing opposing evidence. Because data can almost always be interpreted to fit a position, people manage to find support even for the most outlandish theories (think of shows like Ancient Aliens or films like The Da Vinci Code). He notes this overlaps with special pleading and suppressed evidence discussed earlier in the course.

Crucially, he argues that having a bias is neither wrong nor irrational; we cannot escape favoring some position. But this does not mean we cannot be objective: if objectivity were impossible, no one could ever change their mind, yet people change their minds all the time. His examples of bias include "George Bush was behind 9/11 because our intelligence is too good to be outwitted by terrorists in caves" and the self-flattering reading that a girl "likes me because she looks back when I look at her."

Conclusion

These four fallacies bring the entire treatment of informal fallacies to a close. Di Donato signals that the next video will move on to the basics of inductive reasoning, staying within informal logic. The fallacies covered here will remain relevant as the course turns to examining different types of thinking.