
In the near term, at least, the most common form of human/android cooperation will involve more assistance than autonomy on the part of the androids. This trend will be especially clear in the areas that involve higher-level thought, such as rhetorical fallacy detection. Nevertheless, that kind of cooperation can transform the knowledge workplace.
Image by Ordered_Chaos, courtesy Pixabay.
Rhetorical fallacies are linguistic constructions that cause communications to produce results that deviate from what rational exchange would have produced. In many instances, when people use rhetorical fallacies with intent, they're disingenuous, unfair, or even dishonest. But some rhetorical fallacies are so subtle that their users rarely realize that they're confused. What they're saying or writing is leading them to unintended conclusions that differ from what clear thinking would have produced.
The fallacy called begging the question is one of these. It has been distorting debates and decisions since the time of Aristotle — almost 2500 years ago.
Defining the fallacy
In The fallacy called begging the question has
been distorting debates and decisions since
the time of Aristotle — almost 2500 years agoits essentials, to beg the question is to appear to demonstrate the validity of a conclusion in a way that assumes at least one premise without evidence. More often, though, begging the question is defined as using in our argument the very conclusion we're trying to prove. Example:
The golden retriever is the best breed for families with young children. Since we have children, we should choose a golden retriever.
The passage above reads as if it was logically sound, but its conclusion is unproven. It provides no evidence supporting the first statement (golden retriever is the best breed). The ability of this fallacy to fit into illogical passages that appear to be logical is what makes begging the question so dangerous as a rhetorical fallacy.
A long tradition of scholarship…and recent confusion
The fallacy we call "begging the question" was identified by Aristotle in Book VIII of Topics. An accessible commentary by Thomas Reid appeared in 1788, with a second edition in 1806. [Reid 1806] As Reid puts it, begging the question, "… is done when the thing to be proved, or something equivalent, is assumed in the premises."
Oddly, though, since about 1990, in the English language, there has been some confusion. There is growing use of a construction similar in form to the phrase "begging the question," but entirely unrelated to its meaning. I refer to the form, "begs the question," used in a context in which it means, "raises the question." [Ammer 2006] [Klems 2008]
Grammatically incorrect as this form is, it does have one redeeming virtue: it is not a rhetorical fallacy. It's just bad English. If you find yourself saying or writing "begs the question," when you mean "raises the question," stop. Do not Pass Go. Back up and say, "raises the question" instead.
A role for artificial teammates
With regard to rhetorical fallacies, one might reasonably assert, "If even well-educated people have been using or have been fooled by rhetorical fallacies for thousands of years, then obviously, we can't do anything about it." Actually, that statement is itself an example of Begging the Question. It presumes, without evidence, that a solid education should be sufficient for preventing someone from using or being fooled by rhetorical fallacies.
But failure to notice a rhetorical fallacy might result from factors other than substandard education. For example, confirmation bias (one of hundreds of cognitive biases) can cause us to tend to accept a flawed argument when the conclusion is consistent with our existing beliefs. Strong emotional attachment to a conclusion can have a similar effect.
Controlling the effects of factors such as these requires discipline and energy, which might not be available at the end of a long day of contentious meetings. There is thus an opportunity here for AI teammates. [Kaelin et al. 2024] AI teammates don't have "long days." They remember every interaction. They could be trained to detect logical fallacies in email, text messages, and meetings. [Jin et al. 2022] Even before they become capable of human-level fallacy detection rates, they can likely be serviceable assistants to human fallacy detectors. Top
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