Point Lookout: a free weekly publication of Chaco Canyon Consulting
Volume 25, Issue 10;   March 5, 2025: On Begging the Question II

On Begging the Question II

by

Some of our most expensive wrong decisions have come about because we've tricked ourselves as we debated our options. The tricks sometimes arise from rhetorical fallacies that tangle our thinking. One of the trickiest is called Begging the Question.
A human shaking hands with an android

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 its 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 The fallacy called begging the question has
been distorting debates and decisions since
the time of Aristotle — almost 2500 years ago
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. Go to top Top  Next issue: Embedded Technology Groups and the Dunning-Kruger Effect  Next Issue

303 Secrets of Workplace PoliticsIs every other day a tense, anxious, angry misery as you watch people around you, who couldn't even think their way through a game of Jacks, win at workplace politics and steal the credit and glory for just about everyone's best work including yours? Read 303 Secrets of Workplace Politics, filled with tips and techniques for succeeding in workplace politics. More info

Footnotes

Comprehensive list of all citations from all editions of Point Lookout
[Reid 1806]
Thomas Reid. Analysis of Aristotle's Logic, with Remarks (second edition). Printed for William Creech; and sold by J. Murray, Fleet-street, London, 1806. Available here. Retrieved 20 February 2025. Back
[Ammer 2006]
Christine Ammer. The Facts on File Dictionary of Clichés, 2nd Edition: Meanings and Origins of Thousands of Terms and Expressions. New York: Checkmark Books, 2006. Back
[Klems 2008]
Brian A. Klems. "Begging the Question: How to Use It Correctly," Writer's Digest Blog, July 29, 2008. Available here. Retrieved 11 February 2025. Back
[Kaelin, et al., 2024]
Vera C. Kaelin, Maitreyee Tewari, Sara Benouar, and Helena Lindgren. "Developing teamwork: transitioning between stages in human-agent collaboration," Frontiers in Computer Science 6 (2024). DOI:DOI 10.3389/fcomp.2024.1455903. Available here. Retrieved 10 December 2024. Back
[Jin, et al., 2022]
Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea, and Bernhard Schoelkopf. "Logical fallacy detection," arXiv preprint arXiv:2202.13758 (2022). Available here. Retrieved 13 February 2025. . Back

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