N.B.: This is Part 4 of my series on “Critical thinking in the age of A.I.”

In my previous post, I turned to David Hitchcock’s survey article in the SEP to revisit several salient critiques of the theory, pedagogy, and practice of critical thinking, and I concluded my review of these criticisms with two questions: “Which of these objections … is the most damaging one to my own Humean/Bayesian approach to critical thinking, and which … are also relevant to large language models like ChatGPT?” Let’s begin with John McPeck (1981)’s critique that there are no general thinking skills, since thinking is always thinking about some subject-matter within a specific field, the so-called “strong subject-specificity thesis”. Although McPeck’s claim is ultimately unpersuasive, it does help us see why ChatGPT represents such a grave danger to higher ed.

To begin with, there are two problems with McPeck’s critique. One is purely academic or definitional: the concept of a “field” or a “subject” is a vague one, since all knowledge is interconnected. The other problem, however, is fatal: even if we could agree on such definitions, McPeck’s strong subject-specificity thesis is subject to “obvious counter-examples”, including the existence of general inter-field principles (e.g. parsimony, originality, usefulness, etc.), the general hypothetico-deductive model of reasoning (i.e. making predictions and comparing them with observed data), as well as general or overarching logical principles, like the ability to recognize confusion of necessary and sufficient conditions. (For my part, I would add my Humean-Bayesian approach to critical thinking as another counter-example, for however narrowly or broadly the concept of a field or subject is defined, one has to be able to evaluate evidence and update one’s beliefs when new evidence becomes available.)

Nevertheless, as Hitchcock concedes (2024, 12.1), a prerequisite for critical thinking is “background knowledge”, the basic facts of the field (however defined) one is operating in: “It is common ground in debates about the generality or subject-specificity of critical thinking dispositions and abilities that critical thinking about any topic requires background knowledge about the topic.” For example, even the most sophisticated understanding of my Humean-Bayesian approach to critical thinking is of no help unless accompanied by some knowledge of what counts as relevant evidence and how much weight to assign to such evidence.

And it is on this particular point (i.e. the all-important question of what counts as relevant evidence and how much weight to assign to the evidence), we can now begin to understand how ChatGPT poses a powerful pincer attack on critical thinking. (A pincer movement, or “double envelopment” or “hammer and anvil” tactic, is a military maneuver in which one’s forces simultaneously attack both flanks or sides of one’s adversary with the aim of encircling and trapping the enemy formation.) To the point, ChatGPT attacks critical thinking in two ways. First off, it dispenses with the need to learn any basic facts or develop any background knowledge at all about the topic being explored by the user, since most AI models like ChatGPT are trained on massive datasets primarily consisting of publicly-available Internet content, including presumably Google Scholar, the Stanford Encyclopedia of Philosophy, and Wikipedia, and thus already has all the relevant background knowledge at its disposal.

Secondly, ChatGPT not only does the thinking for us, so to speak, by providing plausible answers to any particular problem or question one may have; it also provides well-reasoned answers to our problems and questions, thus dispensing with the need for any thinking altogether, let alone critical thinking! (See, for example, this intriguing new paper by Damien Charlotin (HEC Paris) and Niccolò Ridi (King’s College London) in which two popular LLM models, Google’s Gemini 2.0 and OpenAI’s GPT4o, competed in the Jessup International Law Moot Court Competition and garnered higher scores than many humans in legal reasoning.)

To recap the potential double-edged threat that ChatGPT poses to critical thinking, why would anyone take the time to learn basic facts or develop background knowledge (or write a legal brief for a moot court competition) if ChatGPT already has those facts and background knowledge at its disposal? Likewise, why waste any time with my Humean/Bayesian approach to critical thinking if ChatGPT can not only evaluate and weigh the evidence for us, but can do so faster and maybe even more accurately? In short, why take the trouble to think if ChatGPT can think for us? Is there any effective way to escape or counteract this powerful pincer attack? And what about the many other critiques of the theory, pedagogy, and practice of critical thinking that I surveyed in my previous post? I will turn to those critiques next …