The Difference Between a Liar and a Bullshitter
October 2, 2026 - 9:13 am
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Back in 1986, a Princeton philosopher named Harry Frankfurt published a short essay with a title you don’t expect to see in an academic journal, “On Bullshit.” It stayed largely inside academic circles for the better part of twenty years. Then, in 2005, Princeton University Press reprinted it as a tiny hardcover, 67 pages, small enough to fit in your back pocket. Within a month, it had sold more than 110,000 copies—a philosophy professor’s little book with a rude word title suddenly became a runaway bestseller.
On Bullshit’s whole argument rests on a distinction most of us have never bothered to make, even though we encounter both kinds of people daily...
A Liar and a Bullshitter Aren’t the Same Animal
The liar knows the truth. That’s key about them. They know exactly what’s true, and they work hard to steer you away from it. Which means, oddly enough, the liar still respects the truth. They have to. So they keep one eye on it at all times so they know what to hide. The liar and the honest person are playing the same game, just on opposite sides.
The bullshitter isn’t playing that game at all. They don’t know what’s true and they don’t care. They’ll tell you the sky is green if green gets them through the conversation, and blue thirty seconds later if that works better. Truth and falsehood are equally indifferent to them because they aren’t aiming at either one. They’re aiming at sounding good.
That, Frankfurt argued, makes the bullshitter more dangerous than the liar. The liar at least admits the truth exists somewhere. The bullshitter doesn’t care if it does or not.
Now, let’s talk about your LLM AI.
Your LLM AI Isn’t Lying to You; It’s a Bullshitter
There’s a comforting story people tell about LLM AI hallucinations: the machine “made a mistake,” “got confused,” or “lied.” We’ve been conditioned to let it slide, but none of those are quite right. The difference isn’t as simple as splitting hairs.
Here’s the plain truth: a large language model doesn’t know what’s true. It was never built to.
Underneath all the flash and polish, it’s guessing the next word based on patterns in its training data. Its connection to reality is as tenuous as a weathervane to the wind—it points whichever way the probabilistic breeze takes it, just as convincingly whether it’s right or making up complete fiction.
In other words, your LLM AI isn’t a liar; it’s a bullshitter. And this isn’t some academic debate. The numbers bear it out. In a 2024 Stanford study, models tested hallucinated in 58 to 88 percent of answers to specific, verifiable questions about federal court cases. That’s the result from legal research questions where convincing-sounding answers could end up in a brief with someone’s name on it.
The lawyers in Mata v. Avianca found this out the hard way. One used ChatGPT for legal research and submitted a brief citing non-existent cases, even providing fabricated opinions when asked by the court.