Link to the full paper:

https://muse.jhu.edu/article/778252

The logical proof in the paper:

1. Literature has a rhetorical function.

2. Literature's full rhetorical function depends on narrative elements.

3. Narrative elements rely on causal reasoning.

4. Causal reasoning cannot be performed by machine-learning algorithms because those algorithms run on the CPU's Arithmetic Logic Unit, which is designed to run symbolic logic, and symbolic logic can only process correlation.

QED: Computers cannot perform the causal reasoning necessary for learning to use literature.

The following seems to be the most relevant part of the paper:

"""[T]here's one feature of human learning that computers are incapable of copying: the power of our synapses to control the direction of our ideas. That control is made possible by the fact that our neurons fire in only one direction, from dendrite to synapse. So when our c synapse creates a connection between neuron A and neuron C, the connection is a one-way A → C route that establishes neuron A as a (past) cause and neuron C as a (future) effect. It's our brain thinking: "A causes C."

This physiological mechanism is the source of our human powers of causal reasoning. And it cannot be mimicked by the computer Arithmetic Logic Unit. That unit (as we saw above) is composed of syllogistic logic gates that run mathematical equations of the form of "A = C." And unlike the A → C connections of our synapses, the A = C connections of the Arithmetic Logic Unit are not one-way routes. They can be reversed without altering their meaning: "A = C" means exactly the same as "C = A," just as "2 + 2 = 4" means exactly the same as "4 = 2 + 2," or "Bob is that man over there" means exactly the same as "That man over there is Bob."

Such reversibility is incompatible with causal reasoning. A → C is not interchangeable with C → A any more than fire causes smoke is interchangeable with smoke causes fire. The first is an established rule of physics; the second, a wizard's recipe. And so it is that, as the Turing Award–winning computer scientist Judea Pearl has shown in The Book of Why, the closest that the A = C brains of computers can get to causal reasoning is "if-then" statements:

If Bob bought this toothpaste, then he will buy that toothbrush.

If this route has a traffic jam, then the other route will be faster.

If this chess move is played, then ninety-five percent of possible outcomes are victory.

If-then statements like these make up the bulk of Artificial Intelligence. And they do a good job of simulating casual reasoning. So good, in fact, that we humans tend to conflate the two in our ordinary speech. When we say, "if you're a smoker, then you're more likely to get lung cancer," we usually mean that smoking causes cancer. We're using "if-then" as a synonym for "cause-and-effect."

But cause-and-effect and if-then are not synonyms. Cause-and-effect encodes the why of causation, while if-then encodes the that-without-why of correlation. To take the example above, Bob buying toothpaste is correlated with him buying a toothbrush. But it doesn't cause him to buy a toothbrush. What causes Bob to buy a toothbrush is a third factor: wanting clean teeth."""

Clarifications:

1. As I understand it, the claim is more precisely about some literature (although in practice almost all), not all literature. E.g. conceivably some allegory could just encode a logical argument, but that can't count as a counterexample.

2. The claim is that AI cannot learn to increase its efficiency at generating text that humans recognize as coherent characters and plots insofar as this requires causal thinking irreducible to correlations - short enough or plagiarized texts might not require this but they don't count as counterexamples.

Resolution criteria: my judgement whether any argument presented in the comments demonstrates that the argument in the paper is unsound. I might resolve N/A if I decide I'm unable to adequately judge some proposed argument.

Feb 28, 5:45pm: Will someone refute Angus Fletcher's proof that computers cannot read (or write) literature? → Will someone refute Angus Fletcher's proof that computers cannot read (or write) literature by 2024?