AI RABBIT HOLES | THURSDAY, OCTOBER 22, 2026

Featuring Professor Parallax, White Rabbit, and Hatta

Professor Parallax had arranged three chairs, two microphones, a blackboard, and a small brass bell.

White Rabbit stood beside a stopwatch.

Hatta sat backward in his chair, wearing a hat that appeared to contain a smaller hat.

"Today's experiment," announced the Professor, "concerns one of the most mysterious capabilities of the human mind."

"Finding one's spectacles?" suggested White Rabbit.

"Understanding humor."

"Much more difficult," said the Rabbit.

Hatta raised his hand.

"Professor, before we begin, I have a question."

"Proceed."

"If a machine tells a joke and nobody laughs, is it still artificial intelligence?"

"It is still artificial intelligence, yes."

"And if everybody laughs?"

"Also artificial intelligence."

"And if the machine laughs at its own joke?"

Parallax considered.

"That requires a more careful distinction."

Hatta leaned forward.

"Good. Because I've brought a machine that laughs at absolutely everything."

He placed a small mechanical box on the table.

Parallax pressed its button.

HA! HA! HA! HA!

White Rabbit nearly dropped his stopwatch.

"What does it find amusing?" asked the Professor.

"Nothing," said Hatta. "It has excellent manners."

And with that, the experiment began.

Human beings have been trying to explain humor for centuries.

Philosophers, psychologists, linguists, comedians, and neuroscientists have proposed different explanations.

One influential approach is called incongruity theory.

The basic idea is that humor often arises when something violates our expectations.

A story establishes a familiar pattern.

We anticipate what should happen next.

Then something unexpected occurs.

And if the surprise makes a certain kind of sense, we may laugh.

Consider:

A man walks into a library.

He asks the librarian for a cheeseburger.

The librarian whispers, "Sir, this is a library."

The man whispers back, "Sorry. One cheeseburger, please."

The joke depends upon several things.

We recognize that libraries are quiet places.

We recognize that cheeseburgers do not normally belong in library transactions.

And we understand that the man mistakes the librarian's correction as an instruction to lower his voice.

The ending changes our interpretation of what came before.

That mental rearrangement is central to many theories of humor.

But incongruity alone does not guarantee laughter.

If something unexpected happens in a frightening situation, we may feel alarm rather than amusement.

If a punchline is incomprehensible, we may simply feel confused.

Humor requires more than surprise.

It frequently requires context, interpretation, and a sense of what the surprise means.

A joke is not merely an unexpected sentence. It is an unexpected sentence that finds a place in the listener's imagination.

Modern artificial intelligence systems can recognize many common forms of humor.

They can identify puns.

Explain wordplay.

Recognize exaggeration.

Generate absurd comparisons.

And analyze the reversal of expectations in a comedic scene.

Large language models learn statistical and conceptual relationships among words, expressions, stories, and patterns of communication.

Through training, they acquire powerful capabilities for modeling how language is used.

This includes humorous language.

For example, an AI system may recognize that a sentence is funny because a word has two meanings.

Or because the final line contradicts an assumption established earlier.

Or because the speaker says something dramatically inappropriate for the situation.

In a 2025 study published in Cognitive Science, researchers found that several language models performed above chance on tasks involving recognition and comprehension of one-line jokes.

But the tested models remained below human performance.

The research suggests that language-based learning can support meaningful humor-related abilities, while leaving important differences between machine and human interpretation.

That distinction matters.

Recognizing the structure of a joke is not necessarily the same thing as experiencing amusement.

White Rabbit looked up from his notes.

"Professor, are you suggesting the machine understands jokes?"

"I'm suggesting we must define what we mean by understands."

Hatta nodded.

"Excellent. That should delay the lecture by at least forty minutes."

Here comes the surprising part.

Yes. Artificial intelligence can produce material that people genuinely find funny.

A 2024 study published in PLOS ONE compared jokes generated by ChatGPT with jokes written by human participants.

The researchers asked people to evaluate humorous responses without knowing whether they came from a human or AI.

In several of the tested conditions, the AI-generated responses received higher average humor ratings than those produced by the nonprofessional human participants.

The researchers also compared AI-generated satirical headlines with professionally written material.

The results challenged the assumption that computer-generated humor must necessarily be inferior.

But we should not exaggerate what the study demonstrated.

It did not prove that AI possesses a human sense of humor.

It did not establish that AI outperforms every professional comedian.

And it did not settle questions about originality, consciousness, emotional experience, or the cultural context of comedy.

It demonstrated something narrower and important:

Some AI-generated jokes can be judged funny by human audiences, even when those audiences do not know a machine wrote them.

Professor Parallax smiled.

"Quite an interesting result."

"Indeed," said White Rabbit.

Hatta produced a sheet of paper.

"I've prepared seven hundred jokes."

"Seven hundred?"

"One for every possible reaction."

"That's not how comedy works," said the Professor.

"Exactly. The system is still in development."

There is an old observation about comedy.

The more thoroughly you explain a joke, the less funny it tends to become.

Humor often depends upon the speed with which an unexpected connection occurs.

The listener follows the setup.

A familiar interpretation forms.

Then the punchline arrives.

For a brief moment, the mind reorganizes the situation.

And laughter may follow.

But if someone stops the performance to explain every detail, the experience changes.

The audience no longer discovers the connection.

It receives a report about the connection.

This is especially interesting in AI research.

A language model may correctly explain why a joke works while producing a terribly flat joke of its own.

Or it may generate a funny line without having a reliable theory of why people find it amusing.

Recognizing humor, generating humor, and evaluating humor are related but distinct abilities.

A 2025 survey of computational humor research noted that these tasks remain challenging, especially beyond relatively familiar forms such as puns.

A system can be good at identifying the ingredients of comedy without being consistently good at preparing the meal.

Hatta stood.

"I should like to demonstrate."

"No," said Professor Parallax.

"I haven't begun."

"Exactly."

Imagine two comedians delivering exactly the same words.

One waits half a second before the punchline.

The other rushes into it.

One watches the audience carefully.

The other ignores the reaction.

One allows silence to build anticipation.

The other fills every pause with nervous chatter.

The words may be identical.

But the performances can produce very different results.

Comedy is not only language. It is timing, rhythm, delivery, context, and audience response.

Human comedians use a remarkable range of signals.

Facial expression.

Body movement.

Voice inflection.

Silence.

Changes in tempo.

Eye contact.

Shared memories.

And a sensitivity to the emotional atmosphere of a room.

A comedian may abandon a prepared joke because the audience is not receptive.

Another may seize upon an unexpected sound or interruption and transform it into the funniest moment of the performance.

Improvisational comedians are especially skilled at this kind of spontaneous adaptation.

Modern AI systems can generate speech with expressive inflection, produce comedic video sequences, and respond conversationally to user input.

But coordinating language, physical performance, audience expectations, cultural knowledge, and spontaneous adaptation remains a demanding problem.

And even perfect simulation of a laugh would not settle whether a machine experiences amusement.

White Rabbit rang the brass bell.

"Timing test!"

Parallax raised an eyebrow.

"Why did you ring the bell?"

"Because the experiment has reached precisely the correct moment."

"For what?"

Hatta fell off his chair.

The Rabbit examined his stopwatch.

"Actually, that was three seconds early."

Consider a performer such as Robin Williams.

His performances could move rapidly among voices, accents, characters, cultural references, and startling observations.

He could build upon a suggestion.

Imitate a character.

Interrupt himself with another character.

Return to an earlier joke.

Then suddenly discover an emotional truth beneath the comedy.

The genius was not merely in the number of words delivered.

It was in the creative relationship among surprise, personality, timing, and meaning.

Jonathan Winters, one of Williams's important inspirations, possessed an extraordinary gift for spontaneous character creation.

Ernie Kovacs explored the very possibilities of television as a medium for visual comedy.

Sid Caesar developed elaborate comic situations built upon language, physical performance, and ensemble timing.

Their approaches differed.

But each exploited possibilities beyond the words of a joke.

A joke can be written on paper. A comic performance comes alive through what happens between the performer and the audience.

And there is another dimension.

Humor can be intimately personal.

A joke shared between old friends may be hilarious because of a memory that nobody else knows.

A harmless remark may bring laughter to one person while leaving another entirely unmoved.

Culture matters.

Language matters.

Timing matters.

Relationships matter.

That is why humor is a particularly revealing challenge for artificial intelligence.

We should also recognize that not every joke is harmless.

Humor can bring people together.

It can ease tension.

Reveal hypocrisy.

Challenge powerful institutions.

And help people cope with difficult experiences.

But jokes can also humiliate, stereotype, deceive, or exploit vulnerability.

Sometimes the same remark is interpreted very differently by different audiences.

AI systems face a difficult problem here.

They must generate entertaining material while recognizing that social context matters.

A satirical joke criticizing a public institution is different from a joke intended to humiliate someone because of a personal characteristic.

Playful teasing among friends is different from harassment.

And a joke that works within one cultural setting may be misunderstood elsewhere.

This is not a problem with a simple mathematical solution.

It involves social judgment, uncertainty, and differing values.

The capacity to produce something funny should be accompanied by the ability to consider whom it might hurt.

Professor Parallax turned toward Hatta.

"Can you think of an example of humor requiring careful judgment?"

"Certainly," said Hatta.

He gestured toward the Rabbit.

"I had prepared seventeen jokes about punctuality."

White Rabbit narrowed his eyes.

"And?"

"I decided to save them for a more appropriate time."

"When would that be?"

"Yesterday."

Absolutely, in appropriate circumstances.

A conversational assistant that can recognize harmless humor may be easier to interact with.

A learning system that uses amusing examples may help students remain engaged.

A creative writing assistant may help a storyteller explore comic dialogue.

And people developing games, animated films, music videos, theatrical performances, and other creative works can use AI to experiment with comedic possibilities.

Consider a writer trying to develop three contrasting characters.

One is meticulous.

One is philosophical.

One is completely unpredictable.

Their different personalities create opportunities for humor.

An AI assistant can help brainstorm situations in which those personalities collide.

It can suggest dialogue.

Identify repetitive jokes.

Explore alternative punchlines.

And help refine pacing.

But the creator still needs to judge what suits the characters, the story, and its audience.

A joke that is funny in isolation may be entirely wrong for a particular scene.

Comedy is not always improved by adding more jokes.

Sometimes the funniest thing a character can do is remain silent while everyone else behaves absurdly.

AI can be a useful comedy-writing partner without replacing the creative judgment of the person telling the story.

Professor Parallax returned to the blackboard.

"We shall now conduct a final experiment."

He drew three columns.

RECOGNITION. GENERATION. EXPERIENCE.

White Rabbit studied the headings.

"Three different questions?"

"Precisely."

The Professor pointed to the first.

"Can a machine recognize that something is humorous?"

"Often, yes," said White Rabbit.

"The second. Can it generate material people find funny?"

"Again, yes, sometimes."

"The third. Does it experience amusement as a person does?"

The Rabbit hesitated.

"We don't know."

"Correct. Current evidence does not establish that today's AI systems have subjective experiences of amusement."

Hatta raised his hand.

"Professor, may I suggest a fourth category?"

"What would that be?"

"SURVIVAL."

"Survival?"

"Yes. Can the audience survive seven hundred consecutive jokes?"

Parallax closed his notebook.

"The experiment is concluded."

"Wonderful," said Hatta. "Then I shall begin the encore."

It depends upon what we mean by the phrase.

If we mean recognizing humorous patterns, modern AI can often do that.

If we mean creating jokes that human beings find amusing, the answer is also yes.

If we mean adapting humor reliably to every situation, person, cultural setting, and emotional context, present systems still have important limitations.

And if we mean personally experiencing amusement, the question remains unresolved.

That distinction is important.

We should avoid dismissing real computational accomplishments merely because they differ from human creativity.

But we should also avoid treating successful performance as automatic evidence of humanlike inner experience.

The challenge is to understand what these systems can actually do.

Where they perform well.

Where they fail.

And how they can become useful partners in human creativity.

Humor may be one of the most demanding tests because it combines language, expectation, social intelligence, emotional interpretation, and invention.

But perhaps that is also why it is such a fascinating field of research.

After all, a machine that can help us think creatively may be useful.

A machine that can also help us laugh?

That could make the creative journey considerably more enjoyable.

The classroom had grown quiet.

Professor Parallax extinguished the lamp.

White Rabbit carefully packed his stopwatch.

Hatta remained seated, regarding the small laughing machine.

"Professor?"

"Yes, Hatta?"

"Did we decide whether the machine understands humor?"

"We established that several different kinds of understanding must be distinguished."

"Splendid."

"And that subjective amusement remains an open question."

"Excellent."

"And that a joke must be appropriate to its audience."

"Wonderful."

Hatta picked up the mechanical box.

"Then I have solved the entire problem."

"How?"

"I've invented a machine that only laughs when I'm funny."

Parallax looked interested.

"Does it work?"

"Perfectly."

"May I hear it?"

"Certainly."

Hatta pressed the button.

Nothing happened.

A full ten seconds passed.

White Rabbit looked at Professor Parallax.

Professor Parallax looked at White Rabbit.

Hatta sighed.

"Still needs a software update."

And somewhere in the back of the classroom, someone began to laugh.

It wasn't the machine.

What is the difference between recognizing a joke, making someone laugh, and actually finding something funny?

If an AI system produces a joke that genuinely makes you laugh, does it matter whether the machine understands the joke in the same way you do?

Or is there something essential about human humor that goes beyond the words?

Tell us what you think.

And if you have a favorite example of an AI-generated joke that worked brilliantly, or failed spectacularly, we'd love to hear it.

Just don't send all seven hundred at once.

Hatta is still recovering.

1. Stanford Encyclopedia of Philosophy, “Philosophy of Humor.”
A scholarly introduction to theories of humor, including incongruity, superiority, and relief.
https://plato.stanford.edu/entries/humor/

2. Gorenz, D., & Schwarz, N. (2024). “How funny is ChatGPT? A comparison of human- and A.I.-produced jokes.” PLOS ONE.
Research comparing audience evaluations of human- and AI-generated humor.
https://doi.org/10.1371/journal.pone.0305364

3. Trott, S., Taylor, S. M., and colleagues (2025). “Turing Jest: Distributional Semantics and One-Line Jokes.” Cognitive Science.
Experimental research investigating language models' ability to identify and comprehend jokes.
https://doi.org/10.1111/cogs.70066

4. Loakman, T., Thorne, W., & Lin, C. (2025). “Who's Laughing Now? An Overview of Computational Humour Generation and Explanation.” Proceedings of INLG 2025.
A survey of the accomplishments, challenges, and limitations of computational humor.
https://aclanthology.org/2025.inlg-main.45/

5. Attardo, S. (2020). The Linguistics of Humor: An Introduction. Oxford University Press.
A linguistic examination of humor, including incongruity and resolution.
https://doi.org/10.1093/oso/9780198791270.001.0001

AI RABBIT HOLES | EXPEDITION #147

Where the questions multiply, curiosity leads the way, and even the punchlines deserve a little investigation.

#AIRabbitHoles #ArtificialIntelligence #AIHumor #Comedy #ComputationalHumor #Creativity #Psychology #RobinWilliams #JonathanWinters #ProfessorParallax #WhiteRabbit #Hatta #Wondermage

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