Why machine-generated humor is the holy grail of AI

In “The Outrageous Okona”, the fourth episode of the second season of Star Trek: The Next Generation, the resident Android Data of the enterprise is trying to learn the one skill she has not been able to master before: humor. While visiting the ship’s holodeck, Data takes lessons from a holographic comedian to try to understand the business of making fun.

While the worlds of Star Trek and the real world can sometimes be far apart, this act applies to the machine intelligence here on earth. Simply put, getting an AI to understand humor and then generate its own jokes is extremely difficult.

How hard Forget Go, Jeopardy !, chess and loads of other impressive demos: according to some experts, building artificial intelligence at the level of a top comedian can be the true measure of machine intelligence.

And although we haven’t reached our goal yet, it’s safe to say that we might get a lot closer.

Witscript cracks the code

Joe Toplyn is someone who is not afraid of challenges. Toplyn, a trained engineer (with a huge career gap in terms of actual exercise), made a successful career as a television writer. A four-time Emmy winner, he was head writer for the likes of David Letterman and Jay Leno. A few years ago, Toplyn became interested in the question of whether there was an algorithm (i.e. a process or set of rules to follow) that would help write really funny jokes.

“People think it’s magic,” he said of Digital Trends. “I think some comedy writers or comedians try to portray their work as magic. Well, it’s like magic in the sense that a magic trick is constructed and designed, and there is a way it works that will fool you that the magician has supernatural powers. But that really has a logic. “

This belief in steel logic in joke-telling – sharpened while Toplyn tried to teach aspiring comedians his “magic” – eventually led him to seek an AI capable of generating spontaneous jokes that Regular conversations fit into the game. With the name Witscript, the results add up to an innovative AI system that generates improvised jokes. A chatbot using Witscript for ad-lib jokes could, Toplyn says, help create personable artificial companions to solve the “huge problem” of human loneliness. Think of it like PARO, the robot seal with punchlines.

“It’s contextual,” Toplyn said of Witscript, which was recently unveiled at the 12th International Conference on Computer Creativity (ICCC 2021). “This distinguishes it from other joke-generating systems that generate self-contained jokes that cannot simply be integrated into a conversation. When talking to a funny friend, chances are their jokes will be incorporated into a conversation in response to something you said. It is much less likely that your friend will just start telling a joke of their own like, ‘A man walks into a bar with a duck on his head …’ “

The funny formula

This spontaneous quality comes from the joke-writing algorithms that Toplyn developed in-house.

“Basically, the basic algorithm for writing jokes works like this: It starts with choosing a topic for the joke, which can be a sentence someone says to you or the subject of a news story,” he said. “The next step is to pick what I call the two ‘topic handles,’ the words or phrases in the topic that are most responsible for grabbing the audience’s attention. The third step is to generate associations between the two topic handles. Associations are what the audience is likely to think about when thinking about a particular topic. The fourth step is to create a punch line that connects an association of one of the two topic handles with an association of the other in a surprising way. The final step is to create an angle between the subject and the punch line: a sentence or phrase that connects the subject to the punch line in a natural-sounding way. “

Francesco Prandoni / Redferns via Getty Images

If all of these holds and angles sound like hard work, the evidence – ultimately – lies in the pudding. With 13 input themes, Witscript generated a series of jokes that Toplyn then contrasted with his own efforts. For an evaluation panel, he outsourced the evaluation to Amazon Mechanical Turk workers, who rated each freshly minted joke on a scale from one (no joke) to four (a very good joke). One of Witscript’s best efforts received a rating of 2.87 (“That’s pretty close to a joke,” Toplyn said) to his own 2.80 as a student Beat Master. The witscript joke? On a line about the 25th anniversary of the performance art company Blue Man Group it quipped: “Welcome to the Bluebilee”.

Though he may not be quite ready to oust Dave Chappelle just yet, Toplyn believes Witscript proves that humor can be automated to some extent. Even if there is still a long way to go. “As machines do these algorithms better, the jokes they generate get better,” he said.

However, he also urged caution. “To generate [truly] elaborate jokes like an experienced human comedy writer, machines need the common sense knowledge and the sensible thinking skills of a typical person. “

A pioneer in AI comedy

It turns out that this can be the crux of the matter. Humor may seem frivolous, but for those who work in language, comedy, and artificial intelligence, this is anything but.

“We use humor in many different ways,” Kim Binsted, professor at the University of Hawaii Institute of Information and Computer Science, told Digital Trends. “We use it to build social relationships. We use it to define in-groups and out-groups. We use it to come up with ideas that we may not seriously want to express. Of course there is non-linguistic humor, however [linguistic humor] falls into a category of usage that is really powerful. It’s not just a stand-up on stage that it uses to get a few laughs. It’s something we use all the time [within our society.]”

“It’s a huge sign of advanced intelligence because to be really funny an AI has to understand a lot about the world.”

When it comes to computer humor, Binsted is a pioneer. In the 1990s, she developed one of the (possibly) first AI designed to generate jokes. Developed with Professor Graeme Ritchie, Binsted’s JAPE (Joke Analysis and Production Engine) was a joke-making bot that could create question-and-answer puns. An example could be: “Q) What do you call a strange market?” “A) A bizarre bazaar.”

“It was great because it allowed me to pick all the low-hanging fruit before anyone else,” she said humbly. “What I did with puns.”

An AI-complete problem

Since then, Binsted has developed various other computer humor bots – including one that can come up with variations on “Yo Mama” jokes. While Binsted’s work has since evolved to examine long-term exploration of human space, she still views joke-telling AI as something of a holy grail for machine intelligence.

“It’s not in one of those things like chess where people at the beginning of AI said, ‘Well, if a computer can ever really play chess, we’ll know it’s perfectly intelligent,'” she said. “That is obviously not the case. But I think humor is one of those things that flowing humor with a computer has to be really intelligent in other ways too. “

Microphone in a bar7713 Photography

This is why telling jokes is such an interesting challenge for machines. It’s not because cracking AI is just as useful for humanity as using machine intelligence to fight cancer, for example. But it’s a tremendous sign of advanced intelligence, because to be really funny an AI has to understand a whole lot about the world.

“Humor depends on many different human abilities, such as world knowledge, linguistic abilities, reasoning, [and more]“Thomas Winters, a Computer Science Ph.D. Student researching artificial intelligence and computer humor said Digital Trends. “Even if a machine has access to this type of information and capabilities, it still has to recognize the difficulty of the joke for itself. For something to be funny, a joke must not be too easy or too difficult for a person. A machine that generates jokes should not use knowledge that is too vague or knowledge that is too obvious with predictable punchlines. For this reason, computer humor is usually viewed as an AI-complete problem. [It means] We need an AI that has functionally similar components to a human brain in order to solve computational humor, as it depends on all of these abilities of the human brain. “

Think of it like a Turing test with a laugh trail. Coming to a super intelligence near you. Hopefully.

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