Can AI master the art of humor? | Bob Mankoff

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[00:01:40] Das ist TED-Tec, ein Podcast von der TED-Audio-Kollektiv. Ich bin Ihre Hostin, Sherelle Dorsey. Bob explores die fascinating intersectionen von AI und Humor. Kann machines truly verstehen, let alone create, something as nuanced und subjective als ein funny cartoon? Und kann AI wirklich decipher die secrets of what makes uns laugh?

[00:02:03] Es ist ein hilarious und thought-provoking exploration of the human mind, the nature of humor, und die surprising possibilities of artificial intelligence. Before we dive in, a quick break to hear from our sponsors. And now, Bob Mankoff takes the TED stage.

[00:02:29] Whether you're thrilled by what AI can do for us or terrified but what AI is going to do to us, whether it can be funny is probably not top of mind for you. It is for me, I don't care if it turns all of us into paperclips, as long as they're funny paperclips. And the fact that it makes stuff up, hallucinates, for me that's not a bug, that's a feature.

[00:02:58] My entire career was making stuff up. They're called cartoons. There is no algorithm for humor, but now with the rapid pace of AI, I have to wonder, could there be a bot Mankoff? You might think my reflexive answer to this would be, how about never?

[00:03:23] But while I don't want to be replaced by a bot, I'm not above being helped by it. Steve Jobs famously said that computers are a bicycle for the mind. If that's the case, what's AI? A rocket ship? And at my age, you know what? I'd settle for a walker.

[00:03:48] The fears of machines replacing humans are not new. When the goals of machines and humans go horribly awry, at least for one of the parties. Cartoons don't happen in a cultural vacuum. They're part of the zeitgeist.

[00:04:10] The guy who invented cybernetics, Norbert Wiener, who said, thinking machines were putting us on the eve of destruction. Now, sadly and tragically, Norbert Wiener died, but not by a thinking machine, but by an unthinking one. He was run over by a bus. That's not true. I made that up.

[00:04:35] I hallucinated it because it's funny. So, these fears are not new, not novel. But now, in the immortal words of Nigel Tufnell of Spinal Tap, they go to 11. They're cranked to the max.

[00:04:59] And here is one of the maximum cranksters of all time, Elon Musk, saying, AI is one of the biggest threats to humanity, but certainly not as big as Elon Musk. People like Elon have a P-Doom number. That's the probability AI is going to wipe us out.

[00:05:29] I think P-Doom is P-Dumb. I'm interested in P-Funny, and I've been using the New Yorker caption contest to look into the probability of that. Every week since 2005, the New Yorker has presented a cartoon without a caption and challenged its readers to come up with the winning caption in the caption contest.

[00:05:57] And for that, they get the glory of being in the New Yorker magazine, a huge amount of money, a house in the Bahamas that Sam Bankman freed. Actually, it's just the glory. On the page of the New Yorker, there's a contest. You enter the finalists from a few weeks before, three finalists, and a winning caption. So, it's staggered in that way.

[00:06:25] Each one of these images are funny. They're in Congress. You certainly think they're humorous, but they're not funny in a way that you get. They're not mentally funny. To make it that, of course, you need the right caption. Okay, but with up to 10,000 captions every week, how do you select that?

[00:06:50] Now, from 2005 to early 16, that burden fell on me and my assistants, but mainly my assistants to try to cull the good captions from what we uncharitably call the craptions.

[00:07:08] But then, in early 2016, for the benefit of all humanity, but mainly for me and my assistants, we switched to crowdsourcing. So now, for every contest, you vote online, and a funniness score from over a million judgments

[00:07:35] is given for all the captions. Now, overall, I'm against mob rule, but actually, in this case, the mob does a pretty good job. Usually, the finalists, almost certainly, almost all the time, really, the finalists come from the top 200 captions. Well, this is popular not only with the New Yorker, but it's caught the eye of data scientists,

[00:08:02] creativity searchers, cognitive scientists, and AI, of course, and everything adjacent to AI. I wasn't really surprised when Vincent Van Hook, then the chief data scientist for Google's DeepMind, now the head of robotics, sent me this email indicating that winning the caption contest,

[00:08:27] which was actually somewhat of the sine qua non of human creativity and intelligence. And I was also flattered by that, of course, but I didn't think they had any chance at all of doing it. And it turned out that was the case. All of the AI juju circa 2016 wasn't up to the task. It really couldn't even decode the image.

[00:08:55] So for the sine qua non of the human mind, DeepMind was non-compostmentous and out of its depth. But time and AI marched on. AI marching quadruple time. Vincent gets back to me and says, while human creativity might still be out of reach, we think we have understanding well in hand.

[00:09:20] He sends me this ridiculous uber nerd example of explaining humor. And I said, you know what? Let me give you a cartoon I did in 1997 at this other watershed moment when IBM's DeepMind defeated Garry Kasparov, the world's chess champion. And here's the cartoon I did then. And it says, no, I don't want to play chess. I just want you to read the lasagna.

[00:09:50] I rate this explanation a solid B minus. But so what if it was an A? Is there ever going to be a beautiful New Yorker cartoon anthology of explanations? I don't think so. But the idea that understanding humor could be a stepping stone to creating it sort of made sense.

[00:10:20] This paper I was involved in tried to look at compared to smart humans, what were the best AIs do on three tasks? Could they, from winning captions from different contests, match to the right image? Could they, between two captions, one that won and the one that was pretty good, pick the right one? And could they explain the humor? Now, for all of them, you know what? Yay, humans, we're still ahead.

[00:10:49] But AI is closing the gap. The most interesting thing about this paper for me was it showed a pathway for which you could create cartoon humor. And that was how we trained the contest. For 653 contests, the AI was trained fine-tuned on these examples which humans annotated.

[00:11:17] A description of the cartoon, explanation of the humor. Okay, if you've used ChatGPT, you sort of get the idea now. Put a number of examples like this. Put it in the prompt window. Rinse and repeat. Repeat. And you get new cartoons. Well, Jack Hessel, the chief author of the paper, did something more sophisticated.

[00:11:43] And what he did was create 50 synthetic new cartoons generated from this old data in which there were five options for captions. I picked four of them, and I gave them to cartoonist Shannon Wheeler to draw up. Now, Shannon said, well, these are weird. They don't really seem like... It's sort of an uncanny valley of cartoons. They're not quite there. But it is interesting.

[00:12:11] All of these are new cartoons that never appeared anywhere that are an idea of computer creativity. But I do see this now as a tool for brainstorming for cartoonists in that we played this completely straight. Shannon wasn't able to manipulate the description of the picture or the caption. Had he done that, it could have been better.

[00:12:38] Also, we could have asked it to make more. We could have put in the rankings for the humor. We could do all this to improve it. So, quality comes out of quantity. You can get an awful lot of quantity here. You can have a human being in the loop to do this.

[00:12:58] But I would not go so far to give AI a true human sense of humor. A human sense of humor is not about making a joke or getting it. It's rooted in our vulnerability. It's the blessing we get for the curse of mortality.

[00:13:26] Mark Twain said, the true source of humor is not joy but sorrow. If we gave AI the thousand natural shocks that flesh is heir to, that would be cruel. If we did that, it might very well want to wipe us out.

[00:13:51] And if they did, all I ask is that they take Elon first. Thank you. That was Bob Mankoff at TEDx U of M. And that's it for today. TED Tech is part of the TED Audio Collective.

[00:14:22] This episode was produced by Nina Bird-Lawrence, edited by Alejandra Salazar, and fact check by Julia Dickerson. Special thanks to Maria Latias, Farrah DeGrange, Daniela Belareso, and Roxanne Hilash. I'm Sherelle Dorsey. Thanks for listening.

[00:14:53] ServiceNow. ServiceNow unterstützt Ihre Business Transformation mit der KI-Plattform. Alle reden über KI, aber die KI ist nur so leistungsfähig wie die Plattform, auf der sie aufbaut. Lassen Sie die KI arbeiten, für alle. Beseitigen Sie Reibung und Frustration Ihrer Mitarbeiter und nutzen Sie das volle Potenzial Ihrer Entwickler. Mit intelligenten Tools für Ihren Service, um Kunden zu begeistern. All das auf einer einzigen Plattform. Deshalb funktioniert die Welt mit ServiceNow. Mehr auf servicenow.de slash AI for People.

[00:15:23] Was ist das Geheimnis für glücklichere, produktivere Teams? Ein Arbeitsplatz, der mentale Gesundheit an erste Stelle setzt. Bei OpenUp bieten wir deiner Organisation einfachen Zugang zu PsychologInnen, Gruppensitzungen und On-Demand-Ressourcen, die alle darauf ausgerichtet sind, Stress zu reduzieren, Resilienz aufzubauen und die Mitarbeitermotivation zu steigern. Bereit, die Veränderung zu sehen?

[00:15:48] Besuche noch heute openup.de slash Unternehmen und mache den ersten Schritt zu einem erfolgreichen Team.