Ethan Malik (2:28)

I think you're probably more than a couple months ahead of a lot of people. What I liked about the book, reading through it, is it was a great exploration of the space and kind of a foundation, but also in a lot of ways a very practical user guide for getting up to speed very quickly and kind of going from, all right, I don't know anything to beginner to intermediate. And I think that it's really useful for, for people in that sense, knowing how quickly the AI landscape has changed.

Dylan Lewis (2:54)

What was the process like for writing.

Ethan Malik (2:56)

The book and was it an accelerated timeline?

Professor Ethan Malik (2:59)

So I wrote the book and edited it through the end of December. I wrote it knowing GPT5 is coming and it's not yet, but will be and all these other tools are coming my way. I did write it pretty quickly. This is my third book, but I couldn't have written it without AI. Actually, there's almost no AI writing in the book. It's not AI writing. Like it's know there's little AI segments, but they're clearly marked. The interesting thing is AI did all the other stuff that made writing books horrible for me on my behalf. So like if I got stuck on a paragraph, right, sometimes you work on a sentence for a long time. I'm like, give me 30 versions of this sentence I use as inspiration. There's a lot of work showing that AI works well as a marketer and as a Persona to market too. So I asked it to read my book in various Personas, to give me feedback on what I was doing and, you know, and advice. And I asked it to summarize research papers that I turned into part of the paper. Like, so it was very, very helpful in accelerating this process. It's sort of what AI does, the co intelligence idea, it's an accelerator.

Ethan Malik (3:52)

I think that that tees up nicely for some of the rules of using AI that you talk about in the book.

Dylan Lewis (3:58)

And I want to run through them.

Ethan Malik (3:59)

Because I think there are probably some listeners out there that are avid users of ChatGPT and probably some other folks who maybe aren't as familiar or have never interacted with an LLM before. So how do you structure how people should be using AI?

Professor Ethan Malik (4:13)

I recommend four rules to get started with. And the first rule is invite AI to everything you do that basically nobody knows how AI is most useful for your field. Like, nobody does. Like, I think people are waiting for instructions. I talk to OpenAI all the time. I talk to Microsoft, I talk to Google. There is no Instruction manual. Nobody has like a book of like that they haven't shown you yet. There's no consultant who knows anything. Nobody knows anything. So the way to figure out what this does is just to use it a lot and see what it does and strongly recommend just trying to use it for everything you legally and ethically can. Then the second piece of advice is that you should learn to be the human in the loop. So the AI is really good at a lot of things. We could talk about the studies and results on this, but like, it's really good at innovation, it's really good at analysis. It out invents most people. You want to think about what you're actually really good at, because whatever you're best at, you're definitely better than the AI. And I think that there's going to be a real benefit to thinking about what you want to do and what you want to delegate. The third principle in the book is one where I say, you know, you should treat the AI like a person. And this is kind of considered a sin in the world of AI. You're not supposed to anthropomorphize it, but the fact is it's trained on human language and human interactions. So it works best when you work with, like, a human. In fact, one of the mistakes people make is they assume that software developers are the people who should be using AI, but it's actually not. It's really managers, writers, journalists, teachers often do a much better job using AI because they could take the perspective of it as a person, even though it isn't. That helps you do great work. And the fourth is this is the worst AI you're ever going to use. And we are in the early days of this kind of revolution.

Ethan Malik (5:42)

So I know you really have your students focus on using AI, believe it's a requirement of your classes. What do those rules that you laid out there look like in practice for them, using it as part of the classroom experience.

Professor Ethan Malik (5:56)

I initially went viral a while ago for my AI rules for the class, right? And right after ChatGPT came out where I required use and made people accountable for the outcomes. None of that works anymore. That was great for GPT 3.5, the free version of ChatGPT. GPT 4 writes better than most of my students. I teach at Ivy League school. My students are amazing, but it writes better than most of them at homework assignments. It makes less errors than an average student. So how do you deal with the fact that that's the case? You can't just say, use it and you're responsible for the outcome is because I can't find the errors as easily anymore. So instead of adapting how we use AI in the class, AI helps me co teach classes, it helps me provide assignments. One of my assignments a couple of weeks ago was that people had to replace themselves at their own jobs. So you're going for a job interview, you have to use the AI to do your job for you and hand a GPT that does this to your employer and say I'm ready for a raise now. And I had students that were everywhere from navy pilots to financial analysts to hip hop promoters and they all found ways of automating their jobs. Three of them got jobs that week by the way, as a result of this.

Ethan Malik (6:56)

So it was a successful trial?

Professor Ethan Malik (6:58)

I think so, yes.

Ethan Malik (6:59)

It's interesting to hear you say that. And I think where most people have lived with AI usage, certainly for me as someone who works in content is it is a kind of copilot for brainstorming. It is something that can be very helpful to kind of get the ball rolling as a creative process. I know with education you've really focused on the way that it can help simulate experiences for people and the way that you're able to kind of mimic real world situations that people might be in.

Professor Ethan Malik (7:26)

Yeah, I mean that's one of many uses, right? So building simulators, I've been building simulators for a decade. They're very expensive and hard to build. I built realistic sims where you, we built fake Gmail, fake Chat, fake Dropbox, fake Zoom, and you literally run a fake startup in real time for the over the course of six weeks. And those took a big team of people, a lot of money, a lot of resources. I could get almost the same effect from two paragraphs. Not quite as good, but pretty good. So simulation is one of the areas that AI is really good at. Another one is that it's very effective as a tutor under various certain circumstances. Actually the default way of using as a tutor doesn't work very well, which is asking the AI to explain something like you're 10. That's great for getting explanation, but we don't remember that a real tutor asks you questions, that interrogates you and we can make the AI do that. It works really well as a, you know, there's a whole bunch of assignments we have around this for integrating knowledge for help with test you. So there's a lot of uses.

Ethan Malik (8:19)

You mentioned the asking it to be a tutor and kind of that leads us into some of the ideas around prompting and the way to set AI up well, to give you what you're looking for and maybe what's most helpful for you. For some folks who maybe haven't spent as much time prompting, what would be some of your tips for interacting with an LLM?

Professor Ethan Malik (8:36)

The mental model you want to have for LLM is that it knows a lot of things about the world. You know, it has a huge web of connections, but it's going to kind of give you the average median answer all the time. Your job as a prompter is to knock it away from that average answer to something more interesting. And you do that by providing it with context. That gives it a different place to start from than just its default. So easiest way to give it context is a Persona. You are blank. You're a very good marketer. You are a marketer for consumer products. Like, that's an easy way to provide context. And then there's more advanced ways of doing that too, by asking it to think step by step, by providing examples. But your goal is to provide additional context and information.

Ethan Malik (9:12)

It's similar in a lot of ways to the way that people use Google. I mean, early on with search, the.

Dylan Lewis (9:18)

More specific you could be, the tools.

Ethan Malik (9:20)

Of using things like quotations to have specific text rather than just kind of a general query helped you get closer to what you were looking for. Over time, search engine results have gotten better and better because they've learned more and more about what we're looking for when we provide specific queries. Does that feel like a good parallel for how people should be thinking about prompting and interacting with AI?

Professor Ethan Malik (9:42)

Well, Google sort of headed the way that AI did. I mean, you can't do all the things you used to do with Google. They removed a lot of their specialized controls that used to make you good at Googling. It used to be called Google Fu, you were good at Googling. Right now you can be good at prompting. I actually don't think it's really that important in the long term because I think the AI already knows your intent. Like, if you want to write a novel, ask the AI, help me write a novel and you'll get a surprisingly large part of the way there from just that.

Ethan Malik (10:06)

So I know we saw a lot of companies putting out these prompting roles that they were hiring for prompt engineers. Do you think that that's a short lived career?

Professor Ethan Malik (10:15)

So I think prompt engineering will be useful if you're building prompts for other people. But I think for most of us using these systems, these systems are getting smart enough. And I don't know a single person who's an insider at one of these organizations who doesn't think that the AI will itself be able to be self prompting. Most of the people I Talk to at OpenAI or Google or Anthropic don't think Prompt Engineer is a long time thing to learn for most people.

Ethan Malik (10:38)

So does that just become a skill that most people are generally bringing into their work rather than it being a specialized trade that we're hiring out?

Professor Ethan Malik (10:45)

No, I just think that the AI is smart enough to be the product. We already know that the AI can already figure out intent better than most of us can. And so you'll just say what you want and you're not going to need to prompt it because it'll know.

Ethan Malik (10:56)

As you've been bringing students in, I imagine some folks have some familiarity with AI, others maybe don't. Have you gotten pushback on bringing it into the classroom?

Professor Ethan Malik (11:06)

I think people expect a lot more pushback in the world than there is. I think there's a lot of theoretical pushback, but people want to learn how to use these systems. So there's a lot to discuss about ethics and privacy and other sets of concerns. But I think people also want to figure out how to make these things useful. They're here. There isn't really a choice anymore. Occasionally, like a, I have like a Google DeepMind person in one of my talks, they'll raise their hand and say, what do you think about the ethics of releasing AI? And I always say to them, look, you made the decision to release large language models. This is not a conversation we get to have anymore. You made this choice and we should know what their limitations are, what their ethical compromises are. But like it's out there in the world so we better figure out how to use it.

Dylan Lewis (11:40)

Listeners, More from Professor Ethan Malik on how individuals and companies are using AI after the break. We'll be back in a minute. You're listening to Motley Fool Money. Welcome back to Motley Fool Money. I'm Dylan Lewis and this is our annual best of interview show for 2024. We are Zooming in on the most zeitgeisty of zeitgeisty things this week, Artificial intelligence. Earlier this year I caught up with Ethan Malik. He is a Wharton professor and author of the AI Handbook Co Intelligence Living and Working with AI. And what I loved about our conversation is that it brought AI down to the everyday person and the implications of things like AI at work and how companies might use it well and also misread its Impact, let's dive in.

Ethan Malik (12:26)

I want to dig into AI at work in particular. Studies in the book that you mentioned show I think it's like 95% of job categories have some overlap with AI, including professor. You know it yourself, you're right up there at the top of jobs. With AI crossover, how do you personally feel and think about that shaping your work?

Professor Ethan Malik (12:44)

The thing to think about with jobs is jobs are not just jobs. Jobs are bundles of tasks. We do many things right? So you know, you do podcast interviews. I'm sure you do five other things. Plus you have to fill out an expense report. You have to email me about this, have a pre conversation, do research, all this kind of stuff. Some of those tasks you probably really enjoy and you're really good at some of those tests you're probably mediocre with, but just got bundled into your job. So the first place you want to start with AI is thinking about what parts of my job bundle do I want to hand off to the AI. It's sort of like accountants used to spend almost all of their time doing math by hand, and then spreadsheets came along and now accountants don't do that anymore. There's still room for accountants. Their job is shifted and moved up market. If you're conscious about how you build it, you can shift to move up market as well.

Ethan Malik (13:26)

So AI is putting you in a spot where you can maybe focus on more of the things that you'd like to be focused on and doing some of the less rote things that you. You aren't as interested in.

Professor Ethan Malik (13:34)

Right? I mean, so expense reports are something I'd be happy to hand over to AI. I would love to hand over grading, but I don't do it because ethically I don't feel comfortable doing that. But like, there's a lot of tasks that the AI can do that are things I don't want to do. When we survey people who use AI, we get the same two answers, which is they are both, you know, a little nervous about the future and also really happy because the AI is taking the worst parts of their job.

Ethan Malik (13:55)

You talk about research showing that AI can really help close performance gaps when it's provided to people. What does that look like? And what is some of the research.

Professor Ethan Malik (14:04)

Showing in that there's a universal result from all cases where AI does work with you, which it improves performance of the lowest performers more than the highest performers. Now, there are a couple of caveats to that's really important. One of those is that sort of naive AI use That everyone goes through initially. We don't know in the long term whether the top performers also get a 10 times boost. So it starts off as a leveler, an elevator for the lower, but it may not work that way in the long term. Little bits of evidence around that. There's a really cool controlled study in Kenya that found small business owners who got access to the AI. If you are a top small business owner, you got a 20% profit improvement by getting AI advice, not help, but actual advice, while the lowest performers weren't able to implement the advice of the AI. So I think it depends on circumstances, but we're definitely seeing that leveling, upskilling effect almost everywhere.

Ethan Malik (14:52)

Are you seeing that in the classroom?

Professor Ethan Malik (14:54)

Yes, of course. There's no bad writers anymore.

Ethan Malik (14:56)

Knowing that everyone's writing gets better, how do you start looking for top performers and weaker students?

Professor Ethan Malik (15:04)

Welcome to everyone's giant problem. I mean there's easier, classes are easier, right? Like we have short term disruption, but like we could test like we've got lots of options. But if you think about middle management in most companies, what most managers produce is words, right? They do a whole bunch of tasks, but they produce as words. So they write reports, they write documents, they do presentations. And the number of words they write is an indicator of effort. Big document, lots more effort. The quality of the words they produce is their intelligence or ability. The lack of errors is their conscientiousness. All that just broke. I can produce infinite number of words that are all high quality, seem good enough at scale. What does that mean for organizations?

Dylan Lewis (15:39)

I think one of my favorite sections.

Ethan Malik (15:40)

In the book is you talk about this notion of the button and it existing in basically any productivity software application or something people would use for slacking, emailing people. This button that kind of auto magically drafts responses for you and it's, it's a very visible, very clear extension of the technology. And I think one that's easy for people to wrap their heads around. But when we start drafting a lot of things out with AI and then maybe tinkering a little bit, what do you think that does to the value of communication and work?

Dylan Lewis (16:11)

How do you wrap your head around that?

Professor Ethan Malik (16:13)

That's the problem. I mean we're about to just break how all of working communication operates, right? I mean, you're kind of an idiot to not use AI for stuff. The clearest example to me is as a professor, I'm supposed to write letters of recommend for people. And the whole point of a letter of recommendation is not the letter, it's the fact that I'm setting my time on fire as a signal to people that I care about this student, right? So they send me the resume, the job they're applying for, and I spend a good 45 minutes working on a letter for them. But if I just give the AI the resume, the job they're applying for, and a thumbs up or thumbs down, say I'm Ethan Mollock, I will get a much better letter in 35 seconds. Especially if I go round or two with the AI, maybe two minutes. Do I send the ethical letter that's less likely to get them the job, or do I send them the unethical letter that's more likely to get them the job?

Ethan Malik (16:57)

Maybe you split the difference.

Dylan Lewis (16:59)

I don't know.

Professor Ethan Malik (16:59)

I mean, it's an open question, right? Although I did just have a student send me the prompt they want me to use to write their letter.

Ethan Malik (17:06)

Wow.

Professor Ethan Malik (17:07)

So this is a first.

Dylan Lewis (17:10)

I want to extend that line of.

Ethan Malik (17:11)

Thinking a little bit. The Motley fool is a business of intellectual property. That's what we do. We provide premium stock newsletters, we provide model portfolios. We have coverage. We have this very podcast as well as a lot of articles. As you see people that are in content making investments in AI, what are some of the things you start to wonder about when it comes to information, when it comes to the way we consume things?

Professor Ethan Malik (17:37)

So right now, AI is at the 80th percent of many kinds of human performance. There's no way you're working within Motley fool that you're not in the top 1% or 0.1% of ability level in whatever you're doing, because you wouldn't be there otherwise. So to me, the biggest danger is organizations, especially content organization, thinking that this is fungible and replaceable. I think the idea that this is going to do automated content, and that's the value, is not really the point. Right. The point is how do I get my writers, you know, and my IP creators to do the stuff that uses their 0.1% ability, their. Their high end ability, and that it lets the AI help with the other stuff that means you're not doing that kind of interesting high end task. You can get the AI to write reasonably good portfolio articles, I'm sure, and with a little bit of tuning, it would do a reasonably good job. But, like, you're not into a reasonably good job. That's not why people are signing up for your organization. So I think that there's a danger of a race to the bottom of like not realizing the main advantages. And this is true with every company. The most dangerous thing you can do is view AI as a productivity tool for cost cutting. So the idea is like, okay, it increases performance by three times. That's great. I can fire two thirds of my staff in a moment where we're actually going through transformation and change. That's a really dangerous viewpoint.

Dylan Lewis (18:51)

That's a wrap on my conversation with Ethan Malik, but we've got plenty more AI wisdom ahead from the CEO of one of the market's hottest stocks of 2024. Stay right here. You're listening to Motley Fool Money.

Ricky (19:07)

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Dylan Lewis (20:08)

Welcome back to the the Motley Fool Money Radio Show. I'm Dylan Lewis and this is our Year End Holiday special where we bring forward some of our favorite conversations from the past year. Earlier in the show we focused on how individuals can interact with artificial intelligence and how the technology is shaping the workplace. Now we're going to turn our gaze over to how companies are using the technology in tangible ways to make their products better for end users. If you spend a lot of time online, you probably know Reddit as the front page of the Internet. If you don't, maybe you know the online community company as one of the best performing IPOs of 2024. Shares have tripled since the business came public this past March, and its growing user base and monetization efforts are a.

Ethan Malik (20:54)

Big part of the reason why.

Dylan Lewis (20:56)

Back in September, Reddit CEO Steve Huffman walked me through how a 20 year old business continues to find new users and how the company is harnessing AI to localize content and reach new markets internationally.

Ethan Malik (21:09)

It's a treat to Talk to you Because I'm a longtime user of Reddit. I first started using Reddit in college, and that was I don't want to date myself too much. That was over 10 years ago. And when I started using it, it was kind of a mix. It was for the memes, but also I was kind of learning how to dress myself. And so I was going to our male fashion advice and trying to pick up some tips there. I was going to school in Boston, and so I was trying to figure out what was going on in the city and what I needed to know about events, and so I was going to our Boston. I'm guessing that some of our listeners of the show are also longtime Reddit users like me. There are probably also some folks who are part of the 300 million plus folks who come to you weekly. For folks that do not know Reddit very well, how do you describe it to them?

Steve Huffman (21:53)

Oh, starting with the hard questions. Okay, look, first, thanks for being a user for so long. Sounds like, yeah, you've been on this journey with us a little bit over the last while. So kind of depending on, like, what, what I sense their context is. I explain Reddit in a couple of ways. If I was explaining it from the ground up, I'd say Reddit is. Reddit is communities. And so those communities can be about anything and everything. Every interest, passion, hobby, whatever you're into, whatever you're going through, it's on Reddit somewhere. And then what I would say is, look, if you're pretty much between the age of like 17 and 70, you know, whether you're a nerd or normie, man or woman, you have a home on Reddit, there's something there for literally everybody. Other times I explain it in contrast to social media, and social media is powered by algorithms, Reddit's powered by people. So every piece of content that becomes popular on Reddit is made popular by people voting and voting in the context of a community. And so, you know, up or down. And so users can make things popular, but they can also disappear things. And so kind of by definition, polarizing content doesn't do as well on Reddit. And so what you get as a result is Reddit is the most human place on the Internet because it's powered by people. And if you look at the conversations on Reddit, everybody has comments. But if you look at the comments on Reddit, if you look at the object of the sentences, you'll see that they're talking to each other about whatever it is, as opposed to social Media, where they're often talking at, but past the poster, they're either super effusive or maybe the opposite. But there's kind of a lack of connection there. On Reddit, it's people organizing around things. They love talking about those things like real human beings.

Ethan Malik (23:43)

Where do you guys think you are in the grand scheme of Reddit's potential? I guess you can take that in the platform direction, you can take that in the business direction, wherever you want to go with that.

Steve Huffman (23:53)

It's such an interesting idea to contemplate because on one hand, Reddit has been bigger than I ever thought it would be since August 2005. And look, by some measure, we're big now, right? We have about 90 million people visit Reddit every day. 360 million people visit Reddit every week. So that's big in terms of absolute numbers. But social media, you know, the biggest platforms there have a billion, two billion users every day. So there is a, I think, huge opportunity there. Reddit, we're about 50, 50 us versus non us. You know, I'd say other. Other major platforms are more like 80 to 90% non us. So I think a lot of opportunity to grow more users. And then on the business side, I think we've gotten out of the beginning phase. We're in the ads business. That's our primary business model, though. We license data and we do some other stuff as well. We're primarily ads. It's growing. It grew last quarter. We reported 50% growth, a little more 50% growth. So that's great. Our ads are working, our customers are happy. We're continuing to deepen relationships there. But I still think. And so on one hand, we IPO'd in March. And so on one hand, it feels like, okay, we've gotten to a certain level of stability and scale where this feels real and it's working. On the other hand, it almost feels like we're at the very beginning. I have a lot of the same feelings today as I did almost 20 years ago, which is, gosh, we've barely scratched the surface of this thing, and it can be so special and I think really, really great on the platform side and the business side. And so I'm really of two minds about it. But the Jeff Bezos idea of day one is really something I feel like we're living right now. It feels like the beginning.

Ethan Malik (25:45)

I do want to dig into some of the company numbers a little bit and talk through some of that. I was impressed as a longtime follower of the business to see the growth that you guys put up in 2024, because platforms have been around for a very long time. The revenue growth of 50%, to me, not crazy surprising for where you guys are at in the monetization story. The user growth story of 50% was a surprise. What was behind that growth?

Steve Huffman (26:14)

There's a couple specific things which I'll get to, but the big picture idea is this goes back to what I said when I was describing Reddit. Everybody's got a home on Reddit. Okay, so then that raises the question, if everybody has a home on Reddit, and you know, Steve, if you say the content's so great and it's so unique and it's such a great experience, then why isn't everybody on Reddit already? And so I think there's two possible answers for that. Well, actually, three, the first, they haven't heard of Red. Well, certainly in the US that's increasingly less likely. Okay, so number two, they tried Reddit and it didn't work for them. That's the group we've really been focused on making it. So the new users who are coming to our front page or opening the app for the first time, that is, they're primed to, like, experience Reddit as opposed to coming from search or something like that, make sure they find a community that speaks to them. And so we made signup much, much easier. The community onboarding, like helping you find your home on Reddit, much more effective. We made both the website and the app much faster. We just redesigned it in a lot of little ways so it's easier on the eyes, There are fewer bugs, and our home feed has gotten much better at making recommendations of communities that you might like. And so really getting people into their home on Reddit and then finding all of their interests much more effectively. And so that's been working very well. And then at the same time, we made our website substantially faster, two to five times faster. We launched this in May of 2023. Googlebot likes speed. And so faster pages rank higher, and faster pages also get indexed faster. And so, like the Google, search works in mysterious ways. As close a partner as we are with Google, we have no idea how search works.

Ethan Malik (28:12)

Nobody does, Right?

Steve Huffman (28:13)

Right. Nobody does. But speed matters. And so when our website got a lot faster, we started ranking higher. And then combine that with the product improvements, users are having better experience on Reddit. And so now it creates this flywheel that we're really benefiting from as we see a lot of new and core users coming from search. And then we're much more effective at kind of getting them into their home on Reddit. And so I said there was two things, right. So either you haven't heard of Reddit or it didn't work for you. Those are that number two we're really focused on. There's a third one, which is you don't speak English. And so that's kind of the next frontier of Reddit. Reddit's corpus today is still mostly English, but growing outside of the United States, outside of English. That's a part of the next chapter of Reddit. Unlocking that.

Ethan Malik (28:57)

What does tackling that look like? What are some of the challenges and things that you guys are working through to make Reddit localized to some of the other big international markets?

Steve Huffman (29:07)

Sure. So all the things I just mentioned around, speed, performance, all that, all that matters. So that's the foundation. There's other parts of the foundation, like safety is a big part of it as well. So the foundation helps everybody. But on top of the foundation, there's a chicken and egg problem. You need content to attract users and you need users to create content. And so we kind of come at this from two ways. One is just program work. So we target a market and then we, you know, there are users in every market. We're not starting from zero anywhere. So we go to the communities there, we reach out to the mods, we figure out, like, what communities probably should exist that don't like cities, sports teams, you know, local passions, things like that. And we work with mods to kind of try to bring those communities to life, make sure they're in discovery, make sure everything's kind of humming there. The second thing we're doing, which is working very well, or at least off to a great start, is machine translation. So new technology here, with large language models, we can actually translate the existing Reddit corpus into other languages at human quality. Now, not all the. Not all the content is relevant, but a lot of it is. So we have been testing this in France, in French in the first half this year, and it's gone very, very well. And so now we're adding on more languages. We're doing German, Portuguese, and Spanish. And so that will get us just a bigger content foundation. And then from there, we need to see the next step, which is kind of organic growth, or call it kind of native organic growth on top of that. So international is it's real work. One of the differences between Reddit and social media is Reddit's communities. People don't just join communities overnight, let alone create them and we can't force it. So what we try to do is really create the conditions for growth, but we can't actually force anything. So we're getting a little bit better at that. But that is, there's a lot of, I think, finesse required to get that right.

Dylan Lewis (31:15)

Say, sibo the party name. Folks, we've got more from Reddit CEO Steve Huffman ahead, including how the company is fueling LLM efforts by licensing its corpus of data to companies like OpenAI, and also how artificial intelligence is improving the site and leading to a better, safer Internet. That's next here on Motley Fool Money. As always, people on the program may have interest in the stocks they talk about, and the Motley fool may have formal recommendations for or against. So don't buy us on anything based solely on what you hear. All personal finance content follows Motley fool editorial standards is not approved by advertisers. Motley fool only picks products it'd personally recommend to friends like you. This is the Motley Fool Money Radio show. I am your host Dylan Lewis and today we are tackling the topic of 2024 artificial intelligence from all angles. How people can put it to use, how companies are thinking about it. And on that note, that is where we will pick up my conversation with Reddit CEO C. Steve Huffman, diving into how the company is looking at AI to open up some revenue opportunities in Data licensing with AI leaders like OpenAI and also some of the ways they are using the tech to improve the.

Ethan Malik (32:44)

Site and user experience outside of the ad business. I know it's a small piece of the pie for you guys right now, but you do have a data licensing business. I think it was about 28 million in the recent quarter. That is, as I understand it, allowing other companies to use platform data for for LLM training for AI applications. What was the decision there and what are you guys seeing there?

Steve Huffman (33:08)

Yeah, so Reddit is one of the largest corpuses of human conversation on the Internet, for better or for worse, but I think overwhelmingly for better. Reddit has been an open platform. Reddit's content was used for training these AIs. Now our terms of service are like Reddit's open. You can use Reddit's content for non commercial use, but for commercial use you need a license. And so I want Reddit to stay open. I also want to be practical. Like Red's content is useful for these things. And look, these AIs, these large language models, they help our business. I think they advance the, you know, humanity. It's one of the most important technologies, you know, of the last generation, help us make Reddit safer, help make the whole Internet safer. And so we like these technologies existing and we're proud that Reddit's content can be used to create these technologies or advance them. But I think just as a matter of, like, business practicality, commercial use of Reddit's content. Reddit's public content requires a commercial agreement. And so that's what we've been working on. We still do non commercial agreements. So we'll give Reddit Countdown away to researchers or other nonprofits like Internet Archive. Now there's terms on all of these things. And so we created a public content policy. We released this earlier this year. So every platform more or less has a privacy policy. And that basically says this is what we do with your private information. So we have one of those two. Now we don't have a whole lot of private information, but what we do have, we don't share. It doesn't leave Reddit. The public content policies basically says, this is the content that you put on Reddit in a public community. It's on the public Internet. You should know that if you don't want it on the public Internet or in search indexes or showing up in research potentially, or potentially being used for training, don't put it on Reddit. So we want the terms of engagement to be clear there. And then we said, look, if you have any agreement you have to use this content, you have to have agreement with us and to use it. You can't do certain things like reverse engineer the identity of our users or use it to target ads against users, things like that. And so I think under those terms and under those policies, we've been able to strike a few deals that I think are important. So Google and OpenAI are the biggest ones on the training side. And then we've done others like with cision and Sprinklr, kind of on the social listening, like what are people saying about these brands? That sort of thing. So, yeah, it's a new business for us. It's off to a good start, but I'd say we're still kind of in early days in what is quite frankly a developing market.

Ethan Malik (35:50)

I'm curious how AI fits into the picture for Reddit itself and the product, the app, the site experience that users interact with.

Steve Huffman (35:59)

Oh, I mean, it's very exciting. So there's so much hype around large language models, but one thing that is undeniable is they are very, very good at jobs involving Text and words. And Reddit has a lot of text and words. So I think some things I'm most excited about, we've been playing around with this idea of post guidance. So if you're a new user, you've grown up on social media, you've come to Reddit and you're submitting your first post, but you've never submitted to Reddit before. So maybe you don't understand that this is a community space and this community has very specific rules. What used to happen is you'd submit this post and then a moderator would be like, oh, this violates a rule in the science community, no joking allowed, for example, and then you get banned. That's not a good user experience. Now we can use things like LLMs to detect like, hey, this is a joke. And you can tell the user, they click submit and say, hey, too funny. Funny is not allowed here. We know you mean well, but try again. Much, much better experience. The user can adapt their post to something that should be a better fit for the community. The community gets a new user. Reddit gets a happy customer or happy user. So I think that sort of thing is really, really powerful, obviously for safety things like harassment and bullying or whatever idiosyncratic rules subreddits have. Like, I was just giving you another example. LLMs can help detect. I think that's really powerful. I was a moderator for a little bit last year. We have a program called Adopt an Admin where our employees kind of guest moderate subreddits. And so I did it with am I the ass? So, you know, it's a large community on Reddit.

Ethan Malik (37:42)

Can they have you explain the community.

Steve Huffman (37:44)

You submit a post as a, as a user? I don't know. I wore, you know, a cream colored dress to my, you know, sister's wedding and everybody got mad at me, like, am I the to pick a real example for my life? And then the community debates and gives you feedback. Yes, you're the. No, you're not. And so it's a really interesting community of people basically kind of debating these social situations. But they have a rule. You can't use the word Karen and you can't use the word man child. Now I've been thinking about rules on the Internet for a long time. I don't like word rules. Like you can't say this word because I think they're too brittle, right? Because there's always this context. And indeed on that subreddit, we'd spend a lot of time adjudicating uses of the word Karen? Like, were they saying it meanly or are they correcting somebody else? Or is this the story literally about a person named Karen? And so it's just like so much time spent on that rule now they eventually convince me it's an important rule because it sets a tone for the conversation and a tone for that community. So I came around to their viewpoints, like, this is important and it's had a good effect on this community. But I'm looking forward to when an LLM can do that work so that the human moderators can do something else, because some of the rules are really complex. I think LLMs will make Reddit safer, honestly, for that matter, they'll make the whole Internet safer. I think that's very exciting, listeners.

Dylan Lewis (39:15)

That's a wrap on our annual Best of Interview show, but it's not a wrap on 2024 for Motley Fool Money. Next week, Asit Sharma and Ryan Gross will be on with me to preview what's ahead for investors in the new year and the corners of the market they are paying attention to in particular. We'll be back with that next week and if you don't want to wait, check out our daily show wherever you listen to your podcasts. Special shout out to Rick Engahl for all his magic behind the glass this week. I'm Dylan Lewis.

Ethan Malik (39:41)

Thank you for listening. We will see you next time.