Prediction Markets vs. Gambling: Where’s the Line? | Prof G Markets

Thanks for having me, Scott and Ed. I'm excited.

You know, one, it's just the exponential. You know, when the numbers are small, the exponential, you don't really feel it quite as much. And then as you compound and compound, all of a sudden, you know, everything basically happens all at once. And you tend to see that with a lot of consumer businesses that really hit the mainstream and they're growing at an exponential or exponential-looking pace. And I think that's definitely happening in prediction markets or at least in the case of Kalshi. The second thing where I think we're benefiting quite... I think that prediction markets are benefiting from an overall societal wave which is sort of this general distrust in traditional news sources or information sources and I think people are looking for an alternative and you know I think they found it. You know, a lot of people have found it in podcasts. I don't think a lot of people have found it in social media. I think people have... I mean, social media had this kind of idea of, you know, crowdsourced wisdom or crowdsourced truth. But social media incentivized clickbait in a way that, you know, people over time are not feeling like, you know, news feeds are basically like split into two. The world is basically completely disparaged. Everything is polarized and prediction markets are in some ways some sort of antidote where you get the crowd wisdom. You have a lot of people participating in prediction markets but you have skin in the game. You know, people are putting money where their mouth is and that leads to some of the answers they get out of prediction markets to be more accurate. And that's been definitely a big catalyst of the growth.

Any consumer company, and this is one of the things that we've learned and I'm learning in real time right now, most consumer companies that hit the mainstream, they go from like really exciting new technology and when they hit the mainstream there's this sort of flip where all of a sudden, you know, there's this sort of like let's just kind of air out all the risks, the dangers, all the ways that this could go wrong. You know, we've seen it played out with Uber, Airbnb had its fair share of it. We're seeing it play out with AI on many dimensions, many levels, and we're seeing it play out in prediction markets. And to some extent, I think that's a healthy thing. Like, I think society having a debate about new technologies and how to kind of deal with them is a good thing, right? If we all agreed on everything, you know, we probably are headed in the wrong direction. Look, my understanding is like there's one, you know, this question of like, you know, is this gambling, is this different, you know, are there kind of concerns about addiction and social isolation. Young man, I know you guys, Scott, you talk about this a lot. I think number two is there's the concerns of insider trading, like are... and to me I bucket it into kind of is the market fair, how do we police it, what is being done about that. But to me I don't think it's totally abnormal given, you know, the rate of growth and how fast it basically has gone mainstream.

You know, the vast majority of volume is really in the bucket of 25 to 45 years old and then we have a bucket in, you know, 60 plus, so retired, has sort of disposable income, time on their hand. And I think that like, you know, when I think about the typical customer, there's been recent reporting which I think was pretty interesting about this. You might have... I don't know if you've seen the New York Times article about the rise of the prediction market trader and they kind of gone through a number of, you know, and the most active traders, the people that basically, you know, drive a lot of the activity on the platform. You know, people that would kind of be considered like a super user or power user. Those are the people that like are spending quite a bit of time modeling. Like, you know, I'm passionate about the economy, I read the news a lot and like, you know, I'm going to basically be forecasting inflation on a daily basis. Or I like mentioned markets, you know, Joel, there was a whole profile on him on this New York Times piece and the guy like has built like, you know, pretty sophisticated models of like, you know, what words are going to be said and what appearances. And those are people that like, you know, have had an interest in something and then they figure out an outlet to basically like, you know, make money off of it or engage, you know, with a community that has kind of that shared similar interest. Like these are the most engaged in our Discord or we have this Kalshi Ideas platform which is basically Twitter but you can only speak if you have a position, so it's kind of a Twitter that's filtered for people that are position takers. But to me it's like, you know, I think the concern that you sort of outlined is a real concern, right? Like I think in my view any financial markets, and I think this concern applies to any financial market, I think it applies to, you know, day trading of options or these kind of idea of zero-day options that settle on any given day. Retail trading. I think it applies to crypto. Also the meme coins. And obviously it applies to traditional gambling and sports betting. And that risk exists in prediction markets. And I think the way that I think of it and as I build a company and as this company scales, there's certain things that are intrinsic to the model and then there's guardrails, like things that you add to the model around your business model to basically protect consumers from this sort of thing. So let's talk about the intrinsic piece. So I think prediction markets is a much healthier mechanism to engage with something than a lot of these other mechanisms. Like I think a lot of the problems that we've seen with dopamine hits and addiction and a lot of the issues that people generally pertain to as gambling have come from the gambling industry. And I think... and you ask why. Well, we got to look at the incentives in that industry. Like when you go to a casino or you go to, you know, traditional sports book, the revenue of that company is equal to the customer's losses. The way that that whole system, the business model is like, well if Ed comes to me, the business model is figuring out how much money can I take from Ed. That's how it works. So if that's your business model, what are you going to do, right? Well, what you're going to figure out is like, okay, I have Ed and Scott as customers. If Scott is a winner, I'm going to block Scott from participating because anything that Scott wins it's going to take from me as a business. And if Ed is a loser, I'm going to figure out how to create a habit, how to get Ed hooked in the platform and get them to come back pretty consistently. And that to me is a lot of where like kind of a lot of where it's a perverse incentive. And you know, show me the incentive, I can show you the outcome. Well, what the outcome is going to be is basically going to get people hooked and dopamine hits are going to basically be, you know, increasingly bigger part of the platform and so on and so forth. Prediction markets just don't have that inherent incentive. You know, I take a small fee and Ed is not trading against me, Ed is trading against Scott. It's inherently just more social. It's inherently more like... I think the model doesn't have the sort of embedded perverse incentive. And that enables me as a business model to just have much more versatility around solving that problem, around creating really good guardrails around that problem. Like, you know, when Ed comes, he's not basically facing an algorithm that's just sort of optimized to get Ed hooked. Ed is facing Scott, is facing you, and is figuring out whether Ed could be smarter than you, whether he could do research. How can he beat you? Intrinsically more social, intrinsically more competitive, intrinsically more interesting. In terms of the guardrail, we focus on this a lot and I think that like a lot of the guardrails are really what you want to prevent is excessive behaviors. I think anything taken to the extreme is bad. And you know, I talked about some of the trading, like retail trading, some of these examples, but you know, you see it in other places. You see it with drinking. You see it with online shopping. Like you probably have a... I mean, I'm the type of person like I have a bunch of [__] in my house like because I have these Instagram ads that keep feeding me all these like random trinkets that I keep sort of like clicking on and buying. And that's a form of excess. Like I somehow like find, you know, I do the thing and then five minutes later I'm like, why did I just buy that? Like why, you know, and I do this on Amazon. I do this on Instagram a lot. And all these things taken to excess tend to be bad. And so how do you, you know, you have to create measures around like, okay, how do you prevent excessive behaviors. You have to do a lot of customer education. We have tools around self-exclusions, limits, pauses. And then we also have surveillance where like when we do find someone especially on the younger side, you know, we do have age gating so you cannot participate as a minor obviously, but someone on the younger side, you know, repeatedly losing, repeatedly kind of taking aggressive actions, doing too much of their portfolio, we start showing warning signs like, hey, you should not put more than X% of your portfolio in one thing. Because you know, again, like long-term if you want to build a healthy ecosystem, you don't want these sort of behaviors to go off the rails. But then also our incentive is not misaligned with those guardrails. In some ways, it is aligned. We want people to be long-term participants in this model. We want them to be engaged socially. We don't win a lot if they come and lose a lot of their money very fast. That's actually a bad outcome for us.

I think there's a presumption in your question that's just assuming that all the trading is basically, you know, dopamine-type behavior, right? Which is not the case, right? Actually, like again, a majority of power users, the people that really contributing the most volume are the people that are making... these are actually necessary. Their trading is necessary to this because they're making the forecast more accurate, right? The stock market doesn't get efficient if nobody trades. You need the trading and you need the informed trading, you need the well-researched trading. And actually the trading that grows the most over time is the winners, is the people that like are essentially very well researched. They predict the weather because they're scraping satellite data. These are people that are building models. They're in the spreadsheets. They're doing math. They're building systems. These are people that are actually rejected from traditional, for example, like sports betting because they're making too much money. They get blocked and limited there, but they can come to prediction markets. It's a good home for that. So like yes you want the trading but you know the dopamine-level trading is not necessarily the thing that makes the forecast the most accurate, right? Like it's not, you know, it's part... you know, it's part... you need that vibrant ecosystem, you need speculators, you need, you know, forecasters, you need hedgers which we can talk about. But um, and then but you don't necessarily need the excessive behaviors. And the excessive behaviors are the things that you can cap over time to build a well-balanced ecosystem.

So we're seeing a lot of sports. Sports has grown astronomically last year. We don't have the Gatorade market. Again there's, you know, unregulated, regulated. So, but we don't have the war, terrorism, assassination markets either. You know, the insider trading is also not, you know, the Maduro trade and, you know, the capture, that's not regulated prediction markets or Kalshi. But look, I think there's sort of definitional... like okay, maybe like let me just kind of... let me just... let's just align on some definitions so we can have like a precise conversation, right? When someone is buying an option that expires end of day, retail participants buying it against Citadel and the open market on, you know, traditional, you know, the most boring names like NASDAQ or Chicago Board of whatever, do you consider that to be gambling or a form of gambling? I think it's something different from investing and so I would consider it... I would call it gambling. Yes. And that is why I'm very interested in the regulatory rules around options trading which are stricter than buying a stock for example. So long answer, short answer: yes.