Prediction Markets vs. Gambling: Where’s the Line? — ft. Tarek Mansour

Summary

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

Guest: Tarek Mansour, Co-founder & CEO of Kalshi
Hosts: Scott Galloway & Ed Elson
Date: February 27, 2026
Podcast Network: Vox Media

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Episode Overview

In this episode, Scott Galloway and Ed Elson delve into the meteoric rise of prediction markets, focusing on Kalshi—a regulated prediction market platform co-founded by Tarek Mansour. With Kalshi boasting explosive growth and mainstream attention, the hosts and Mansour deeply examine the blurred line between prediction markets and gambling. They explore the appeal, criticisms, regulatory considerations, and broader social implications of these markets, tackling topics like addiction, fairness, and potential for insider trading.

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Key Discussion Points & Insights

1. Unprecedented Growth of Kalshi & Prediction Markets

• Kalshi’s Performance: Revenue has surged by ~1,000% over the past year, with trading volume exploding from $280 million to $2.3 billion ([06:23]).

• Why Now? Tarek attributes growth to both compounding network effects and a societal “distrust in traditional news sources”—users seek the “crowd’s wisdom” with real skin in the game ([07:12]).

  “Prediction markets are in some ways an antidote… you get the crowd wisdom, but you have skin in the game.”
  — Tarek Mansour ([08:06])

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2. Are Prediction Markets Gambling—Or Something Else?

• Dueling Identities: Prediction markets serve two functions: as information/content platforms (to gauge consensus about future events) and as trading/gambling platforms ([08:38]).
• Major Criticisms: Mansour outlines the top concerns:
  • Addiction and unhealthy user behaviors, drawing parallels with gaming apps targeting dopamine responses in young men.
  • Insider trading—whether prediction markets can ever be truly “fair.”
  • The risk that rapid mainstream adoption brings greater scrutiny and regulatory debate ([10:05]-[11:20]).

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3. Audience Demographics & Incentive Structures

• User Profile: Most active participants are ages 25–45, with a sizable contingent 60+ ([12:07]).

• Super Users: Many core users are sophisticated, data-driven “power users” akin to day traders analyzing macroeconomic indicators or constructing elaborate models for niche markets.

• Incentives vs. Casinos: Unlike traditional gambling, where the platform profits when the user loses, Kalshi makes a transaction fee on trades—users trade against each other, not the house.

  “Prediction markets just don’t have the inherent incentives… I take a small fee and Ed is not trading against me. Ed is trading against Scott. It’s inherently more social, more competitive, more interesting.”
  — Tarek Mansour ([14:33])

• Addiction & Guardrails: Kalshi implements user education, spending limits, self-exclusion tools, and surveillance to detect problematic behavior, especially among younger users ([16:55]).

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4. Is Trading Itself Addictive or Problematic?

• Transaction Fees: Ed’s skepticism: Even if the platform doesn’t profit from losses, isn’t it incentivized to drive excessive trading—regardless of user outcome? ([17:45])

• Mansour’s Response: Not all trading is dopamine-driven; the high-volume, most engaged “winners” typically rely on research and analysis. The ecosystem needs informed trading to improve prediction accuracy ([18:33]).

  “The stock market doesn’t get efficient if nobody trades. You need trading and you need informed trading. … Exponential behaviors … you can cap over time to build a well-balanced ecosystem.”
  — Tarek Mansour ([19:33])

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5. Gambling vs. Speculation—Defining the Line

• Sports Markets: Contrary to reported figures, Kalshi does not host novelty markets like “Gatorade color at the Super Bowl.” Most markets have broader importance (like weather, elections, or macroeconomics), not sheer entertainment ([21:39], [26:41]).
• Definitions Debated:
  • Some states define gambling as “staking money on something you don’t control.” By that logic, most investing is gambling.
  • Kalshi’s standard: Does the event have societal/economic consequence, and is the market structured as a fair, open exchange? ([22:50]-[26:10])

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6. Why Prediction Markets Matter

• Societal Value: Well-structured prediction markets improve societal forecasting capacity for everything from Federal Reserve decisions and inflation to election outcomes and extreme weather risks ([26:41], [29:23]).
• Real-World Impact: Example—Kalshi creates markets on whether events in seminal AI policy papers will occur, giving more accurate and real-time forecasts than traditional Fed “dot plots” or expert surveys ([26:41], [29:23]).

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7. Insider Trading—Risks & Enforcement

• Nature of the Risk: Scott suggests that “organic” market effects could limit insider trading—no one bets where someone else has a clear informational edge ([30:23]).
• Ed counters: Robust regulation, as in stock markets, is needed because insiders will always exist ([30:34]).
• Mansour’s Position: Kalshi bans insider trading and follows standards similar to equities markets. The standard: trading on “material non-public information” is forbidden ([33:53]).
• Policing Insider Trading: Detection leverages transaction surveillance and parallels financial market oversight. For prediction markets, if a piece of information isn’t restricted (e.g., the color of Gatorade known by a halftime performer), and there’s no law or obligation of confidentiality, it’s fair game ([36:05]).

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8. Practical Applications Beyond Speculation

• Insurance Substitutes: Kalshi enables individuals (e.g., Florida homeowners) to “hedge” physical risks like hurricanes via prediction contracts—especially where traditional insurers have exited the market ([37:59]).
• Sports Bonuses: Teams hedge player bonus risk via liquid contract marketplaces, often at favorable prices ([37:59]).

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9. Regulation & Kalshi’s Position

• Rigorous Compliance: Kalshi is notable for having pursued regulation before launching, in contrast to “offshore” and unlicensed competitors ([44:49]).

• Embracing Oversight: Mansour argues that enduring, systemically important companies cannot thrive without regulatory legitimacy—especially in financial services ([44:49]).

  “I want to build an enduring company… you need a regulator overseeing every step where the money is going, reporting of transactions. Everything needs to be public.”
  — Tarek Mansour ([44:49])

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Notable Quotes & Memorable Moments

• On Prediction Markets as Social Good:
  “When social media is incentivizing clickbait, prediction markets are incentivizing truth.”
  — Tarek Mansour ([44:49])

• On the Difficulty of Drawing the Line:
  “Options trading… maybe 90% of the [stock] market is speculation… it’s me betting against you that the stock's going to go up or down… This isn’t much different—but at the same time, it does feel like it has more of a gambling feel to it. So I don’t have moral clarity around that.”
  — Scott Galloway ([47:43])

• Ed’s Challenge on Clarity:
  “There needs to be a lot of clarity on what are the definitions between these different things. Because what I can tell you is that betting on, say, the color of the Gatorade is flat out gambling. And there is no real benefit to society other than it's fun and it's a form of consumption.”
  — Ed Elson ([50:24])

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Timestamps for Key Segments

• [06:18] — Interview begins: Kalshi’s explosive growth explained
• [10:05] — Tarek lists primary criticisms/risks facing prediction markets
• [12:07] — Who uses prediction markets? The demographics and power users
• [14:33] — Poker vs. prediction markets: incentives, addiction, and social utility
• [17:45] — Are excessive trades incentivized? Ed and Tarek debate
• [22:50] — What is gambling? Regulatory/pragmatic definitions
• [26:41] — Why trivial bets like “Gatorade color” don’t fit Kalshi’s model
• [29:23] — How prediction markets outperform traditional forecasting
• [33:53] — Can you really police insider trading? Enforcement mechanisms discussed
• [37:59] — “Insurance” and corporate use-cases for prediction markets
• [44:49] — Embracing regulation: Kalshi’s approach and rationale
• [47:43] — Hosts’ closing thoughts: the blurry boundaries of gambling, speculation, and investing
• [50:24] — Calls for regulatory clarity and responsible risk disclosures

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Tone & Conversational Highlights

The exchanges are candid, with the hosts unafraid to push back on Mansour’s optimism. Scott leans into skepticism and big-picture philosophical questions, while Ed drills down with specific regulatory and behavioral concerns. Mansour’s tone is practical and deeply informed by his experience in both regulated finance and the startup world. Banter periodically cuts through, but the debate always returns to substance—regulation, incentives, and social utility.

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Summary Takeaways

• Prediction markets are growing rapidly, propelled by distrust in traditional information sources and the appeal of “crowd wisdom with skin in the game.”
• The distinction between gambling and speculation is murky—especially as the line blurs between “fun bets” and socially valuable forecasting.
• Kalshi positions itself as “the clean, well-lit corner” by embracing regulation, robust guardrails, and refusing to do “pure gambling” markets like Gatorade color.
• Behavioral risks and addiction remain real issues, but may be mitigated by tools, community norms, and market structure.
• Broader economic utility—prediction markets can supplement (or replace) clunky insurance products and sharpen forecasting across finance, economics, and even public policy.
• Regulation is both challenge and opportunity for Kalshi, setting it apart in an industry often tempted to “move fast and break things.”

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In short: A wide-ranging, thoughtful debate that peels back the layers of an increasingly important financial technology—with no easy answers, but real accountability and ambition for the space’s future.

Transcript

[Scott Galloway]

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[Ed]

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[Tarek Mansoor]

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[Ed]

I'm freaking out.

[Scott Galloway]

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[Ed]

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[Sponsor Announcer]

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[Tarek Mansoor]

No problem.

[Scott Galloway]

I'll be with you every step of the way.

[Ed]

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[Scott Galloway]

Visit lifelock.com podcast terms apply today's number 30. That's how many additional minutes Americans spend sleeping per day compared to two decades ago. True story, Ed. I find that when I have a bad sunburn, it helps me sleep to take Viagra. It does nothing for the pain, but the sheets no longer touch my legs.

[Ed]

Listen to me.

[Scott Galloway]

Markets are bigger than us.

[Ed]

What you have here is a structural change in the world distribution.

[Tarek Mansoor]

Cash is trash. Stocks look pretty attractive. Something's going to break. Forget about it.

[Scott Galloway]

How are you, Ed? How are you?

[Ed]

I'm doing very well. I'm here in London and I had drinks with you last night, which was awesome.

[Scott Galloway]

You know me, I like to get to know my staff. I like to spend quality time with them.

[Ed]

We did spend some quality time.

[Scott Galloway]

We did.

[Ed]

We got kicked out after about an hour. The other thing is we went to a bar that we were very excited about and I show up cause Scott showed up a little late. And I show up, and it turns out that it's comedy night.

[Scott Galloway]

Comedy night. And there's some Scotsmen on stage speaking a dead language that only twins speak to each other. And they closed the bar down. So I'm like, oh, this fucking sucks.

[Ed]

So we had to spend the first 20 minutes listening to this guy. I gotta tell you, he was absolutely bombing as well. It was not comfortable to sit through. But then we had a lovely drink.

[Scott Galloway]

I got to know your girlfriend where I just sat there and thought, what does she see in him? I don't get it. I don't get it. I don't get it. Ed, I don't think young people should get married. But my advice to you is three things. First, lock. Second, it. Third, down. Lock it down. I think the world of you. You are so out of your way class, my brother. You are so out of your way, class. Anyways, it's good to see you.

[Ed]

That's very. It was great to see you. She had a great time. I had a great time. It's good to be in London.

[Scott Galloway]

It's nice, right?

[Ed]

Yeah, it is very nice. It's too dark and it's a little late, but it's nice. Well, we have a big, important interview here with the CEO of Kalshi. Shall we start to move on to that?

[Scott Galloway]

Let's do it.

[Ed]

Okay. Actually, before we do that, I. Apologies. Let's not to also say.

[Scott Galloway]

Go ahead.

[Ed]

I forgot to also say that Prof. You Markets is returning to the Vox Media podcast stage at south by Southwest. We will be there on Saturday, March 14th. So if you want to see that, come join Scott and me at 10am on the 14th of March at the Hilton Austin for a live taping of Prof. G Markets live show. It's gonna be epic. Scott and I very excited, or at least I am. I think Scott's excited.

[Scott Galloway]

You had me till you said Hilton Austin. I don't. That's not what I aspire to. But you know what's gonna happen here? It's the same thing. We come in, we skirt the line, and a few people take a picture with me, and they're like, oh. They're like, oh, and by the way, I have a daughter. She's at ut. Is Ed single? Is Ed single? Everyone is asking about your romantic status when we go to these things.

[Ed]

That's not what happened last night. Where we're standing, someone comes up and goes, oh, my gosh, Scott Galloway. And he looks at me, he's like, I know, you too, but Scott Galloway, It's Great to see you.

[Scott Galloway]

A tall, handsome guy.

[Ed]

That's right.

[Scott Galloway]

He is a tall drink of lemonade. Like a nice, young handsome man. Yeah. Yes, I enjoyed that. I enjoyed meeting him.

[Ed]

Yeah, it was good. It was very good.

[Scott Galloway]

Yeah. But south by Southwest and you can learn more and get a special discount. I love how they're already discounting us. That makes me feel good. On your south by innovation [e-mail] SXSW that's voxmedia.com SXSW we'll see you there. I'm actually really excited. How many people from Prop GEO are we bringing to Austin, Ed?

[Ed]

Oh, we've got a huge crew. I think it's like 12 people maybe.

[Scott Galloway]

I heard 16. I wonder how much money that's going to cost me. Oh my gosh, I'm excited. Anyways, everybody, Ed and Scott are going to be at south by Southwest. Please say hi. We really do enjoy meeting our fans. And Ed, not so much. Ed's sort of standoffish and a little bit arrogant, thinks he's better than everybody else, but not me. Not me. Not me.

[Ed]

Say hi.

[Tarek Mansoor]

Hola.

[Ed]

Hola.

[Scott Galloway]

El pero el absorbo do self. Young person, young man. See it. South by Southwest.

[Ed]

No comment. Here's our conversation with Tarek Mansoor, co founder and CEO of Kalshi. Tarek, good to see you. Welcome back to the show.

[Tarek Mansoor]

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

[Ed]

So it's been a little over a year since I first interviewed you on first time founders. A lot has happened since then. Just looking at Kalshi as a company, your revenue has grown by about 1,000%. Your volume on this platform has gone from $280 million to $2.3 billion. You also recently raised a billion dollars at an $11 billion valuation. Basically, we knew Kalsi was going to explode, but it's exploded in a way that is kind of larger than life and getting a lot of attention. I'll just start with this. Why is Kalshi so popular right now? And why are prediction markets so popular?

[Tarek Mansoor]

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, everything basically happens all at once. And you tend to see that with sort of, with a lot of consumer businesses that really hit the mainstream and they're growing at a, I mean, 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 I think they found it. A lot of people have found in podcasts. I don't think a lot of people have found in social media. I think people have. I mean, social media had this kind

[Ed]

of

[Tarek Mansoor]

idea of crowdsourced wisdom or crowdsourced truth, but social media incentivize clickbait in a way that people over time are not feeling. Like news feeds are basically split into two. The word is basically completely dispersed. 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. People are putting money where their mouth is and that leads to some of the answers that get our prediction markets to be more accurate. And that's been definitely a big catalyst of the growth.

[Ed]

There are two things I want to separate in this conversation. One is prediction markets as a content platform, which I totally agree with you on. It's been massively helpful for us. I think a lot of people find it interesting because it just tells you a little bit more about the future. If you're trying to understand an issue, you will go to the prediction markets and you'll find the question and then you'll get to see, like, this is what the consensus view is. This is a probability of this event occurring or not occurring. That's content. It's also a trading platform, some would say a gambling platform, which is a different kind of thing. And it brings with it a lot of different issues. And I think as this platform has gotten so popular over, over the past year, it has also drawn a lot of criticism. And I think a lot that criticism is reasonable, valid, worth talking about. So I guess I'd love for us to dive into those criticisms. As, as the founder of this company, as the CEO, what would you. What would you say is the. The overall, let's say the. The three or four biggest criticisms of the company right now based on what you're seeing, based on how things are being reported, what would you say are the issues that people are worried about when it comes to prediction markets in Kalshi?

[Tarek Mansoor]

Any consumer company. And this 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 is this sort of like, let's just kind of air out all the risks, the dangers, all the ways that this could go wrong. I think we've seen it play out with Uber. Airbnb had its fair share of it. We're seeing it play out with AI on many dimensions in many levels, and we're seeing it play out in prediction markets. And to some extent, I think that's a healthy thing. 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, we probably are headed in the wrong direction. Look, my understanding is like, there's one, you know, this, this question of like, you know, is this gambling? Is this different? You know, are there kind of concerns about addiction and social isolation? Chung 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, is. And to me, I bucket 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, totally abnormal given the rate of growth and how fast this basically has gone mainstream.

[Scott Galloway]

Well, just to double click on that. So there's a real fear that a lot of big tech or a lot of technology companies, as they scale, tap into a less mature prefrontal cortex of men looking for dopa hits, and that essentially prediction markets are sort of the high IQ or graduate education version of gaming apps, and that it preys on a dopa hungry male and that there's enormous incentive for. Well, first, let me start there. Who is your typical. What's the demographic profile of your average customer and what is different from speculation or prediction markets from just flat out gambling sites?

[Tarek Mansoor]

You know, the vast majority of volume is really in the bucket of 25 to 45 years old. And then we have a bucket and you know, 60 plus so retired has sort of disposable income time on their hand. And I think that, like, when I think about the typical customer, there's been recent reporting, which I think was pretty interesting about this. 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. And the most active traders, the people that basically drive a lot of the activity on the platform, people that you would kind of consider it like a Super user or power user, Those are the people that are spending quite a bit of time modeling. I'm passionate about the economy. I read the news a lot and I'm going to basically be forecasting inflation on a daily basis or I like mention markets. Joel, there was a whole profile on him on this New York Times piece and the guy has built pretty sophisticated models. What words are going to be said and what, 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 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 idea platform which is basically Twitter. But you can only speak if you have a position. So it's kind of a Twitter that is filtered for people that are position takers. But to me it's like, I think the concern that you sort of outline is a real concern, right? Like I think in my view any financial markets, and I think this concern applies like this concern applies to any financial market. I think it applies to day trading of options or these kind of idea of zero DT 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 are 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 we, you know, people generally pertain to as gambling have come from the gambling industry. And I think. And you ask why? Well, you 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, that, that whole system, the business model is like, well, if AD comes to me, the business model is figuring out how much money can I take from ad. 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 AD 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 AD 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 you're 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 the inherent incentives. 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 this 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, 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, with online shopping. Like, you probably have a, I mean, I'm, I'm the type of person, like, I have a bunch of shit 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, and I think that's a form of excess. Like, I, I, I somehow like, find out, you know, I, I, I do the thing and then five minutes later I'm like, why did I just buy that? Like, I, what, why? You know, and, and I do this on Amazon doing This on Instagram a lot. And, and all of these things taken to the excess tend to be bad. And so how do you know you have to create measures on 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 percent 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.

[Ed]

The pushback to that point though, you make the point which I agree with. Show me the incentive, I'll show you the outcome. The pushback for a lot of people to that would be actually the incentive might not be that consumers need to lose or that traders need to lose money, but they need to trade. And if you can get them addicted, if you can get them to keep trading and get hooked, ultimately that actually is a boon for your business. So the guardrails you're describing, they are inherently counter to the incentives that are built into your business, which is we need people to trade as much as possible because that is our business model. We're taking a transaction fee on all the trades that happen. We don't want you to lose money, but we want you to put some money up. What would you say to that?

[Tarek Mansoor]

I think there's a presumption in your question that's just assuming that all the trading is basically dopamine type behavior, which is not the case actually. Again, a majority of power users, the people that are 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. 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 trade training 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 the dopamine level trading is not necessarily the thing that makes the forecast the most accurate. Right? Like it's part, you need that vibrant ecosystem. You need speculators, you need forecasters, you need hedgers, which we can talk about, 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.

[Ed]

We'll be right back after the break and if you're enjoying the show so far, send it to a friend and please follow us if you haven't already. We're back with Property Markets. I just want to go back to some of the criticisms. And by the way, the reason I'm interested in this is because this is what everyone is interested in when it comes to prediction markets right now. I was just on a PBS panel where this was the entire conversation. There was a focus on young men and young men's issues, this prevalence of addiction and this trend towards gambling. And this question of do prediction markets fit that, fit that description? And so what are we supposed to do about it? How are we supposed to feel about them? So one thing that I found interesting and I want to get your reaction to, I read somewhere that almost 90% of the volume that is happening on these prediction markets and I think on Kalshi is related to sports. So it's prediction markets trading. But if it's trading based on what color is the Gatorade going to be at the super bowl halftime show? That to me fits the bill of gambling. It to me is a kind of a different thing from the looking at satellite data and figuring out how will this affect weather patterns. So I guess my question is one, is that right? Are you seeing that amount of sports prediction markets trading? And two, does that not fit your definition of gambling?

[Tarek Mansoor]

So we're seeing a lot of sports. Sports has grown astronomically last year. We don't have the Gatorade market. Again, there's unregulated, regulated. But we don't have the war, terrorism, assassination markets either. The insider trading is also not the Maduro trade and the capture that's not regulated prediction markets or Kalshi. But look, I think there's sort of definitional. Okay, maybe let me just kind of. Let's just align on some definitions so we can have 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 traditional, the most boring names like NASDAQ or Chicago Board of Whatever. Do you consider that to be gambling or a form of gambling?

[Ed]

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.

[Tarek Mansoor]

So let's just establish a definition and then we can like, basically, you know, have a principal conversation here. So there's a few definitions we can basically take on, right? It's like one definition could be there's a threshold of research or understanding in a certain market that needs to happen for this to be a trade or not gambling. And obviously you'd see kind of the problems with that definition from a, from a, you know, delineation perspective, because how do you know who does research? And you get into nanny state questions and like now you have access, you know, open access problems, etc. One other one that I believe to be too broad is, is one that a lot of states in their state rules, rule books hold, which is like you're staking some money in the hope of making more money on something you don't control. That's one. You know, now you could see where that lands, right? You know, if you and I just leave this call and open Schwab and buy stock, even if we're investing in that stock, that's gambling, right? Like we just gambled. So, so what is the line like? I mean, how do we define that line? And you know, I'll tell you how we do it. But I, but it's actually kind of grounded with how historically the lanes and the regular, like the regulations have basically landed on this piece, which is one, is there a natural underlying instrument that, you know, where it's, it's helpful to price or forecast the thing because some people in society care about it, whether socially or economically or other. And you know, number two is the mechanics. And I think that's the most important thing when we talk about addiction, all the issues, the mechanics is this, you know, to me, gambling is the negative incentives, right? It's the incentive where I'm walking into a casino and that business is essentially like structured against me, like it's rigged against me. It's basically going to incentivize all the bad behaviors that we're talking about because that's how they make money. Whereas an open marketplace, like a marketplace where I'm a marketplace, I'm a neutral fair exchange where I provide the rules, I provide the guardrails, I provide the technology, I provide the structure. But then people are engaging with each other and they're figuring out the pricing. You could be a price taker ad or you could be a price maker and then you're figuring out how to beat others. That has historically fell under the definition of an exchange, a marketplace, whether it's stock market, commodity market, et cetera. And that same principle was drawn in 1905 at the Supreme Court for grain futures. And then they delineated, there's the bucket shop. So if you go and trade directly or bet directly against like a company on the grain, on grain futures, that's like bucket shop laws. It's going to go state by state. And if you do it in an open fair marketplace and the Chicago Board of Trade and now cme, that's considered like a federally regulated financial market. And then the same thing happened with the election market for Kalshi. And then, you know, what we're seeing kind of play out in sports also exists, by the way, in insurance. You know, you have state regulated insurance, which is like one insurance company is the one that gives you the price and you just take it how it is versus hedging, which is on cme. If you go and want to offload some risk and open fair marketplace where anyone can compete on the price, that's also like open and fair game. So that's kind of like where we, I think draw the line. And to me, all prediction markets very squarely fit under kind of number one.

[Ed]

And number two, I mentioned the Gatorade at the halftime show. What color is the Gatorade going to be, which is something that you can bet on on gambling apps. You say that's not something that we provide on Kalshi, which I didn't know that. I assumed that that was kind of fair game. That raises an interesting question of where does that fall on the line? Why does betting on the color of the Gatorade not work for you guys?

[Tarek Mansoor]

Well, I think it's kind of the pillar number one is, is this like a natural like thing, a risk or an occurrence that like, okay, trading on Brexit, like if you have a market on whether Brexit is going to happen or not, that has extrinsic consequences to a lot of people, government, businesses, people pricing that thing is relevant, people care, right. Like pricing whether this is a 20% chance or is a 60% chance, that's a very important thing that can go, that can be basically traced back to asset prices, that can be traced back to how we price the S and P, to how we price the footsie. That's a very important thing to have that has extrinsic consequences outside of the speculative activity that is going to happen on people trading on whether Brexit is going to happen or not. Right. The Gatorade is a harder kind of argument because the odds are, I think it's, I would assume it's 50, 50, right. Or, or some, or, or coin toss is the same like similar, similar sort of setup. So, so this is where like when you go back and if you all take a step back, you know, on kind of like this sort of what, what is the purpose and maybe we didn't talk enough about this so far, like about prediction markets, like why is it so important? Well, I, you know, I'll say like what they do is they apply a market based mechanism to questions. These key to a lot of questions about the future, some of which may be existential to humanity, some of which less existential. And you have to build a marketplace of diverse range of participants and diverse range of sort of opinions and all of that. But I think to me it's like what this does, and I don't know if you have seen there's a Fed paper last week that has kind of in some ways confirmed a lot of stuff that we've been saying over the last few years. And the Fed paper was saying basically calculate fills a lot of holes. One, it's more accurate than Fed funds for forecasting Fed decisions. It's more accurate than any other survey like the Boomer Economist survey for forecasting CPI or inflation prints. But it also gives us a full distribution of outcomes and it does it in real time. It gives us a much better understanding of basically the economy or a better understanding of the economy. And what excites me about what we're building is over time is if you get a very liquid marketplace about all these kind of different questions, you will basically just have a better light about our future which enables better decisions, better resource allocation and then better, also better asset pricing for all the kind of assets that we're currently pricing. So There's a paper from Kevin Hassett about this idea of as society gets increasingly more complex and you used to be agriculture based economy. So as long as you understand the agriculture, you understand where we're heading. Then we added industrials, then we got into a service based economy and now information economy. All these different. Now AI is happening as you add more and more complexity to society. It argues that we need infinite number of markets, in some ways need prediction markets to price all these different aspects and facets of society so that you can actually price the core asset prices like homes and S and P and the rates and the big sort of ticket items that we currently price. And maybe to make that example very concrete, like, you know, did you read the AI paper that some people are calling it doomerism? AI paper from what was it called? The Citrini. Citrini, yes. And what we're doing is we're launching a market this afternoon on like whether the Citrini outcome is going to happen. Because in the Citrini paper, like someone put out an opinion and it actually tanked a bunch of stocks. The market actually reacted to this. And I want to release that market to price that specific outcome, like price these, like the outcomes that people are talking about when it comes to AI and get a better understanding of AI. Because if you have these markets getting us better prices about these things, those will end up basically helping us price the bigger things like the S and P and the stocks. And those are things that basically excite me about what we're building.

[Scott Galloway]

When I think about potential for insider trading, which has gotten a lot of reporting, I think eventually that'll be starched out when people realize that you never want to bet against someone who has more information. So I see that probably going away organically.

[Ed]

Why would you say that this already happens? I mean, insider trading is rampant across many markets, including the stock market. The way we prevent it is through regulating it and making it stop. It doesn't organically stop itself.

[Scott Galloway]

If I'm betting on the speed of a baseball pitch and I realize I don't know, but someone in the audience may be giving hand signals to somebody or it comes out that this is highly susceptible to insider trading, I think fewer and fewer people are going to bet on those things that aren't that don't have access. My friend Todd Benson once said to one of my classes at cern, never bet on anything where there's, if you can, where you believe there's people who may have much greater information than you. I think a Lot of the most ripe for insider trading markets are just going to quite frankly die a slow death because people are going to realize they're maybe betting against people who. I don't understand why anyone would buy. Would anyone would bet on a. I figured what you call the markets where on someone saying something on a TV show that's already been pre recorded. Unless you are engaging in insider trading because it's fun, well then it's consumption, it's not gambling. And you better make sure you're having a lot of fun because it means someone with a lot more information is betting against you. You're on the wrong side of that trade anyways. Tarek, what would you say?

[Tarek Mansoor]

I mean look, there's a lot of consumption and I like that frame too. It's like the consumption bucket to think about a lot of these different things. And I think there's consumption on prerextion markets and a lot of traditional financial markets and that's not necessarily a bad thing. So I agree with Scott and I think the way I always think about this is let's think about why is insider trading bad in the first place? Some would argue, well, if you let insider trading happen in stock market, shouldn't that make it even more accurate? But the reason it's banned and actually in some ways we've tried this is that what happens is exactly what Scott mentioned is that like if you let insider trading kind of go loose, people stop trusting the market and if people stop trusting the market, they stop trading. Like no one wants to participate or very few people want to participate in a game or a structure or a mechanism that is rigged. Like that is, that is just like, you know, unfair. So, but, but, and so, but, but that's why we actually, you know, we are regulated. There are rules against seller trading. So, so, you know, and these rules are very similar to the stock market rules and the mechanism of how we police it are very similar. And you know, this has been a big topic of discussion and it goes back a little bit to the regulated versus unregulated situation. There are unregulated players, you know, and they are, you know, offshore. And there is, or at least allegedly, allegedly there is a lot of insider trading going on like the Maduro trade that a lot of people have talked about. And you know, that has brought kind of these issues into light. But at least on the cautious side, like we have a very strong position, we ban insider trading. Insider trading is not a good thing. It makes the marketplace unhealthy long term and it Creates an unfair field.

[Ed]

Can I ask how you do that? Because I think in the stock market, inside of, I mean, insider trading laws are very, very strict. And I mean anyone who's, who's walked on Wall street will know and will tell you just how intense everyone is about making sure.

[Tarek Mansoor]

I mean, the problem is the executive who told the cousin, who told the cousin. Right. And that stuff does happen in the stock market.

[Ed]

But we have such airtight definitions in the stock market and such airtight regulations. Or you're shaking your head. As airtight as we could make them.

[Tarek Mansoor]

Yes, sure. But the definitions are airtight here too. And the regulations are airtight here too.

[Ed]

So please expl that.

[Tarek Mansoor]

And I think it's an education thing. So it's, it's a thing that over time we need to get there as an industry. And look, are they perfect? I don't think they're perfect. And I think there's work to do with regulators and policymakers and, and that's something we're very committed to. But the, so how is it defined? The. In the, in. In the stock market? Right. And, and you know, let's just sort of attack that problem first. I think at a high level it's defined as like, you cannot trade on material non public information. Which is basically, let's can make that even simpler. Is like, Ed, if you have a legal obligation not to disclose information that you have that you have received, you cannot trade because trading is a form of disclosure. Right. Disclosing information. You can, you know, one way to disclose information is you can call Scott and tell him. One way is go on CNBC and tell them or you can trade it. And that's way, that's one way of disclosing it. Right. That same standard applies to prediction markets and our rules ban it the same way. Right. So if you have information that you receive that you legally cannot disclose, you're not supposed to tell anyone, like you work at the BLS and the Fed, you're not allowed to release the report beforehand. You cannot go into the marketplace and trade it. And this applies to any of the other markets that we have.

[Ed]

Isn't the reason that it's that it's. There is a legal requirement not to disclose it because of the insider trading laws in the first place, which says you can't disclose this. And just to explain this for people, this came up in your interview with CNBC where Andrew Ross Sorkin was providing to you the hypothetical, like, what if there's a dancer at the halftime show who knows what's gonna happen in the halftime show. And there's. I mean, there's no law requiring her to not him or her to not tell someone about it, but then he or she does. And that's seems to me to be insider trading.

[Tarek Mansoor]

The stock market is not the only market that exists out there. Right? We have markets on commodities, we have market on rates, we have markets on. I mean, we have all sorts of markets. It's not like we add the stock market and then all of a sudden prediction markets happen. But those markets also have rules around market manipulation, insider trading, and so on and so forth. Right? So. So yes, there's some reflexivity. I agree with you. Like there maybe the com. Like the companies, in some ways, the underlying got more strict about some of these things because of the existence of the market. And this could happen in our market too. It's possible. Right? But like, the, the, the way I would describe and describe it is like. And by the way, I do also want to address how we actually police it. Like, how do we actually find. So let's just finish. So let's finish the definition and let's move on to that. But on the definition piece, like, if there isn't a problem with disclosing the information to people, then there isn't a problem with disclosing the information to people. You can trade it like, you know, and, you know, you could tell a friend who can tell a cousin, and then that's completely fair game. And that is not considered insider trading. There's no issue with that. And if people feel like, hey, maybe too many people may be around the stadium and can look at it, and that's like an unfair market, they would stop trading. Like, they would just like, you know, if you over time feel like the subset of information is too important or too prevalent, like too deterministic for the marketplace, and they would start trading, like Scott basically was saying. But I think that the line, you don't want to be in a position where you block information because it is actually totally fair game to go and sit around next to a stadium and figure out what the next song is going to be and listen to rehearsal. That's like doing research outside of Walmart.

[Scott Galloway]

It seems to me my mind starts spinning around the different types of synthetic applications of this or different things you could use prediction markets for, whether it's hedging existing positions. Can you give us some examples of different applications of prediction markets that people have not hit the mainstream yet?

[Tarek Mansoor]

One example. And every time around hurricane season, we get a lot of Calls from people that live in the Keys and they want to basically buy our hurricane contract. They're buying a hedge against hurricanes hitting their city. And it's super interesting because historically what they do this is they go to state regulated insurance, they go to an insurance company and the insurance company insures their home against a hurricane. There's sort of like two issues with that. One, it's an inefficient marketplace. And it's a little bit goes back to how when I started the company, when we were like structuring these trades around Trump or Brexit. Like there's one pricer which is the insurance company and usually don't get a very good price and oftentimes they don't pay out the policy. Whereas having it in an open marketplace enables competitive bidding. Right. So if Ed wants to buy this hedge, you know, Scott or other people can basically be, you know, competing for that market so he can get price improvement. The number two issues for this specific like use case is like insurance companies have pulled out of the Keys because they've had a lot of trouble and a lot of difficulty pricing hurricane risk. It's been like a very, very difficult thing for them to put in their balance sheet. Usually they reinsure it with reinsurers, but reinsurers have pulled out of the market. And so this is a very good alternative that people basically go to. And we see this in a bunch of other places like the Fed. Interest rates, inflation, geopolitical events, bills passing, where kind of regulation could negatively impact an industry or other. And we even see it a lot in sports. I mean, sports, the reinsurance or insurance industry for Sports is around $10 billion today, 9 to $10 billion today. And the same sort of thing applies. So for example, there's a lot of teams that have big bonuses that are due at the end of the season if they achieve certain milestones. And a lot of teams like to insure against those performance bonuses. And they do it oftentimes with reinsurers, but the prices are really bad. And so now that they can basically all float on an exchange, they get better pricing and they get more efficient pricing. They actually know what the fair price should be for this thing. And that's generally a good thing because it increases liquidity in the ecosystem for all these types of use cases.

[Ed]

We'll be right back. And for even more markets content, Sign up for our [e-mail] subscribe.

[Scott Galloway]

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[Tarek Mansoor]

And breathe.

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[Scott Galloway]

1-800-contacts.

[Ed]

We're back with property markets.

[Scott Galloway]

My understanding is that your revenue 10x in 25 relative to 24, are you assuming that same level or ballpark of

[Tarek Mansoor]

growth in 26, 24 to 25? Just to kind of talk about the number, I think we grew, it was closer to like 35, 40 x 24 to 25. And this is like on an FY basis, on an annualized basis, much more. It was maybe like 60. I think we could do, I don't know if 10x but maybe half of that is, I think, within the realm of possibility for this year. It is pretty mainstream now, right? Like, it is very, very mainstream. I think, like the. So obviously, as you get more in the stream, the growth, you know, at some point, I mean, you know, 45% of people up to the age of 45, of men up to the age of 45 are like basically active users of prediction markets now. Some part of them are trading pretty actively and the other part is like consuming. Consuming it as an information feed, as a news feed that they use next to X and other places. Like, that's a pretty large number. Right? You're starting to kind of like flirt with. I wouldn't say you're flirting with the boundaries, but you're starting, you know, you start decelerating as you kind of get closer to the boundaries of the tam. But yeah, I think it's possible. I mean, I think, you know, we're growing. The institutional business is starting to pick up traction. I think going international is exciting. Diversifying into more marketplace markets, types of markets and. And there's a lot of categories that are growing. So, you know, I think there's a lot of lot to be excited about for 2026.

[Ed]

Tarek, I've grilled you a good amount in this episode. I think as we just close here, I would separate two things. As I said at the beginning, on the content calcium prediction markets as a content machine, as an information machine, I don't think it can be disputed. Everyone is looking at this stuff. Everyone is interested in this Stu. This is, by the way, one of the Great things about markets in general. This is kind of why I love markets. It has this really awesome thing which is that it tells you a lot about the world. You can look at a chart and you can understand things. It tells you about the future. This is the great thing. It's even a great thing about options trading as well. Options trading also is an interesting and helpful information machine, content machine. At the same time, I am personally someone who, who thinks that the act of trading options is not a good or wise investment decision most of the time. I would grant you that there are a lot of people who make a lot of money who. Yeah, yeah, yeah, ultimately are doing well. But ultimately something I wouldn't recommend. I don't think it's great. Now, the law generally agrees for the most part, which I think is why we have these stringent laws on things like gambling, on things like options trading, where we say you're only allowed to do it if you prove this, this and this. You're only allowed to do it if there's sufficient education.

[Tarek Mansoor]

That's not true for gambling or for gambling.

[Ed]

It would be. We need to express to you. And I mean, if you're advertising as a gambler, you need to say you need to gamble responsibly. We kind of recognize that that is built in. You need regulation. Which brings me to. I view Kalshi as kind of the only platform in prediction markets that actually is embracing regulation. I think prediction markets are here to stay. I think the genie's out of the bottle. This is happening. So the thing that I think is really important for you, and I guess I'd want to hear more about, is how will you embrace the regulation that so many tech companies throughout history have tried to shirk off? Because it eats into margins, it eats your bottom line. It can be an annoying problem. How do you deal with that?

[Tarek Mansoor]

I don't think of it that way. Look, I think. Let me just address it in two folds. First, the model. You may or may not. You know, people may or may not agree whether trading an option is a good or bad thing. I strongly believe that trading on prediction markets is a good thing. And we've seen the results. People are being more engaged in the political process. They research different things. And if you talk to our traders, you see like it brings them community. Going back to the Joel example, I think one of his best men is someone who he's met in a prediction market in Calchain, our discord. And I think there's a lot of beauty that's coming out of these markets where you're seeing this subjective debate that usually happens, people insulting each other on Twitter and polarize on Instagram, happening more quantitatively, more objectively, more in a more engaged way, more intellectually on prediction markets. And I think that's a good thing. I think we're like, we're not talking about like when you have a position on something you get more self calibrated like you know, and when social media is incentivizing clickbait, prediction markets are incentivizing truth. Calibration, objectivity, the pursuit of truth, all of these things are good things. And I think over time, you know, when I think about people like even you know, when we think about like you know, our generation, like we want people to value things like being accurate, being precise, thinking critically about the word. And I think prediction markets brings a lot of that our regulatory position. So we spent four years getting regulated before we launched a single product. So the reason why you heard about Polymarket and a lot of other, you know, Polymarkers really primarily and other is they just launched without a license or anything else. We were committed to like we will get the license upfront no matter what. And let me tell you, like when I was 22, the idea of spending my 22 to 26 year olds just doing regulation and law and legal stuff without a product, I mean it was horrendous, it was really difficult. But I'm very proud of that decision because it led to the outcomes that we're seeing now. We're leading in the market. But I want to build an enduring company and I just don't see a way to build a financial services company. I can't talk about social media and other places but a financial services company without proper regulation, I think it's not right. I think you need a regulator overseeing every step where the money is going to reporting of transactions. Everything needs to be public. But then I also think that there are questions like the ones that we're discussing that over time we need to get better at solving and that's something as a company I can do alone. We need the regulators to work with us.

[Ed]

Tariq Mansour is the co founder and chief executive officer of Kalshi. Tarek began his career as a quantitative trader at Goldman Sachs and as a global macro trader at Citadel. He went on to co found Kalshi in 2018. Tarik, thank you very much. Appreciate your time.

[Scott Galloway]

Thanks Tarek, thanks for having me. What do you think Ed?

[Ed]

What did you think? Can I throw it back to you?

[Scott Galloway]

Well you know me, I don't. I'm pretty quiet. I don't like to share my viewpoint just sort of reserved. I think they're trying to be the clean, well lit corner of this environment. I mean I struggle with the concept as a whole and the tension between. You can't infantilize young people. Paul Tudor Jones, one of the great investors will say that 80% of the stock market is speculation that if you look at there's $3 trillion in transactions, it's like 300 billion of secondaries and equity offerings, true financing. So technically 90% of it is not investing. It's me betting against you that the stock's going to go up or down and you taking the other side of that trade. So this isn't much different but at the same time it does feel like it has more of a gambling feel to it. So I don't have moral clarity around that. What I am absolutely fascinated by is the opportunity for. So I am a resident of Florida. Basically Floridians are struggling with they can't get insurance. And it's not only you have to go naked in terms of risk. If you have a mortgage a lot of. Because the mortgage industry is in bed with the insurance industry. In order to get a mortgage you have to show proof of insurance. And now homeowners in Florida can't get insurance. So is there some sort of synthetic where they basically every time Hurricane Claudia pops up they basically agree to buy or bet for you that this, this will hit and if it hits, you get a bunch of money to cover your, you know, damage. I just think there's so many opportunities here. As you know we are constantly using this information because as it ends up the wisdom of crowds really is wise that it. This might put pollsters, an investment banking analyst out of business because the guy covering Apple for JP Morgan wants Apple's next debt offering and is always going to exaggerate the upside or have a bias towards the upside. There's nothing to get to how you really feel about something when you ask people to put their money behind it. I hope that he does appear to be sincere about not embracing regulation but at least being relative to his peers he gets credit for embracing regulation as opposed to trying to skirt around it. So I think he gets some credit there. It'd be interesting to see if he. I thought it was 10x. He said 40 to 60x. Obviously 26 is going to be a pivotal year for him. Anyways, my thoughts. What are your thoughts?

[Ed]

I think you have to give him credit for wanting to comply with regulation. I think there are so many of these companies. The idea is, let's just scud around as many rules as possible to make as much money as we can. That's not the route that he is taking. I do think he needs to get more clear on what are the lines that you're drawing here. What are the lines between speculation versus investing? What are the lines between speculation and gambling? These are hard lines to draw. It's not very clear, as you say, options trading, you can make the argument that the entire stock market, or at least 90% of the stock market, if you're not directly participating in the fundraising and investing of an actual company, if you're just trading the stocks around, maybe that's speculation, maybe that's gambling. I think it's a harder argument to make. But the point being, there needs to be a lot of clarity on what are the definitions between these different things. Because what I can tell you is that betting on, say, the color of the Gatorade is flat out gambling. And there is no real benefit to society other than it's fun and it's. And it's a form of consumption. And if that is the case, and if that is happening on the platform, he says they didn't do that, do the Gatorade on the platform, but maybe there are some others. If that is the case, you gotta regulate it like it's gambling. You gotta have disclosures you need to add. If you're gonna advertise, you need to say, gamble responsibly, trade responsibly. The same way that we have real robust regulations around any other addictive product, around cigarettes, around drinking. I mean, the rules are there in place because bad things can happen. And so what I would love for Tarek, and I think he's doing this better than anyone else in this industry, which is happening. Sorry. It's happening whether you like it or not. He is embracing that more than the others are. And I think that is going to be crucial to minimizing the very real potential for downside risk here when it comes to speculation addiction and gambling. Because unfortunately, that is happening on these platforms. So now it's on regulators to figure out how to make sure this works for everyone. This episode was produced by Claire Miller and Alison Weiss and engineered by Benjamin Spencer. Our video editor is Jorge Corty. Our research team is Dan Shalan, Isabella Kinsel, Kristen O' Donoghue and Mia Silverio. Jake McPherson is our social producer. Drew Burrows is our technical director, and Catherine Dillon is our Executive producer. Thank you for listening to Profgy Markets from Profgy Media. If you liked what you heard, give us a follow and join us for a fresh take on markets on Monday.

[Scott Galloway]

You have me in kind. Reunion

[Tarek Mansoor]

as the water.