Stephen Grugett (Manifold Markets Founder) - Predictions Markets & Revolutionizing Governance

Now here's a question I've had for a while.

Why don't companies who have direct incentive to get the best possible information on themselves, on the factors affecting their business, why aren't they using internal prediction markets if this is the best way to aggregate information?

All right, this is going to be fun.

Today I have the pleasure of speaking with my friend Stephen Grugit.

He's the founder of Manifold Markets, which has received a grant from Scott Alexander.

Scott has written

thousands of words about these guys, and they've raised a $2 million seed round.

And, you know, it's an incredibly exciting project.

So Stephen, why don't you tell us a little bit about Manifold Markets?

Great.

Thanks so much for having me on this podcast, Dorkash.

It's great to be on here after seeing other people like Tyler Cowan and David Deutsch.

I guess first thing, I'm one of three co-founders of Manifold Markets.

But what we're doing is building a platform for user-created prediction markets.

So the idea is that anyone can come onto our site and create a question about anything that they care about.

And then they can have their friends and other people on our site come bet on that.

And the betting process, through the magic of our market mechanism, will help

get the best and most calibrated probabilities that you could find.

So let's talk about the mechanism here.

So

correct me if I'm wrong, but the idea is you use real money to buy Manifold dollars.

What is your reason for expecting that people will care a lot about how many manifold dollars they have?

So what is your hypothesis about human nature and reputation that makes you think this is something people are going to invest a lot of effort and time into calibrating?

Yes.

So I guess to take a step back for people listening to this, Manifold uses a Play Money currency.

If you sign up right now, we'll give you $1,000 Manifold dollars, which is our in-platform currency

for you to use and bet as you see fit.

But the reason why we think that play money can work is that people are driven more by status and competitiveness than greed.

We kind of see ourselves as a social game where people can come on to hone their skills at predicting and then demonstrate to others that they really do know more about what they're talking about and they can prove it with

an objective track record from their betting history.

yeah that that that's uh that's a very interesting point which makes me wonder do you expect that in the future wall street firms will be enticed to get the top people on the leaderboards on manifold markets to come work for them one of the objections that tyler cowan has to um prediction markets is you know he he's kind of tongue-in-cheek about this but i remember at one point him saying you know if you guys are so good at predicting stuff you would expect all these hedge funds to be trying to constantly hire you guys the fact that they're not makes me think that, you know, this is kind of just a hobby.

This is not...

So I'm curious about your reaction.

Do you expect people to be coveting these top predictors for

their prowess at predicting the future?

Yeah, I'm obviously very biased, but I think something like that is possible.

I think we have a leaderboard right now.

Our top predictors are actually quite good.

The person who's currently occupying the top slot won big on the Russian, on one of our markets on whether Russia would invade Ukraine in February.

So in the forecasting community in general, there actually is like, as you would expect, a fair amount of overlap between the people who are using these services and financial professionals who actually do manage money or are trading as their profession.

So I don't entirely agree with

the premise of the question or Tyler Cowen's earlier point.

Although obviously

as a plain money platform, we do attract a fair number of hobbyists who, despite not having a financial background, still are quite good.

I do believe that there is a lot of like untapped potential

in these top predictors and that sites like ours actually are able to identify them.

In your experience, what has made people who are the top predictor so

good at the art?

Is it just their domain knowledge?

I know there's different theories about how people can get good at predicting.

Based on your experience, what kind of traits do you identify here?

So, probably a big one is just like experience.

A lot of our top predictors have actually come from other sites and have spent a good deal of time thinking about forecasting and prediction in general.

Probably the first hurdle that most people have to overcome in order to start improving as a predictor is getting used to clarifying and

crystallizing your views about the world.

If you're thinking about some political event,

you can very easily incorrectly

misremember that you got some event right or not.

But if you're not like actively putting out numerical predictions and recording those to

keep yourself audiences, it's very difficult to improve.

So you have to have, that's, that's a good first step.

And a lot of our users already cleared that before before joining our site.

You know, we talked about whether

finance firms would want to hire these predictors, but it would be incredibly exciting if we lived in a world where news firms would want to hire the people who are very good at predicting.

Scott Alexander actually has a very interesting post where

where he high where he speculates, what if you had investigative reporters who could short, like let's say they discovered that some government has really fucked up.

They could they could like, I don't know, short the market on the government's GDP in a year and then release the information and then benefit from having that from their investigative journalism.

I don't know if you're what your reaction is to that, those kinds of ideas.

Oh, I think that's great.

I think that's great.

I think that's a very obvious case of pro-social benefit of markets

using the market mechanism to, or in some ways, it's kind of like providing a public good

that wouldn't, you know, society otherwise wouldn't be able to produce.

Getting accurate information about

corporate

malpractices or whatever is very valuable to society.

Anything that we can do to encourage that is good.

This is the question a lot of people will be interested in, and maybe you can't comment, but is there any potential that eventually, through crypto or offshoring or some other option, that

somebody's ability to predict will somehow be able to get reflected back on them in some sort of monetary gain outside of the play money?

Oh, on our site.

I think that's possible.

Well, first of all, we are planning to do things like host tournaments with real cash prizes.

That's something that we are able to offer despite being a play money product.

You know, we originally started as a

crypto idea before

pivoting back to Web2.

You know, that's funny.

We're one of the first firms to pivot from Web3 back to Web 2 for

usability reasons.

But

real money crypto,

creating a real money crypto offering is something that's on our back burner and something that's worth thinking about, that we're thinking, actively thinking about.

It would probably be in the form of a separate product.

though, rather than as an addition to our current offering.

I'm curious what the usability concern was.

Is it like connecting the MetaMask wallet to your account?

Your current process is so easy.

You can basically make a bet within 30 minutes or 30 seconds of visiting the site.

I'm curious what the concern was there with crypto.

I think there are several things.

The first is just like onboarding.

Only a tiny chunk of

the global population actually has created a MetaMask wallet or a Solana wallet or any of these things.

And the process of doing that and transferring tokens to the wallet is actually pretty cumbersome and not yet very easy.

So that's kind of a a huge hurdle just to start with.

Then you have to add in all of the other frictions associated with being a crypto platform.

It takes a while for transactions to be confirmed.

You have to, you know, if you're doing everything in a purely decentralized way, you will have to sign each transaction with your wallet, stuff like that.

Each of those things is just like an additional hurdle, you know, that will prevent users from being able to bet and enjoy their experience on the platform.

Yeah, not to mention transaction costs, which would reduce liquidity.

Yeah, yeah, that's a big one, too.

Yeah.

So, you know, one of the things,

speaking of reputation, one of the things that seems interesting to me, my prediction over the long term is that the reputation of the market maker or market creator rather will matter a lot because in your website, they're the ones who get to resolve

questions or resolve markets.

So what is equilibrium there?

Because is it just that there's going to be a few trusted market creators who people trust to

adjudicate what happened or will anybody be able to have a create a big trusted market?

I think it'll be kind of a bimodal distribution where you'll see a few huge market creators that are high trust and have

huge volumes across a lot of their markets.

And then there'll be a very long tail of smaller individuals with less of a track record and their markets will be participated on by people closer to them on the social graph, their friends or friends of friends and stuff like that.

Now, here's a question I've had for a while.

Why don't companies who have

a direct incentive to get the best possible information on their, you know, on themselves, on the factors affecting their business, why aren't they using internal prediction markets if this is the best way to aggregate information?

Yeah, this is a great question.

So, first of all, a lot of companies have

tried using prediction markets internal, including Google, GM,

the CIA, and a bunch of other firms as well.

But for the most part, you find that

they will use it, people will talk about it for a bit, they will even praise the benefits of prediction markets, but ultimately they'll abandon them.

And I think the main reason for that,

and

a very Hansonian point, is that people literally don't want to know the answers to a lot of questions.

So, in a corporate context, that mostly

manifests itself in

the manager not wanting to,

you know, the manager choosing a course or vision for their company and then not wanting to get negative feedback about that.

Even if the feedback is mostly positive, you know, the fact or like it still can like see doubt on the part of employees.

And, you know, the introduction of a prediction market by itself might just

lower the odds that that mission will be successful.

You know, even though one wouldn't think that just the addition of more information would actually change the outcome.

But I would say that that's the biggest point.

It steps on management's toes and they don't like that.

Interesting.

It's almost the opposite of his point about consultants.

So his point about consultants is that they basically put a pretty face from Harvard.

They allow you to say, oh,

this highly credentialed person who talks well supports what I'm doing.

So that's how we should go ahead and do it.

Now, one question I've all said about this Hansonian view is,

Even if it's true,

you would expect some firms to do the painful thing or some managers to do the painful thing.

I mean, you're a startup founder.

You know that many of the most successful startup founders

will go ahead and do something that is quite difficult that they don't want to do.

And we would expect over the long run for the market to be dominated by players who have done the thing that helps their company, right?

Out of all the thousands of companies that are out there.

So why

do you think in like a decade or two, all the best companies in the world will have internal prediction markets?

Or the force from managers against us so strong that that's not going to happen?

So I would say there are two parts.

I would say the first is a rational concern on the part of managers to not use prediction markets because it undercuts their mission.

It's not merely an irrational quirk of human nature, although

perhaps it is in general, but it's not an irrational quirk of the manager's part in choosing not to use them for certain contexts.

The second part is they're actually, I think they're the areas where prediction markets more clearly add value without distracting from the mission or hurting management are where they're used for their informational aspects or to do like market research.

You know, questions where you need to like survey, a broad survey of like what consumer behavior will be, how our competitors will behave, that sort of thing.

I think that's a much clearer example of where prediction markets can provide value in a corporate setting,

which

doesn't fall prey to most of these downsides.

So, and then the the question becomes like, why hasn't that happened yet?

And I would say

part of that is actually just a

usability concerns.

It's actually very hard to create a product that's extremely simple and easy for all of your employees to use, that doesn't require too much thought, but can still yield reasonable results.

And I would say part of our goal with Manifold really is to bring the bar down lower such that more and more people can participate in prediction markets and it'd be like a pleasant, fun, and easy-to-use experience.

Yeah, yeah, that it definitely is.

You know, I was about to suggest, you know, maybe it would help Zuckerberg to know, maybe it's like subsidizing market to find out how many VR devices there will be in the world by 2030 to

help him make his metaverse plans.

But maybe he doesn't want to know that, or maybe at least he doesn't want that publicly known.

So, you know, one question I have is: in what situations is it best to have a single person

compound all the available knowledge?

And

in what cases is it best to kind of decentralize the decision-making process by having a market?

I would say that in general, like if you're making a decision in the real world, it's often very difficult to operationalize what the success criterion is down into one thing that the market can then

measure and be used to act upon definitively.

I would say so that that's kind of the biggest case for

personal discretion or

human involvement in decision making.

Or in general, I think prediction markets work best when people are

creating markets on a variety of metrics and then using human intuition to figure out what the best course of action is to proceed using that information.

I'm curious, what is your opinion about insider trading in Congress, for example?

I know this is like a big debate.

Do you think it serves like a useful price discovery function or too much of a hazard of adverse election?

It kind of a tangential point.

I'm just curious about your opinion.

I would say in general, my view of insider trading is,

I basically have Matt Levine's view is that it should be viewed as a like taking from shareholders rather than a like fairness or equity

type of discussion.

I do think in general, like insider trading obviously does benefit price efficiency, but there are other things that we care about.

We also don't want,

in general, our corporate shareholders to be profiting from

certain types of information and all those.

In the case of

congressional betting or insider trading by elected representatives, I think that's for the most part not cool.

We would prefer for them to be compensated directly through salary or other things which are more open and transparent to the public rather than

this is kind of a way of profiting or, you know,

like a roundabout way of corruption in some sense.

You know, you can make a deal with some company and then trade on that.

And instead of the money that never directly passes into your hands, but you're privy to this insider information.

And the net effect is,

you know, equivalent to this practice, which we would not normally condone.

Now, one place where I'm skeptical of prediction markets is when we're talking about

questions that resolve over a long period of time and

which there's no good base rate for, so the market hasn't really been trained on that kind of question.

One example would be, what are the odds of catastrophic AI by like 2030, which I'm sure is a question on your website.

And I'm not sure how much crudence I put into the prediction on this question.

I mean, one, because I'm not sure why I would expect that much

good information to be aggregated here in the first place?

Would it just be, I mean, what is the information they're going off of?

And

second, I guess more important is, you know, why would somebody bet

yes?

Because the best case scenario, if they bet yes, is they die anyways, right?

They have nothing to gain if catastrophic AI happens.

So in these kinds of scenarios, what do you think is the role of prediction markets?

Do you have these kinds of concerns?

What are your thoughts?

Oh, I think, yeah, both of those concerns are very valid.

I think part of this is just like a fundamental like human constraint.

If things are very far in the future, we care about them less.

It doesn't really, you know, that's true in prediction markets, but it's also true in every other domain as well, and every other forecasting technique as well.

You know,

the interest rate is like a fact about human nature.

Or like discounting of the future is like a fundamental facet of human nature.

And you can twiddle with the mechanism here on the margins here or there, but I don't think it'll fundamentally change that.

For your second point, though,

your other point is very well taken, too, that you can't

bet on apocalypse.

You're not going to be there to collect your winnings.

The money is worth less in that universe, so you should rationally bet against it.

Actually, so Brian Kaplan and Eleazar Rudowski actually do have a bet on an AI apocalypse.

The bet is about whether there will be

catastrophic AI, I think by 2030 is the exact bad.

And so

Brian pays Eleazer now, and if by 2030 there hasn't been catastrophic AI, then Eliezer pays Brian

the sum that Brian paid plus more based on like the ratio of their bet,

which I thought was an interesting idea.

Just going off this topic a little more, you know, one of the things that Scott Alexander brought up in one of his blog posts is when you have these kinds of bets that resolve over long-term, it doesn't have to be as

far-fetched as

AGI.

It could just be something like who's going to be president in 2024.

He pointed out that, at least at the time that he wrote it, Dwayne Johnson had like a 9% chance of being elected president, which seems high, except why would somebody get their manifold dollars held up in a question that won't resolve for four years, or I mean, two years now.

The ability of speculators to correct prices is diminished because they don't want their money to be held up in questions that won't resolve for a long time.

How are you guys dealing with that kind of problem?

I would say, like, so in general, the best way to tackle these long-term, more speculative questions is to try to break them down and address the proxy variables that are most relevant

to, you know, to predicting their success in the future.

You know, so instead of asking, like, will the AI apocalypse happen in 2030 or like in 2050, you can ask like, will OpenAI's GBT4 like exceed you know this number on this benchmark etc or similarly for like the rock like um instead of asking like will the rock be the president in like a 12 years or whatever 20 whatever uh you could ask like what are his polling numbers today like what are his favorability ratings has he like will he indicate interest in running

show interest in running as a politician etc etc and those are much more short-term questions which you can use to you know get a sense of um

uh you know of

the longer-term, more speculative questions that

interest you.

Okay, so

Tyler Cowan has this other criticism of prediction markets

that, listen, these prediction markets are tied to financial markets that you actually could bet on, right?

So I don't know if you think somebody's going to be has a higher or lower odds of being president.

Maybe that has effect on

GDP or something, and that has effect on stock prices.

And so then he says, well, if you're so good at doing,

so good at betting in prediction markets, why don't you just bet in the financial instruments that are linked to whatever question you're interested in?

And Brian Kaplan's response to this is,

There's so many different things that can affect any given financial instrument that it's not, it's, you know, it's not easy to explain.

Okay, because I think A, about, you know, you know, Dwayne Johnson becoming president, I can invest in asset B.

I feel like that defense of prediction markets is a criticism of your response that you just gave, where you're saying short-term prediction markets can substitute for your interest in long-term prediction markets.

I would say yes and no.

So, like,

asset prices of

major financial commodities and equities and other instruments are affected by way more factors than another prediction market on a more isolated question on some proxy variable that you care about.

The nice feature of prediction markets is that you really can isolate the particular risk that you care about.

And even if it's just discussing like one proxy variable that's related to the overall picture, you can still get a much better understanding of the thing that you care about by picking multiple well-targeted like proxy variables and creating markets on those rather than like oil prices, which tell you many things.

too many things.

Okay, so lay out your vision for me of like 10, 20 years.

You know, we have have uh prediction markets are not only you know much more liquid more people participate in them and it's kind of uh everybody kind of knows what a prediction market is so like people understand what it means when you say um you know this prediction mark uh

you know biden

i guess it wouldn't be biden then but whoever the president is passing this bill had uh huh

uh one of the many things that would need to happen other than you know a constitutional change would be um major advances to longevity research um

oh yeah So, what would the world look like

if people actually cared about

prediction markets and if it was like common knowledge,

what the market thought about any given situation that was happening?

Well, I would say, first of all, I would say that would probably be a much better world.

Across a wide variety of domains, I think it's better

in nearly, but not all cases when people are grounded in terms of facts and well-calibrated predictions instead of like pure speculation or like

you know ideologically biased thinking.

But you know more concretely, I can imagine a world where

the average like news article, blog post, CNN station, if that's still around in

10 or 20 years, has like an embedded prediction market on whichever topic that they're discussing.

And it'll just like allow people to immediately get a sense of what like the most grounded or like

it'll immediately ground the opinions that people are hearing in fact and make it easier to have more productive conversations and ultimately allow them to better understand the world.

I hope that's the case.

You know, there's a pessimistic take that people are not consuming politics to understand what's happening

and that

they'll almost resent you for presenting them with this kind of information.

That's true.

Or certainly I'm not implying that a large part or even like a majority of the consumption of political news is based on a desire for accurate information.

You know, I think that would be a very, very naive view of how

humans operate.

But at least a small part of that is, you know, at least some portion

of people's desire to consume news actually is to legitimately understand the world.

And insofar as people are attempting to do that, you know, prediction markets can help.

I really hope so.

And I think that actually could be true,

which is very exciting.

So one question I have is

these trades that people do on your market, you know,

4% of

what is traded, or the traders' winnings, they go to the market creator and 1% are just burned.

Correct me if that's wrong.

But that seems like a negative sum

bet,

which means that are you concerned that that would reduce liquidity?

Because

people have to get over a higher threshold of confidence before they're willing to bet on any given market?

Yes, yeah.

Like

fees

do impede the efficiency of the market in some sense.

You know, there are people who on the margins would trade

if there were no fees who don't when there are fees.

That certainly is true.

But part of the reason why we have fees is like to encourage things that we like.

You know, we have a creator fee.

The creator earns a commission on trades that incentivizes them to create and resolve more markets.

We currently have a liquidity fee as well, which feeds into the liquidity pool, which you can think of as subsidizing the entire market.

I'm curious,

what is your background?

So, you know, one of your co-founders is your brother.

Do you guys have some sort of financial background or mathematical background?

Because I was looking at

your technical documentation.

I'm not claiming to have understood most of it, but I saw the formulas that were there.

I visually skimmed it.

And

how are you guys able to get into this field?

So I guess I studied computer science in school.

Then I went to work for SIG or Susquehanna.

It's an options trading firm for a little bit.

Then I left to go work

for my friend's like RoboAdvisor startup where I wrote their like

their portfolio optimizing software.

Yeah, so I have some financial experience as well.

And all three of us are technical, you know, and

also have a previous background doing other entrepreneurial things as well, too.

So we're all, we're kind of like full stack entrepreneurs, I guess you could say.

Can you talk a little bit about your previous entrepreneurial experience?

I think listeners might be interested.

Sure.

So right before this,

my brother and co-founder James and I were working on our app called Throne.

It's a subscription group chat app for online creators.

So people like you

or like Instagram creators or DJs or anyone who's built up an audience online,

the idea was that, you know, they can set up a private group chat where they're their audience where they're paying a subscription fee to join.

And basically

the premise of our

app is that we provide a much better chatting experience for larger groups.

So it's designed uh, designed to accommodate like the creator's entire audience and make that a seamless experience.

Yeah, I have a friend who has a popular fantasy football channel and he has,

you know, he has a very profitable Patreon where basically from the point of the Patreon is it'll give you the link to the invite to the Discord,

which is, which seems condiluted.

And this product where you're just basically combining those two services,

that seemed very useful.

So what happened with that?

It's still going slightly.

Basically, we couldn't get the growth that we were hoping for.

The ultimate cause is it's kind of too late.

Like the creator market is already saturated with all different sorts of tools.

Most creators are already monetizing one way or another and aren't keen on moving, monetizing using a new platform.

So when it comes to the manifold markets, I mean, the idea for having prediction markets, even the idea of having prediction markets play money, I I believe, has been around for a long time, right?

What took so long for somebody to make a user experience that was so comfortable as yours?

Or is there something else that prevented somebody from making a manifold marketplace?

Yeah, I would say the other key piece of the puzzle that other people were missing is the idea of user-resolved markets, which on the surface sounds a little bit crazy, that you just allow anyone to come and create a market on any question where they are also the judge of that question and can resolve it in any way that they want.

You know, that obviously opens the door to fraud and abuse and people taking advantage of the system.

And the fact that there is a possibility of fraud basically has prevented other people from like even exploring this option.

Instead, they're opting for oracles or centralized authorities deciding the outcome of all markets.

But of course, that like severely limits the scalability and reach of a prediction market platform if users can't go on and create their own thing.

So it's really realizing that user resolve markets actually can work that led us down this path.

There is a small amount of fraud, but it's actually quite small and manageable.

If you allow users to choose which markets to participate in, they for the most part are making pretty good decisions about where to allocate their time and money.

There's this great essay called Unix is Worse is Better.

I don't know if you've gotten a chance to look at that.

The basic point the author makes is, you know, if you ask like, why has Unix been so successful, you know,

you can say, oh,

some of the features and some of the design decisions are arbitrary, they're somewhat inoptimal in certain situations,

and then

but then you,

it seems that maybe it was those bugs that actually allow Unix to be the kind of thing that can actually run on real computers.

Maybe it's not

maybe it's not optimal from the

perspective of somebody who wants something super elegant and beautiful.

And Groan has a really good blog post about this, Bitcoin is Worse is Better,

where he makes the same point about Bitcoin.

Like some of the, I'm not remembering the details right now, but some of the,

you know, some of the actual constants involving like, you know, block size or whatever, they're pretty arbitrary.

But the fact that somebody just put out the arbitrary numbers meant that innovations that could have been around years before in terms of cryptographic tools actually got instantiated in like a in a product like Bitcoin.

And it kind of seems like you're taking a similar attitude towards prediction markets,

even if it's somewhat arbitrary to let users resolve markets.

That's better than having some sort of Oracle structure, which is super convoluted and hard to use and may sound good in theory, but is kind of impractical as something that people want to use.

Yeah,

that's exactly correct.

I think the most important thing for,

you know, not just for us and not just for prediction markets, but for creating a usable platform is making sure that the key mechanism is something simple and easy to understand, more so than handling every possible edge case perfectly.

As long as it's the core experience is extremely simple and easy to use and user-friendly,

that matters much more than like the 1% of cases where.

But I'm curious if this is something you learned at your previous startup.

Did you guys make this mistake and now you've learned to avoid it?

Or

curious how you came to that realization?

You know, I don't know.

I don't know that I can think of a good example that's directly relevant.

Although we did like simplicity of,

I guess, like both the business model and our user interface for our previous chat app were big considerations.

You know, the idea of having, or like a subscription model is kind of like the minimum viable

business for like a creator to support themselves in a real way over time.

That might be one manifestation of this principle in action, but I don't know.

Okay, so one concern somebody could have about manifold markets is,

you know, you said you were giving out 1,000 manifold dollars.

Somebody could, you know, just maybe even make a bot that I'm not giving anybody ideas,

but make a just like create a thousand different accounts, make different trades on all of them,

and or make a sequence of different trades on all of them.

And in one of them, they just make a series of the best trades that anybody has ever made on the platform.

And now they're on the top of the leaderboard.

It's certainly true that if you're giving away free money,

that's not an economically sound mechanism.

We currently do do some things to prevent abuse and bot behavior.

I'm not going to tell you what those things are.

If we end up open sourcing our code, though, the cat will be out of the bag.

You can see for yourself what abuse practices we have in place.

I would say that we're not necessarily committed to maintaining our free giveaway or free sign-up bonus indefinitely.

That's definitely partially a

growth and just starting off thing.

In the beginning, most of our users

have been very well behaved and haven't

abused this system.

If Manafold becomes a key nexus for people trying to weigh in on the future, we may have to be more strict with our policies.

It kind of reminds me of the PayPal story where they were giving like a $10, $20 bonuses for people for signing up and it basically meant they got exponential growth, but they were losing money faster.

I guess in this case, you're not like losing real money, but

I don't know, maybe you're

diluting the reputational value that the best people in the leaderboard have, at least for now, maybe.

Yeah, I would say one of the other things that we're interested in, or like the concept of a global leaderboard becomes less important over time, the larger our site gets.

You know, a lot of the markets that people bet on are personal markets or markets between friends.

What you as an individual care about

in terms of ranking who the top traders or predictors are really is not all of the markets that we have on our platform, but the subset of markets that interest that are of interest to you.

We actually just remove, or like we used to have this feature called communities, where you could create a community centered around a collection of different markets and we would show the leaderboard just for those markets.

And that's a way of judging

assessing the

ability and skill of predictors within some particular domain that you care about rather than globally.

We'll probably bring that back in some capacity in the future.

Can you give an example of that?

I guess something like fantasy.

Yeah, so one thing you might care about is like, who is the best, like Russia, Ukraine, who is like the best like, you know, like geopolitical and war predictor?

You know, and what the one way to assess that would just be to handpick a few markets about

the invasion and the subsequent course of events during the war, and then just see how much profit people have made within those markets.

And I think that that'll actually give you a reasonable estimate of

who the top predictors are there versus just like a global thing.

For a while, one of our top markets on our site was about whether this guy would allow,

whether this stray cat would allow its, like, this random human to pet it.

You know, totally, totally random stuff like that.

You know, if you're, if you're trying to assess who the best like geopolitical thinkers are, who the best economic thinkers are, you may not care about the stray cat.

But a lot of people really do care about the stray cat

in other contexts.

So

it's a fine balance to strike.

Another interesting part of your platform is, so people can buy and more play money.

And I guess the concern is even within these

even within these subdomains where people are being compared, that

the actual proficiency of a person could be distorted by the fact that somebody else could just buy more manifold dollars and

as a result, maybe able to have a higher profit.

I guess you can measure it maybe by

percentage gain on the total amount of money or something.

But yeah, I'm curious on your thoughts about this.

So, in general, I'm

pretty pro-efficient markets.

You know, if you think about what's happening when a whale comes in and buys up a huge amount of money and bets it on the wrong side, what they're essentially doing is just providing a huge subsidy and bonus to the people who are actually correct.

You know, markets are a mechanism which is like the most efficient way of solving the whale problem.

If you are too much money and you are not very smart and are very confident in your views of the world, like the markets have a very fast and easy solution for you to solve, to

obviate that problem where you will no longer have so much capital

to

throw about.

There's a direct analogy to this, actually, as I'm sure you're aware in, you know, like real markets, where like a pension fund or some other sort of big fund needs to like rebalance its books or something.

So it'll it'll need to just like dump a bunch of stock and you know liquidity providers can make money off the big trades that the

you know that these big funds need to make.

So I guess then you wouldn't be you wouldn't be interested in schemes like I guess quadratic

like

some decaying

some some decaying value of the manifold dollars that you can buy in one account.

So like the neck the marginal

the marginal manifold dollar costs more than the one before it.

You think this would inhibit price discovery, right?

Yeah.

Although I have toyed with some other interesting monetary schemes in the past.

So one idea I had is introducing demurrage or like basically negative interest rates on cash balances.

So like you could imagine a world where like

where

your purchasing power kind of erodes over time.

You know, if you made a bunch of like really good predictions this year, you know, it's not necessarily the case that you should be like rewarded by, you know, having all of that cash forever.

You know, maybe some portion of that uninvested, those uninvested cash balances erodes by, you know, 20% a year or something like that.

I think it's a really cool idea in principle, but in practice, like users absolutely hate,

you know, losing money for any reason at all.

So it's kind of like a non-starter.

But it's interesting to think about.

Sorry, I'm not sure I understood.

If the re-explanation is unnecessary, then we could could just cut it down to the final.

But just for my benefit, can you clarify what you were doing?

Sure.

So the idea is like

at certain times you'll have just like uninvested cash, you know, that's sitting in your account.

Yeah, yeah.

The idea is to just like charge you, charge you for that.

So

charge a sales tax at the rate of like 20% a year, but like maybe like once per once per day at midnight, you lose, you know, whatever, whatever amount that is,

a small fraction of your uninvested cash.

Okay.

So, you know, one thing that makes financial markets really efficient is you have these big firms that are putting in large amounts of capital to recruit the top talent in the world

because it's worth it for them.

You know, they're running like these supercomputer simulations

and,

you know, like it's expensive to do all this stuff, right?

But it's, you know, it's worth it if you're getting like 0.001%

of a trillion dollar market.

In the case where you have play money, what is the incentive for, I get that people who are hobbyists or are in other ways motivated to do this might choose to do it and like choose to engage in it

themselves.

What would incentivize somebody to put in the kind of effort it takes to have efficient financial markets and cost and time and so on?

Yeah, so I would say that in general, people are willing to put a lot of time and effort into virtual economies irrespective of financial gains.

You know, if you look at things like World of Warcraft or earlier like Second Life, which has like virtual real estate, people are willing to invest the equivalent of hundreds of thousands or millions of dollars

in this game world.

I feel

people's ability to drill in and focus and work on things that are of interest to them

is just like a very, very powerful force, even if it's not directly tied to a financial payout.

So what is the point by which Manfold's own internal decision-making will be informed by prediction markets involving, I don't know, the firm's

predictions about the firm?

Oh, it is already.

We actively create markets on all sorts of things which are of interest to us.

So most recently, we created a market on whether we would be able to complete our fundraising round by the end of April.

that was a cool market.

The market believed in us for the most part.

I don't think we like fell lower than like 85% somewhere around there.

But we,

you know, internally, we actually do try to

dog food our markets as much as possible.

We have a new market now and whether we'll be able to onboard three employees, I think, before the end of June, something like that.

You know, that's a number that we like try to keep our

eyes on.

I guess probably the first, the first big

case where the market actually

substantively informed our decision about how to act as a company was an early market we created on whether whether we should try to monetize

by selling the play money.

Initially, we weren't sure whether that would be a good thing to do at all, whether users would hate it or it would seem scammy or whatever.

But we created a

prediction market on this subject.

I think phrased in conditional terms that if we did introduce this,

if we introduced the feature, would we keep it for some period of time?

And

the market seemed to think that we would.

So that actually was a factor which played into our decision.

Yeah, I'm asking these questions in probably the wrong order.

So this is probably one of the initial questions I should ask you.

But talk me through the timeline of developing Manifold Market.

So how long ago was it launched?

And like, what were you, you said in the beginning it was supposed to be based on crypto.

When did you guys change your mind?

What is the timeline here?

Yeah, so this company began long, long ago, way back in December of 2020.

Yeah,

yeah, so it's a very very new company.

Basically decided to ditch crypto after like a few maybe like a week, a week's worth

of

speculation and research.

Mo mostly because we or part of it is that we just thought we could build a play money prototype very quickly and we could just like test that and see what the experience is like.

And if we wanted to, we could continue further on into crypto.

And partially is just based off

reading about the regulatory nightmare that is prediction markets and crypto.

And partially is the usability concerns with crypto.

But basically,

we all like in the month of December, we came up with the original idea.

We applied and received the ACX grant from Scott Alexander.

And we timed it such that right when the grant announcement came out, we had a working prototype of our prediction market system ready to go.

And then we were able to onboard a bunch of users from the ACX community immediately, which formed the base of our platform.

And since then, we've been growing and

responding to user concerns and improving uh improving our site to be ever more usable i i know you guys use something called a dynamic pair of mutual uh betting system i you know i i looked into the paper i i think i understood like maybe a quarter of it um so is uh

what was it like a experience uh of learning as you went or is this something you guys are already familiar with no definite definitely the former you know we we had heard i had heard of uniswap and some other mechanisms i had heard of like hanson's log market scoring rule and some other things, but I didn't actually delve into the details until quite recently.

Originally, we actually came up with the idea for dynamic paramutual by ourselves, thinking about it from first principles.

And then we later, I went back through the literature and read a bunch of papers and realized that it was called dynamic paramutual and found a more elegant implementation.

of a dynamic paramutual system based, you know, based on a quadratic cost function

that I hadn't considered previously.

Yeah, you'll have to talk me through it over dinner next time.

Yeah, so you mentioned that you are hiring.

Maybe

there are some people in my audience who might be interested.

So you want to talk about what kinds of roles you're interested in hiring for,

other kinds of things that might be involved in recruiting?

Sure, yeah, yeah.

So we, right now, we're looking to onboard a few people to our team.

We're looking for full stack developers who preferably have front end, a lot of front end and potentially React experience.

We're looking for a community manager that would be someone to help us manage our Discord, help write blog posts, help with our sub-stack, help reach out to people on social media and organize online events.

Someone with a previous background in doing this at a startup would be great, but we're open to people from other backgrounds as well.

And then we're

then looking for a head of growth or someone who has

experience

scaling up an early to mid-stage startup.

We're looking for

someone

who's helped take the company from

to

$1 to $10 million annual recurring revenue or around 50,000 monthly active users, something, somewhere in that neighborhood.

But yeah, if you are interested in prediction markets and Manifold in particular, I encourage you to reach out to us.

You can either

or email us at jobs at manifold.markets or me personally, Stephen at manifold.markets.

Excellent, excellent.

And any other topics involved with prediction markets or manifold that we have not discussed yet that you would like you, you know, you want to touch on?

I guess they're

one of the things that we've seen from launching this site is that users have come up with all sorts of like exotic ways to use prediction markets that we hadn't previously considered.

So part of that, or like prediction markets, obviously can be used on, you know, predicting the future, basic yes or no questions.

But some exotic things you can do are like getting users to help like research topics for you.

You know, do you can create a market on phrase these types of things in a market-based way, and then people can propose certain answers, and other users can bet on them.

That's an interesting feature of our site.

People have hacked our platform to do things like create lotteries, to play games.

We did Manifold Plays Wordle, where we created a series of prediction markets on which word we should guess next.

You know, people, yeah, they're just like all sorts of other things, non-prediction type things you can do with

this market mechanism, which are really cool.

That is an interesting idea.

I'm not sure how that was conducted, but like I could imagine, you know, researchers saying,

will my conclusion on a paper of this question be

X or Y?

And

then to move the market, somebody would not only have to bet, but also like maybe put in the comment section the data that makes them think it's X or Y, which can be the basis of the paper.

So you're basically getting research assistance.

Yeah, that is very interesting.

Oh, yeah.

Yeah.

I would say

relatedly, one of the

new types of markets we've introduced is this concept of a free response market.

So in addition to a yes or no market where you're just betting on something will happen, we have this idea of a free response market where you ask a broad open-ended question and people can submit an answer.

And when they're submitting an answer, they're also placing a bet on that answer and other users can

bid up

different answers that the market creator

will then choose.

And that really opens up the

space of possibilities towards allowing a much

wider array of questions.

Stephen, thanks so much for coming on the podcast.

And yeah, so that's manifold.markets, right?

Any other places or links that people should be aware of?

I think that's the the big one.

Manifold.markets.

You can join right now, and we'll give you $1,000 Manifold dollars to bet on any market you like or create your own.

Excellent.

Thanks so much, Stephen.

All right.

Thank you.