Prediction markets are about forecasting outcomes. But spend enough time creating markets, trading, arguing in the comments, watching the probabilities move, and tracking outcomes, and you begin to develop habits that have little to do with the markets themselves. You’ll become more deliberate about questions, evidence, certainty, disagreement, and the nature of information.
The most useful thing about prediction markets may not be learning to anticipate future outcomes, but learning to think more carefully about the present and notice how you interpret the world.
This is a long one; you can cut straight to the punch if you must…
Asking better questions
Curiosity becomes operational
I guess there are totally incurious people in the world, but I haven’t met many of them, and I doubt they’re three paragraphs into this article, so forgive me for speaking in absolutes here:
We’re all curious about the world! To varying degrees, we all have questions, and some of us wonder not only what is or will be, but what others think of that, too.
But being curious isn’t the same as knowing what it is you’re asking. Sound silly? Trust me, you’d be surprised how common it is to not really know what you’re asking until you’re forced to write resolution criteria for it.
Here’s a little example: Will a new Lyme disease vaccine be available by the end of 2027?
Seems like a simple enough question, right? In face-to-face conversations, it’s probably sufficient. After all, if you’re having a discussion about it, you’ll learn along the way what the person you’re chatting with counts as “available.”
But what happens when you need to write clear and objective criteria, and you can’t just go with the flow when people come along with different ideas? Chatting about it with the guy sitting next to you at your airport gate when you see a poorly captioned CNN segment on a muted TV is much different than needing a reliable framework for what qualifies to resolve a market around the question you mean to ask.
Here, “available” needs to be much more concrete.
Do you mean
Approved by the FDA?
Approved anywhere? Or in the country where you live?
Actually launched commercially?
Prescribed outside of a clinical trial?
Stocked somewhere and technically obtainable by a patient?
Routinely available through ordinary doctors’ offices or pharmacies?
Covered by insurance?
Featured in an RFK Jr. podcast episode about why it’s evil?
What happens if it’s technically available, but so highly constrained that it won’t be broadly accessible until much later? Will it count if it’s only available to certain ages or risk groups? Interrogating the question you initially asked may reveal that it’s not actually the question you want answered.
Of course, even if you try to be explicit, you may end up with some gaps. Thankfully(?), the comment section will often let you know what you’re missing.
Language is less obvious than you might think
There’s what you know, what you know you don’t know, and what you’re absolutely sure you know until you meet someone who’s equally certain of a wildly different interpretation.
That third category has been a rite of passage for many people who start writing markets on Manifold.
Let’s try one of my favourite semantic examples:
If I ask you, “Will Taylor Swift be photographed with Pope Leo XIV by January 1, 2027?” do you think I mean:
Will Taylor Swift be photographed with Pope Leo XIV on or before December 31, 2026 at 23:59?
or
Will Taylor Swift be photographed with Pope Leo XIV on or before January 1, 2027 at 23:59?
If you chose the former, congratulations! You’re right! Here’s an example of a thing you know!
Except, if you went with the latter, you’re also right! Oh no! It’s a trap!
I’m on Team December 31st, mostly because I’ve considered “by” to be synonymous with “before,” and it didn’t occur to me that it could mean anything other than that until I started writing questions or betting in other people’s markets.
This is easily the most common mix-up because, no matter whether one is more typical in common parlance, both options are defensible interpretations. What an annoyance of the English language.
There’s nothing that will teach you about the intricacies of language like people whose money (or mana) is riding, in part, on your ability to be clear in your question and criteria.
Theory of mind
So, what does it take to be clear in your question-writing? I could argue a great many things, like subject-matter knowledge, a firm grasp on what exactly you’re asking, and a solid lexicon for putting those ideas down into words. And those are all crucial skills, but the S-tier skill secret is theory of mind.
Now, this is one of my (many) favourite soapboxes, but that’s a rant valuable monologue better saved for another time and another Substack. Instead, I just want to highlight how far ahead you often are in both writing and predicting when you develop a good theory of mind.
Communication is less about what you intend to say than what you want another person to receive. The more time you spend in prediction markets (especially user-created ones!), the more you build a model of how people see and communicate things. As with the above on the silliness of language, you start to anticipate grey areas by putting your default aside and auditing from someone else’s point of view.
Instead of assuming a counterparty or market creator is a fool, you can put yourself in their mindset and ask what interpretation would make their question or bet make sense.
Once you build a habit of interrogating your own questions, you begin hearing other people’s questions differently, too. You become less inclined to answer at first read, and more inclined to ask what information the person is trying to get at. What are they trying to determine?
That habit follows you out of the market, and you begin listening not just for the literal question but for the thing the person is trying to point to.
Learning how certain you actually are
Certainty becomes proportional
In casual conversation, we tend to speak in binaries:
I think this will happen.
I don’t think it will.
Or,
There’s no way in hell this doesn’t happen.
You’re out of your mind to think that’s remotely possible.
Wanna shake on it?
Maybe you make a handshake bet on who buys the next round, but ultimately, this structure demands there’s a winner and a loser.
A market asks a different question: How sure are you?
Proportionality matters. You may land on a market asking a question that you believe will resolve Yes, but how strongly do you believe it? It’s sitting at 55%; do you think it’s actually closer to 70%? Or 30%?
You start noticing how often “I think [xyz]” is doing a lot of work for beliefs held at very different levels of confidence.
A belief at 55% is fundamentally different than a belief at 90%, and participating repeatedly teaches you how to notice that difference internally. It changes certainty from something you feel into something you have to inspect.
Having something at stake changes your relationship to your own conviction
There are real-money sites out there, of course, and if you’re reading this Substack (and you’ve read this far), I’m going to keep moving along because I trust you know who they are. Manifold runs on play money, but that doesn’t mean you don’t have skin in the game.
Even with play money, there is a consequence. You have a visible position. You have a track record. Other people can see what you believed, and how strongly you believed it. If you burn through it, you have less mana to play with.
Suddenly, you have to ask:
How much of my belief is based on information?
How much is intuition?
How much confidence does the evidence actually justify?
What evidence would move me from 60% to 80%?
What evidence would make me substantially less confident?
tl;dr: Am I going on vibes?
Prediction markets don’t only teach you to assign confidence. They train you to develop a relationship with your confidence, and notice what actually moves it.
Markets give you feedback about whether your preferred way of knowing actually works
You may believe you’re good at going on vibes, spotting political shifts, reading people, parsing scientific developments, anticipating outcomes, etc. And maybe you are! Maybe you’re even unusually good at it! But, how confident are you? how do you know?
I’m not saying there are some memory biases at play here, but I’m not not saying it. Without a ledger, it’s easy to kid yourself a bit, and after all, why not? It’s good to feel good about yourself!
Life may not come with a formal audit trail, but markets leave receipts.
Over time, you build a record of not only which calls were right, but how confident you were when you made them. Maybe your political instincts actually are unusually good! Maybe the “vibes” you were getting right are just more memorable than the ones you misinterpreted.
You’re not only on record to yourself, but in front of your counterparties, and you may find the evidence humbling. You’re reality-testing your own self-conception; do with that knowledge what you will.
Learning your relationship to risk
Markets reveal that risk tolerance isn’t necessarily a single personality trait
Over the years I’ve known many, many people who think I’m either very brave, very irresponsible, or some mix of the two. Within about three months, I went from making a joke about leaving the US for Australia to quitting my job, selling all of my stuff, booking a hotel for 3 nights, and flying one-way to a country I didn’t know anything about with two suitcases in hand. I don’t think I had time to think of it as brave, but I just assumed I’d figure it out.
Since then, I’ve been to dozens of countries on one-way tickets, traveled extensively as a solo female without a plan, moved to a couple of other countries, quit my job to backpack until I ran out of money more than once (I call these chapters “practice retirement”) and, perhaps most bravely, eaten street food all across SE Asia and India.
And yet, when I joined Manifold, I was fascinated to see how conservative I was with my bets. I was making little baby bets; I was anxious about outcomes; I found it particularly unsettling to lose mana. I suppose I’d been reserving all of my risk-aversion for the markets.
Prediction markets can highlight that “risk-taker” and “risk-averse” aren’t particularly useful global descriptions.
People have very different tolerances for:
financial risk
career risk
uncertainty
reputational risk
social risk
physical risk
and markets can bring those differences to light because they repeatedly force you to decide not only what you believe, but how much you’re willing to put on the line for it.
Markets create material for self-audit
Your trading history not only provides valuable information on how often you were right, but also produces data about your own decision-making. Over time, you can start asking:
Am I chronically too conservative?
Do I only make bold bets in domains where I feel personally knowledgeable?
Do I hesitate even when I have an informal advantage?
Am I willing to take low-probability/high-upside positions?
When I’m wrong, is it because my evidence is bad, my probability estimate was bad, or my willingness to act on it was bad?
Over time, your portfolio not only gives you information about the world, but information about yourself as an instrument to interpret the world. That kind of self-knowledge is useful; you’re learning more about how you respond to uncertainty, loss, conviction, and risk. You wind up with a distinction between what you believe and what you’re willing to do with it.
Separating prediction from preference
A bet is not an endorsement
Okay, finally. Now’s my chance to Take Back a pithy statement often used in disingenuous ways:
Facts (and markets) don’t care about your feelings!
(If that saying doesn’t sound familiar, I pat you on the head, my sweet summer child. Don’t worry about it, just know I’m out here fighting the good fight.)
This is one of those things that becomes obvious once you’ve been around prediction markets for a while, but it can be surprisingly unintuitive. Someone buys Yes on an outcome you find awful, and the novice instinct can be to read that as support for the outcome rather than a prediction about reality. Or to be disgusted that a market even exists for what you consider a distasteful question.
But prediction markets aren’t a chance to vote with your wallet; they’re a mechanism for pointing to the truth.
What do I think will happen?
is not the same as
What do I want to happen?
And,
What do I think is true?
is not the same as
What would I prefer to be true?
If you can’t separate your desires from reality, you’re going to have to be comfortable just doing a token victory lap for the cause, and you might as well just leave your purse on a park bench while you do it.
Markets punish motivated reasoning in a very direct way
People naturally tend toward evidence that favours their desired outcome. Hell, there’s an entire Catalogue of Biases to explain this tendency through a ton of different lenses. You may think you can be pretty objective, but prediction markets have a way of making your biases more visible.
You overweight ambiguous information in your preferred direction, filling in the gaps yourself while discounting unpleasant evidence. You treat a prediction as a moral statement, and your aversion to aligning with (or profit-seeking from) the idea causes you to burn currency in protest without even noticing.
Once you stake something on the outcome, even play money and your reputation, wishful thinking becomes more expensive. Part of the training is learning to say “I hate this outcome, and I think it’s 70% likely.”
The ability to separate your values from your beliefs is an important civic/intellectual skill, but once you’re holding both in your soft little hands, where do you go from here?
Well, to start, you may find yourself watching the Super Bowl or the Oscars and feeling really awkwardly conflicted in a way that feels almost darkly comedic.
More usefully, once you stop allowing “I want this to be true” to serve as evidence, you have to get more serious about what does, and who you trust to provide it.
Learning whom and what to trust
Prediction markets teach source discernment rather than source allegiance
Author Michael Crichton coined the term Gell-Mann amnesia, noting that we often notice how badly media gets subjects we know about wrong, then turn the page and resume trusting its reporting on subjects we know less about. If we’re this inconsistent about how much skepticism is applied to sources we’ve already read, what might that say about the ones we’ve written off entirely?
Forecasting can teach you to evaluate a source on dimensions that are separable from “Do I like this person?” or “Do I agree with their worldview?” Good forecasting rewards a willingness to use information from a variety of sources, even those you may not particularly like.
Someone may have opinions you think are terrible and nevertheless be:
unusually careful with factual claims,
very well-connected in a particular domain,
good at distinguishing what they know from what they suspect,
willing to report inconvenient facts,
capable of separating factual information from their own editorialising,
or known to possess an excellent track record.
On the other hand (and most people don’t like to reckon with this), someone whose worldview resembles yours may be a terrible source of factual information.
The skill is not to simply “be skeptical.” It’s closer to learning to disaggregate trust. You can distrust someone’s politics and trust their reporting on a narrow subject. You can admire someone intellectually and still recognise that they’re consistently overconfident. You can dislike a publication and still find one of its reporters extremely reliable on a particular beat.
Credibility becomes granular rather than tribal.
Learning from disagreement
Disagreement contains information
It’s painfully common (in part for the reasons above) to dismiss a person’s opinion as not credible, a tendency that grows more stubborn the more firmly someone holds their own conviction. But, even if you’re right, that disagreement may contain information.
Disagreeing with other traders gives you a chance to investigate how someone else arrived at a different conclusion, and perhaps discover information or ways of interpreting the world that you hadn't considered.
If someone disagrees with you, consider exploring things like:
What does this person know that I don’t?
What assumptions or model of the world might produce their estimation?
Are they weighting the same evidence differently?
Are we even answering the same question?
Is there something in their worldview worth learning from, even if they’re wrong about this particular outcome?
Sometimes people are just simply wrong. Sometimes they haven’t yet learned the difference between their preferences and their beliefs. Sometimes they just have money to burn. Sometimes they’re mildly illiterate.
The point is, you don’t have to agree with someone to potentially extract valuable information from them. It may not be immediately relevant to the current market, but it may be useful later.
And sometimes their trading history gives you a reason to look twice. Does this smart, typically successful person seem to be taking a dumb position on this market as my counterparty?
Curious.
Understanding vs. being understood
I spent years dating a guy who couldn’t argue. It was incredibly frustrating, not because I wanted to argue, but because we were already disagreeing and we’d constantly circle the same points.
No, I don’t mention it to suggest we (or you, dear reader) should operationalise our relationships with prediction markets… but you could do that on Manifold, if you wanted to. Just for the record.
Instead, I mention it because it taught me something that markets have reinforced to me years later: if you’re not getting anywhere, you may need to try a shift from Trying to Be Understood to Trying to Understand. I tried to suggest this a number of times when we were on neutral, not-currently-bickering ground in hopes of navigating friction in more fruitful ways, but alas.
I’m the last one to argue that this is easy (in theory or practice), as there are a lot of factors that affect a person’s ability to zoom out on something close to their heart. Especially once those pesky feelings flood in. Having something at stake can encourage you to examine your thinking more carefully, but when what's at stake is close to your heart, it can become much harder to step outside your own point of view.
It’s incredibly common in interpersonal disagreements for two people to spend the entire conversation trying to get the other person to finally grasp their point. The more one person feels misunderstood, the more they double down on getting the message across.
Guess what the other person does in this scenario?
They double down, too. Now you’ve got two people working very hard to be understood, and neither is making much progress toward understanding.
I've noticed the same instinct in forecasting debates. It's easy to become so occupied with explaining why your prediction is right that you stop investigating why someone else disagrees. Sometimes the more useful move is to notice that you're no longer asking questions and change how you're participating in the conversation.
Learning to follow reality over time
Markets create ongoing questions
Spending a lot of time in prediction markets comes part and parcel with spending more time paying attention to the news. If, that is, you want to have a leg to stand on in a variety of forecasts.
But it amounts to more than “I read more news,” because a prediction market creates a continuing question about reality. You don’t simply consume an article and move on. The market (or supplementary, adjacent, or follow-on markets) remains open, so new information has somewhere to go.
If you’re built like me, you’re incentivised to indulge all of those impulses to dive down rabbit holes.
This trains you to follow a path that looks something like
event → new evidence → revised probability → subsequent event → revised probability
rather than accumulating a loose collection of memorable headlines and cursed retweets.
You’re constructing a living record of local or global events while building a habit of integrating new evidence into an existing view.
Knowing the news isn’t the same as tracking reality over time
I don’t mean to call anyone out, but there are a lot of smart people who are up on events and still struggle to retain an accurate sense of sequence and context. Knowing an outcome can make it surprisingly difficult to remember how uncertain things looked while they were unfolding.
Even with an accumulated wealth of knowledge, your memory of
what happened,
in what order,
what was known at the time,
and which later developments changed the picture
doesn’t necessarily correspond to the actual sequence of events.
Prediction markets help you build a timeline of events, track outcomes, and in some cases, see how one development affects another. Over time, you build a record you can return to, and you’re less dependent on reconstructing the story after the fact based on the handful of headlines that happened to stick.
Following events this way also trains you to be more careful with hindsight, because it’s easy to forget just how uncertain things were in the moment. In fact, it’s so common, we’ve got a whole name for it, too.
tl; dr What’s in it for me?
Yeah, fair question! We covered a lot of ground here, so whether you’ve read all the way through or arrived here because it’s close to the comment box where you’d planned to tell me how long-winded I am, we’re here together nonetheless.
Spending time in prediction markets helps you develop useful skills that translate to more than just writing questions, predicting outcomes, and debating world events in comment sections. Or being profitable, building clout, that sort of thing.
You’re learning to more effectively:
formulate questions,
define outcomes,
weigh sources and parse information,
distinguish evidence from desire,
incorporate disagreement,
develop a theory of mind,
revise or update when the world changes,
and understand your confidence level in a result.
Some are intellectual habits, some are communication skills, some simply teach you more about how you process information and uncertainty. These also bleed into your interpersonal relationships: listening for what someone actually means, noticing when you’re talking past each other, not turning a disagreement into a character flaw, and getting more curious when someone arrives with another viewpoint.
Prediction markets aggregate information across people, but participating in them trains you to be a better aggregator of information yourself as well.