The way we interact with online media is changing. Amidst an increasing abundance of information, our culture and values are shifting in terms of where we place our scarce attention.

The media landscape is illustrative of this dynamic: legacy institutions and verifiable truth are waning while creators’ influence is rising alongside AI-generated content. The past election was a sign of what’s become of our new paradigm:

• Presidential candidates on podcast tours

• Campaign socials pumping out memes

• Polymarket hosting bets on the winner

It’s hard to say exactly where all this will lead but one thing is abundantly clear: everything’s a market. Online media, narrative, attention, capital, and truth are all converging behind one idea…

Crowds vs. Markets

Do you have a friend or acquaintance who hasn’t got a clue? Perhaps they’re addicted to TikTok and always talking about whatever new show they’re watching. You love ‘em, but they haven’t got a clue.

Say this friend were to one day voice a particularly egregious belief. Something along the lines of a ridiculous conspiracy or ignorant take that borders on harmful to say aloud.

You are quick to assume moral authority and chastise their obviously false rhetoric, yet your efforts are in vain. No matter what angle you attack from, you can’t get through to them. Maybe you can’t even agree on what certain words mean or what facts are. You grow tired from arguing and finally decide to accept defeat by ‘agreeing to disagree’.

Your friend has been lost to the supposed ‘wisdom’ of the crowds.

Modern social media platforms operate through black box algorithms that optimize for engagement signals from users. This model enables the spread of misinformation at no personal cost to the individuals sharing it— in fact, there's potentially more to gain in attention and validation.

The ‘wisdom of crowds’ concept holds that collective judgment converges on truth. But there's a fatal flaw in applying this to social media: crowds have no skin in the game. When sharing or promoting information carries no risk of personal loss, incentives for accuracy disappear.

The result is a divisive media landscape that perpetuates by design. Algorithms love controversy and division because it sells ads.

Markets Tell the Truth

When content flows freely on platforms where engagement determines visibility, crowds largely determine what rises to the collective consciousness. The crowds happen to be quite stupid and vulgar these days (thanks Elon), I don’t like half of what I see on my ‘For you’ page.

Markets, on the other hand, work because they're ruthlessly efficient over time. When participants must risk capital on their convictions, information quality improves dramatically. With properly aligned incentives, sufficient capital scale, and a heterogeneous makeup of individual actors, information markets can function similarly to financial ones.

Consider prediction markets like Polymarket, where participants bet real money on event outcomes. The prices reflect genuine probability assessments because being wrong has consequences.

Information is inherently valuable, the right piece of knowledge can change your life. When the supply of information is abundant and free, there is no objective consensus on quality, and value is bound to the amount of attention captured. The solution may lie in transforming how we allocate our attention through a new value system that leverages market mechanisms.

Polling vs. Prediction Markets

Last November, an anonymous Polymarket ‘whale’ known under the alias “Théo” made a reported $85M in profit from betting on Trump to win the 2024 election.

A trader by profession with an eye for arbitrage, he suspected mainstream polling to be underestimating Trump’s election odds for a third consecutive time. Following his hunch, he leveraged his fortune to conduct his own polling, asking one really good question: “Who is your neighbor is voting for?”

Théo understood what other pollsters couldn’t adequately account for: aligning with Trump’s controversial figure goes against people’s own social incentives. By reframing the question to remove the respondents’ personal stake in the answer, people were all too willing to throw their neighbors under the Trump bus.

Polymarket told a dramatically different story than mainstream media leading up to the election. While polls and ‘experts’ suggested a tight race with advantage to Harris, prediction markets consistently favored Trump. This wasn't noise or manipulation, it was a fundamental difference in information quality.

Prediction markets measure what people truly believe (as demonstrated by their willingness to bet), while polls capture what people are willing to say.

This polling failure provides a good parallel to our previously-introduced social media problem:

The long-term accuracy of prediction markets in forecasting presidential elections remains TBD. But their meteoric rise to relevance (over 3.3bn bet on 2024 election) is vindicative for now: when people must stake real value on information, the quality of that information improves dramatically.

Enter Zora

The meme “information wants to be free” is widely-known in the digital era, however the proposed dichotomy in the latter half of the quote has flown under the radar. And yet, that tension between the ease of distributing information and its potential value has not gone away.

The market for information/media is enormous. The largest big tech distributors have democratized the exchange of free information, ballooning to absurd valuations: Meta has a market cap of $1.65t, YouTube an estimated $500bn, TikTok an estimated $300bn. The value of the content created on these platforms is tangible, however most of it flows upstream into the pockets of the companies themselves.

Users of these platforms are willing participants in a privatized information exchange that is extractive of their time and attention. Creators add value to the system (for free) by creating content and attracting attention, yet that attention is then sold to the highest bidder (advertisers). This monolithic value capture is short-sighted and primed for disruption as new technologies enable new possibilities.

I recently came across Zora, a new consumer app that is attempting to solve this problem. It’s like Instagram and Tumblr had abandoned a baby in a casino.

The underlying concept is simple: every piece of content is tokenized. That pretty picture you double tap is also injecting a pre-set amount of capital into a meme coin (mine is set to ~10 cents). It’s free to participate if you’d like but a whole lot more fun with a little spare change involved.

Don’t get me wrong— I’m not big on crypto or a degenerate gambler by any means. My motivations are intrinsic and based in curiosity, yet I’m rewarded for them extrinsically. The app is admittedly a lot of fun to use and potentially make money as a byproduct.

Creators own actual stake in the content they share, curators can collect coins as patrons and show off their collection, while speculators can trade and ‘invest before viral’. The hope is that in achieving a critical mass of motivated users willing to stake money, robust markets could form around content, art, memes, ideas, etc. and benefit the collective.

The UX is still raw, I have no idea how the settlement layer works, and the odds of success are a complete moonshot. Widespread adoption would require feature parity with Instagram and a lot more things to go right for them bringing social media on-chain. What’s promising is the fact that the underlying value system cannot be vampirically-siphoned by big tech. And did I mention that it’s already fun as hell?

The opportunity presented by Zora is discussed at length in an article by @wagmialexander:

“I like to think that most of us building in this space are doing so because we believe in the technology's ability to deliver better products through the removal of value extractive intermediaries, enabling more value to flow to users and the broader commons.”

Jacob Horne, co-founder and CEO of Zora also appeared on the Dialectic podcast:

“Markets are a way to have signal in a world of truly infinite content.”

I’d encourage you to hear out Jacob’s thesis. I like Zora’s vision and their long-term direction. It remains to be seen whether they can continue to iterate and find ways to accelerate adoption in a crowded market for attention.

More than anything else, I’m rooting for this new media model because I’m curious: Will we like what we see in the markets? Do we really want the truth about our information age?