The Perfect Information Economy
What if we had Etherscan for every aspect of every business?
“The press acts like information's a dirty word. Everyone has access to the information. We just know how to analyze it better.” - Bobby Axelrod, Billions
When I started writing Charterless, I thought it would be hard to get a good handle on these new DAOs – I had a limited network since I was new to the space.
But the beauty of Web3, I soon discovered, was its legibility.
If I wanted to understand the rise of a new, hot project and which influencers were pumping it, I could see the entire transaction history on Etherscan or track user adoption on an open-community dashboard.
If I wanted to understand the major debates inside a new organization, I could read their Discord or their debates on Discourse.
If I wanted to understand a contentious issue, I could see how their members voted on Snapshot.
If I wanted to know who the key players were, I could find them on Twitter or Discord and DM them.
Just by having access to the internet, I had the keys to the whole kingdom.
It’s hard to imagine a similar level of access for stealth startups or even large publicly traded corporations. Even on earnings calls, well-credentialed Wall Street analysts have limited access to roadmaps, public plans or the data underlying top-line numbers.
If there’s something powerful about blockchain it can be found in the promise of this openness. Open data + open community + open planning compounded + open source software = a positive sum economy. #WAGMI, indeed.
And yet, the on chain remains rife with accusations of nepotism, insider trading, insider dealing, and gatekeeping. So what gives? Has the vision failed or are we still not getting the right information?
My hunch is that we’re still not getting the right information. But it’s not just a problem of what data is available on chain – it’s about what we’re doing with that information. Blockchain currently provides unprecedented access to financial reporting. But it provides little direct signal on the actual work that that capital enables.
(Insert Web3 skeptic joke about how there’s no actual work being done…)
This means that Web3 is financially open, but operationally closed. It’s easy to know who is trading which token. It’s easy to know the result after a vote happens. But it’s far harder to get involved and participate in building the digital economy.
That’s a problem for Web3 because its theoretical promise is to harness the collective wisdom of the open internet. And that’s a problem for builders because, it turns out, economic outcomes are just as much a function of an inequality in information as they are an inequality of capital or talent.
Where does that execution information live today?
It is tightly held by the world’s legacy behemoths.
Facebook and Google control a digital ads duopoly because they maintain the world’s most comprehensive information on our desires. The use of that information is available to users for a fee.
Bloomberg does the same for stock markets. If you want a terminal, you can fork over $25,000.
Or, if you’re in the B2B game and want information on where to look for leads you can turn to LinkedIn or ZoomInfo for a few hundred or thousand dollars per seat.
If you want the best information, you have to pay top dollar.
Economists make a lot of simplifying assumptions on their way to concluding that markets are the best system for managing an economy. But one that’s particularly important is that everyone in the market has perfect information on what they want, what’s available to buy and what it should cost. Asymmetries in information cause frictions that keep the economy from operating well.
Imagine how much easier your job in R&D would be if you had access to data on your customers’ habits and needs. Imagine how much easier your job in sales would be if you knew what your customers were already buying and what their goals were.
So what if we could transcend that information gap? What if a combination of blockchain’s open information and AI’s ability to sift through it for signals could provide us with a truly perfect, open market free of information frictions?
The Promise of Perfect Information
Hiring Help
I worked with some of the smartest people I have ever met at Facebook. I also worked with some real lemons. These two groups had shockingly similar resumes. They both could perform reasonably well in interviews. The company invested a lot into recruiting and evaluating its practices – and yet, it was almost impossible to actually get reliable information on who would be successful and who would fail in their role.
Let’s imagine I’m running a firm. How can I decide who I should hire and how much I should pay them? I create a process, hire some people, then fire the ones that don’t work out.
But this is a pretty expensive way to vet talent. It essentially introduces a tax on my hiring since I need to bake in a certain expectation of failure in any new hire. (Worth mentioning that I could also hire someone surprisingly great. That would be great for me! But then I would likely be underpaying them unless I decide to be generous with bonuses…)
And since this information gap increases the price of acquiring the talent, I am likely to buy less of it. Put another way: I will hire less people. And that’s what economists find.
This is, fundamentally, a problem that the signals we use for hiring – school attended, companies worked for, selected references, performance in a 30 minutes interview – are poor proxies for the work to be done. So what if, instead of looking at someone’s LinkedIn, we could actually look directly at their contributions?
With on-chain code and Github, we can see who contributed directly to projects, how they contributed and what the eventual impact of their work was. Increasingly, this is why open source contributions are a pathway to work for coders. By lowering the cost to assess candidates, perfect information makes labor markets more effective.
Pricing and Expanding Trade
But it’s not just labor markets!
Better information leads to more trade of goods and services. And this has been true from the telegraph to the internet.
In 1886, telegraph wires connected to the New York and London cotton markets for the first time. Up until then, prices between the two markets would fluctuate widely, according to data assembled by Claudia Steinwender. After the telegraph connected the markets, prices equalized across the American and British markets.
This reduced the opportunity for arbitrage, but it also gave merchants more confidence in their trades. The result of better information was better trade. Steinwender finds that the overall volume of trade increased by 6% thanks to more trustworthy price signals.
Not bad for sending dots and dashes under the ocean.
And the internet does much the same. A 2011 study by McKinsey looked at the power of connecting small businesses in developing countries to the internet. What they found was that access to list their goods on global markets and receive purchase orders directly led them to double exports. That had a profound effect – businesses connected to the internet grew at twice the speed of their competitors.
So imagine if there were a global market for goods and services, complete with reputation mechanisms, where companies could list wares and compete with any manufacturer worldwide. Imagine that all of that data – including sales – were available to every firm, every seller, every person in the world.
The closest we have today is Amazon. And Amazon is great, but … well… sellers are less sanguine about it. Because Amazon owns the platform, they have the best data about what is selling and will often undercut their own sellers or create copycat products.
There’s nothing wrong with competition. But when only one company has perfect data, no other company can hope to compete with them.
Lead Discovery
Or, consider the case of ZoomInfo and LinkedIn Sales Navigator.
Both of these products command over ~$1B in annual revenue by augmenting publicly available data to help connect sellers with firms that will buy their goods.
Imagine instead if there were an open database of officers and purchasers at various companies complete with a set of open RFPs. That would enable competitors to bid on pretty much any contract and build relationships with any buyer.
It would enable firms to find new clients, and clients to find new useful products and services. By eliminating the cost of finding customers, open ledgers can make the economy operate far more efficiently - and put more money/value in each of our pockets.
The Perils of Perfect Information
Unfortunately, perfect information is not a cure-all.
To begin with, there’s the privacy implications. Most of us are generally uneasy about large corporations like Google or Facebook having detailed records of our lives. So now imagine if anyone could search your entire work and purchase history? Gross.
There are steps we could take to limit the damages. There are privacy protecting “mixers” that allow us to send transactions privately when we need to – like an incognito browser for our wallet (though, the current controversy over Tornado Cash makes that defense problematic). There’s also the option of using aliases for our online entities – this is why so many folks in the crypto community operate behind cartoon avatars.
But perhaps the best solution will be the widespread adoption of Zero Knowledge Proofs. This technology allows private transactions on public blockchains. It is likely we will enter a future where many of our personal transactions are private while our economic transactions – especially those made by public firms – are publicly reported on-chain.
But more troubling than privacy implications are the fraud implications.
In a 2018 paper, Benedikt Notheisen and Christof Weinhardt argued that while, in the short term, perfect information leads to better trade, in the long-run it becomes another vector that bad actors can exploit. As they show in their model, in a truly open economy, bad actors learn the signals that good actors watch to make their decisions. They learn to mimic these quality signals, and then make it even harder to catch them.
Private information on assessment criteria, it turns out, limits the ability of bad actors to deceive.
And this brings us back to our good friend, Sam Bankman-Fried. SBF was able to watch the cryptomarkets play out. He knew why typical customers didn’t trust the first generation of crypto-barons.
They were too ideological, they were too hostile to regulators, they spoke too much about shaking up the world order, they dressed and drove around ostentatiously while giving nothing to charity. So Sam invented a more compelling character. SBF was an ideological “effective altruist”, he came from the right schools and family, he worked credulously with regulators. He was the trustworthy player in a game of thieves.
And it worked. To the tune of 30-some-billion dollars.
Because Sam understood that the evaluation criteria of his audience was not about what was going on in his books – it was about the character that he created. And this system worked.
Which brings us to an important warning about perfect information – it’s always an illusion. We simply don’t have the attention to look at all the data or the ability to capture every actor’s private intent. This should remind us, even in the face of overwhelming data, to stay humble about our ability to discern the truth.
Perhaps the best thing we can say about open data is that – like a bug in open source software – enough eyes on enough types of data will make any threat shallow. We can do more to make a dark world legible, but safety – safety is always an illusion.