Escrow is a perfect case study for trust.
We use escrow in online trading because there’s no reason to trust a stranger that can get away with our money or goods.
But what is the reason we trust strangers in real life? All the minor daily interactions of buying bread, going about our errands, or even in-person trading unfold relatively frictionlessly in civilized contexts.
The reason is just that: in civilized contexts people can be held accountable for their actions. We can either directly oppose them, or report them, or spread the word about their corruption, effectively damaging their reputation. In civilized contexts, actions have consequences.
Real life is frictionless, because it depends on this kind of structural trust. It doesn’t require people to be good, it just requires people to be self-interested. People are discouraged to cheat or steal, because it’s not in their best self-interest to do it.
In simple terms, the expected gain from cheating is much less than the expected loss:
When we’re dealing with a complete stranger, we can place trust in that structure of self-interestedness. The civilized world creates the contexts in which this equation is more often true than not.
In this essay I’ll show how Bitcoin’s hard signals make it possible to recreate this accountability structure online.
I’ll show how a frictionless P2P trading system can exist without escrow. People can choose to trade with those that have put real skin-in-the-game and can be held accountable for their actions.
How a Game of Hard Signals Creates an Accountability Structure
In How Bitcoin Fixes the Internet, I introduced the concept of hard signals: signals backed with pubkeys and real cost in terms of provable Bitcoin burn.
In the game of easy signals where accounts are cheap to create and signals cost almost nothing, the gain from cheating is much more than the potential loss, because the scammer has nothing to lose.
Because one has nothing to lose, the equation in most online contexts incentivizes cheating:
The hard signal game flips that equation around by imposing real costs and consequences. Chronicle is the protocol that implements this game. To play the game, a person first has to put real skin-in-the-game: either they use a public key that has a credible history of activity, or they burn an adequate amount of Bitcoin to back their pubkey. This proves they have something to lose in case other people oppose their pubkey.
When a person actually has something to lose, the equation to cheat can become:
Now, the factors of this equation depend on the context: how much a person can gain from cheating depends on the value of the trade, and how much they can lose is proportional to their reputation.
In the real world we intuitively estimate the reputation based on the context: a disheveled person in a shady neighborhood probably has less to lose by cheating us in a trade.
In Chronicle where the pubkey’s reputation can be computed from the public record, it’s possible predict the L_cheat accurately, and know whether we’re entering a context where the pubkey can gain more from cheating than lose from it.
A new pubkey that has no history of credible activity has nothing to lose by cheating. So even if the trade value is very low, they stand more to gain by cheating. If one chooses to trade with a new pubkey that has nothing to lose, they are naively placing trust in a stranger.
A pubkey that has been around for years and has a record of credible and useful activity can lose the reputation that among other things allows them to trade with other high-reputation actors. However, if the value of the trade is very high and exceeds the value of reputation, then the equation is tilted toward cheating, and we’re again naively placing trust in a stranger.
So if we know the value of the trade and the value of the reputation, we can choose those contexts or traders that give us a reasonable basis for trust, where honest dealing is more profitable than a dishonest one.
Trust is simply our anticipation of whether the outcome will turn out to be good, or of positive value:
And that depends on the context. You may trust your 10-year-old kid in a lot of contexts, but you won’t trust them to drive your car, because that’ll probably result in a negative value outcome. Similarly, if we know the value of the trade and the value of people’s reputation, we can step into the right contexts where the future outcome will likely be positive.
P2P Trading Without Escrow
Using Chronicle’s accountability structure, we can imagine reputation-based peer-to-peer trading without escrow and its friction, fees, and third-party trust.
Chronicle is a general record of who backed what or whom, and at what cost in terms of how much Bitcoin they’ve given up. A user can back their pubkey, domain name, email address, and other subjects they control, to show they have taken responsibility for the online activity they conduct with those subjects.
On a P2P trading platform, traders can advertise their offers and conduct trades under their chosen pubkeys. Other users can compute their reputation from Chronicle’s public record, and enter into trades they feel comfortable with.
If a new user were to bootstrap their pubkey reputation from scratch, they can back their pubkey by burning a specific amount of Bitcoin. If Bob burns 100k sats (approx $100), that puts at least that much skin-in-the-game.
[”chronicle:pubkey”, bob_pub, 100000000, bob_pub, ts, sig] The fact that Bob has $100 to lose means that other traders will have a reasonable basis for entering into trades with less than $100 value. Some may be comfortable with only a $10 trade, but this depends on each trader’s risk tolerance. The point is, the higher the pubkey’s initial burn, the larger the trading pool available to it.
(It may seem inefficient to put down $100 worth of Bitcoin to conduct $10 trades, but Chronicle is a general protocol, and a user with years of online activity might have built high enough reputation to conduct trades without a large initial burn.)
Now, if they cheat, the victim (Alice) can publicly oppose Bob’s pubkey by burning the effective amount of Bitcoin that would diminish the value of his reputation more than the value he gained from cheating.
[ “chronicle:pubkey”, bob_pub, -x, alice_pub, ts, alice_sig]The exact amount ‘x’ depends on Alice’s reputation. If the trade value was $10, and Alice’s reputation is very high, she can burn $1 worth of Bitcoin to diminish Bob’s reputation by the entire $100 of value he had put into it. If Alice is likewise a new pubkey backed by the same amount as Bob’s, she would have to put in at least $10 to get even with Bob. She would be at a temporary loss, but this would simultaneously improve the safety of the entire network, and potentially increase her future reputation.
On the other hand, if Bob is consistently reliable, and has built a good relationship, Alice can choose to endorse his pubkey:
[ “chronicle:pubkey”, bob_pub, x, alice_pub, ts, alice_sig]This public backing means Alice becomes accountable for Bob’s pubkey’s future actions, because she has effectively distributed part of her credibility to him1. By this endorsement, she decides to take on the consequences of his future activity, both good and bad. The larger her endorsement, the greater the share of her total credibility she has lent, and the more accountable she is to the consequences.
I call this recursive accountability. If a new pubkey with zero reputation was boosted by a credible trader, which allows that pubkey to commit theft, the actor most accountable for the transgression is the one that allowed it to happen. Because the record is public, the pubkey’s reputation can be traced back to the credible pubkey that endorsed it.
When people can be held accountable for their endorsements, they are given sparingly. The way influence is distributed is mathematically transparent and precisely known to everyone. When you know exactly who’s pulling the strings, there’s no concept of a frontman.
Now, this accountability structure doesn’t prevent theft. It only allows people to enter into the contexts where theft is unlikely because it is irrational. By selecting the context in which G_cheat is sufficiently lower than L_cheat, the individual can essentially avoid all possibility of being cheated:
If one willingly conducts a high-value trade with a low-reputation pubkey, then one is inviting theft. It’s like going into a shady neighborhood with a Rolex and pockets full cash.
What this system does is make it transparent which online neighborhoods are safe and which aren’t, so one can avoid danger by choosing civilized contexts instead. Those civilized contexts have less to do the intrinsic goodness of people walking those streets, and more to do with the accountability structure that incentivizes civilized behavior.
How This Solves Trust More Generally
Escrow is a good case study for trust, because the value of the trade is explicit and can be compared to the value of the reputation2, but this principle can be applied wherever trust is needed.
Whether we trust this email sender, this online store, this payment link, this phone number, this social media post decides whether we open the email, enter our credit card details, accept the call, or trust the content of the post.
Without a public record that proves that the person behind these subjects has actual skin-in-the-game, we have no reasonable basis for trust.
With one we can choose the right contexts, or more accurately, we can configure our email clients, web browsers, and smartphones to expose us to content backed by people with a certain level of reputation.
By adjusting the threshold based on our personal risk tolerance, we can step into the contexts where we have a reasonable basis for trust.
Thanks to Curtis Heinen for feedback.
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Chronicle is under active R&D
Chronicle has a working prototype, a whitepaper, a protocol specification, and a registry of events. Hard signals are a new primitive that can reshape the internet and the way we interact online. We’re developing new UI/UX patterns, reputation algorithms, simulations, mathematical models, and small-scale experiments to understand and refine the system before launch.
If you want to get involved in early beta experiments or work on Chronicle, let me know. You can leave a comment or get in touch through our website.
When Bob receives backing from a credible public key, the value of his reputation increases not just by the burned amount, but by the factor of Alice’s credibility, which depends on the recursive structure of endorsements she received from others, and those received from others.
The monetary value of reputation can be calculated from the total amount of capital in the entire Chronicle record and the share of the actor’s reputation in the network, which depends on the recursive structure of the graph. But the ultimate value of reputation is ineffable and incalculable as it depends on what actions and possibilities that reputation affords (e.g., possibility to trade with other people without escrow.)