DAPPCON 2025: The Cirles Web of Trust: When it Works, When it Fails, and What to Do About it - Paul

Transcript

Amazing. Hi everybody. Very happy to be talking to you guys today. My name is uh Paul. I'm with the circles team and I want to talk to you about the circles web of trust. This is not an introductory level talk. Uh Martin yesterday gave a presentation on this. There's been several workshops. In fact, as I guess you all know, it's been hard to kind of evade us uh in this conference and over the last couple of weeks. Instead, this talk builds on the understanding, the basic understanding that we hopefully all have um about this protocol. So, let's just recall um what circles is about. Here are the the core three rules of circles. Everybody can can come and uh create an account. There's no

gatekeeping. And then as soon as you have an account, uh you're going to be enabled to create your own personal CSC token at a fixed rate of one circle an hour. And all the circle tokens that are being created by everybody suffer from uh a sort of constant evaporation uh which is called the demarrage at a rate of 7% per year. And on top of that we have uh the notion of trusting users trusting each other. That's just a relation that is sort of registered on chain. And by Alice trusting Bob, Alice is kind of communicating to the rest of the the the the network that she is willing to accept Bob's circles at face value. And so if we think about it, we

have one rule relating to money creation, one rule creating to relating to money destruction and then one rule relating to money flow. By which I mean uh if you sort of took a snapshot of all the balances, the third rule would kind of govern the dynamics of how these circles can then move about. And in this talk, I'm not going to be um caring at all about the first two rules. I'm only going to be interested in this in the third rule. And all these trust connections, they produce a trust graph. And people get really excited about the trust graph. We talk to them. We we ask people here, what do you like about circles? And we often hear uh that the trust graph is what they find most exciting. And I

think there's several reasons for that. One of them is that people just love graphs. Full stop. Um, one of them is that people really dig the idea of kind of curating and engineering their personal currency. And so, you know, projects like Trust Lines or Ripple Pay um, have, you know, always excited lot lots of people in the community. There's also this social and local nature of trusting. So circles is fully sort of breathing decentralization and sort of uh giving sovereignty to to the user. So of not just at the the techstack level but also clearly at at how the the protocol works and people get really excited to think about

secondary use cases, things they can do with this trust graph that go beyond um just the circle currency. Um but the trust graph also brings up questions. It brings up some questions. Um or kind of confusion. Um there's questions like why do we need the trust graph to begin with? And whom should I trust? Just in practice like somebody comes up with a QR code, should I scan it? Should I not scan it? What should be the criteria based on which I decide is the tri is the graph providing a proof of personhood? If so, how strong is that guarantee? And if not, what is it providing a proof of?

And I think we as a team or the community sort of we're also not yet quite decided. So there's conflicting advice floating around such as trust all accounts you think aren't bots or trust those who you think will provide the most value to the community. Trust the people you trust in real life or don't trust accounts by people that you believe might run a second account. So they all kind of pull in the same direction, but they target different underlying criteria. So this talk tries to sort of help answer these questions. It's just sort of my two cents on on these questions.

They don't represent necessarily the the the views of the circle team or kind of what we're going to be rolling out or whatever. It's just me thinking about them. But why I think it matters to kind of have this discussion and think about it is because a lack of alignment on these questions among the circles user base undermines trust in the protocol and hinder adoption. So if it seems like an arbitrary thing, everybody's just trusting based on different criteria, how can this become sort of the next big uh onchain uh money? And B, if we're really committed to thinking about secondary use cases, things that we can do with this trust graph, I think we need to be sort of confident in the properties of the graph and the value

proposition, right? So that if everybody's doing things based on different criteria, what is it? What is it that the trust graph is encoding? So the main points I kind of want to drive home over the next 15 minutes or so is that a what we prove depends on our collective trusting strategy. And that's kind of a truism. I mean, of course, that is true. But what I mean is that if what we're after is a proof of personhood, then depending on the collective accuracy of our beliefs and the personhood of others, we might achieve that. If our criterion is something other, another property that is sort of hidden that we want to provide proof of then again depending on the accuracy of our collective beliefs, we might do that. If all of us are doing

different things, then probably we're not really proving anything. The second point I want to drive home is that there are some good reasons in my view to kind of move beyond thinking of what we're doing with the web of trust approach in circles as providing just proof of personhood. And the third point is I want to quickly talk about how groups which are a new construct in circles v2 allow us to go beyond the web of trust approach. So let me start by addressing my view of the question why we have the web of trust and the trust graph in circles in the first place. So I think that within circles the web of trust is primarily a technical solution to a technical problem. Circles is an ambitious project and we kind of want to have the cake uh

and eat it. We want to have a currency that is universally accessible in the sense that everybody can create an account. It should be democrat the issuance should be democratized in the sense that all of these accounts can start participating in the money creation but we also want what I would call sound tokconomics and I know so this is a loaded term sound tokconomics I hear means something very modest by it I mean the rate at which a person should be able to produce circles should be one an hour not more but not less and so if you're willing to just take any or two of these it's relatively easy to see how how you how you can do it. Uh but getting all three of them under one hood is kind of difficult because of

this obvious civil attack that you you kind of open up for. Um and the web of trust is meant to uh address this issue. So when Martin for example gives this kind of advice, what he's getting at is that here's obviously an account that has on the media is anonymous. We don't know who they are. they have no form of sort of verification and they evidently have at least two um two accounts on metri that they're sort of mixing up right I mean so there's several red flags right there for why we think they are not using the protocol as as intended right so um now how does the web of trust approach help us address this problem in detail it helps me to think

of sort of construct a kind of a a toy model a mental model that I use to think about how we as a collective use our beliefs um about the personhood or the properties of other people to kind of uh produce a currency that is universally accessible uh issued dis democratizedly if that is a thing and and also has sound tokconomics. So let's take the example of an online community that wants to set up a currency with democratized issuance and universal access. And the community knows that it's somehow infiltrated by accounts that have some hidden property which for lack of creativity we're just going to call bad. This is bad accounts. But bad could also be a person. It could also be, you

know, people with, I don't know, well, things that you can't see like certain chromosome structures or something. And we're going to define the tokconomics of the currency that they're going to come up with as sound. If these accounts are somehow successfully oluded from the economy of this online community in thinking about what they should do, they come up with the toy rules of circles which are look which look as follows. First of all, give everybody some circles and they're all non-f fungeible tokens, right? Everybody gets circles. In the second step, each of the participants in the community gets to decide whom to trust based on some strategy. So, they have articulated the strategy and they decide, well, this is how I'm going to trust. And then third,

they're going to sample a random good exchange partner. So, this is this red arrow here. And so, this is how this sort of day looks or this round looks from the point of view of this one player. But now they all all all participate in this game. And the task is for the good accounts to come up with a collective strategy such that the economy among them is liquid but bad accounts are isolated. So we can now kind of formally evaluate the quality of a given strategy by you know liquidity which I'm going to take here as the average fraction of their circles that good users can spend right spend with the transaction partner that was chosen and adversarial exposure

which is how many of the how many circles can bad accounts pay good accounts. So we now have a mapping from every possible strategy to the quality of that strategy. And there's a simple optimal strategy which is well all accounts just trust each other and no none of them trust any of the bad accounts. That's that's the perfect uh strategy. Liquidity is 100% adversarial exposure is 0%. So far so good. The only catch is that to come up with that strategy you need to have known who's who in the first place. So that kind of begs the question right?

But people might not have full knowledge of this hidden property but they have informed beliefs. They might have interacted with them in the past. So um you know they might have applied sort of base rule or whatever and they might run around with some uh uh indication of whether uh a given account has that property or doesn't. And one possible strategy that they could kind of agree on is that each of them samples their trust as a function of their current beliefs and they update them accordingly. Right. So here we have these accounts kind of having sort of roughly correct beliefs and you can then show in this toy model that if there are islands of knowledge for every account this strategy will work well. So what do I

mean by islands of knowledge? I'm not going to tell you sort of I'm hiding sort of technical lingo here but so quite clearly the web of trust approach in this sense in this toy model builds on the wisdom of the crowd and it can only work if the crowd is wise in that sense right if they have no clue who's who then that approach is not going to work now um a couple of interesting properties of this approach are that a um beliefs don't need to be optimal for a strategy to work well here we have sort of circular uh trust network and so that is not the same you know so of this this person here do I have a pointer uh no uh the person on the bottom left she's only trusting the the one at the

top but not on the right so because she might have not not have interacted with them but nevertheless they get good liquidity and good adversarial exposure now um this approach is also naturally resilient because you can have subsets of the economy like the two accounts here at the bottom that if they um have accurate beliefs um and they can kind of shield themselves from other parts of the honest set of the network that have fallen prey to uh bad accounts, they can get sound tokconomics going among them and they are not sort of exposed to the bad decisions of others.

So to summarize the web of trust approach works as follows. If a collective agrees on some property X of people that people should have that they want to include and they hold collectively accurate beliefs about the excellence of others and they also choose their trust relationships according to their beliefs then we can achieve so then we can have the cake and eat it right that's the kind of idea now what's the implication for per for circles if we as a collective circles user base want to have sound tokconomics mean for us one circle per person per hour independent of we know what that person is, how what they do, we know how they live their lives, whatever. Then

what we should be doing, we should trust all those accounts that we are confident represent the primary account of somebody. And that's the only criterion. We shouldn't consider any other information. But we might of course decide to go beyond that. And so I want to kind of quickly uh just introduce the idea that what we should be after is maybe not proof of personhood but proof of economically uh trustworthy personhood. Right? Um so if uh I'm going to sort of tell you what I mean by that. But if that is what we're after is then what we should be basing our trust uh decisions on is um those we should trust those accounts that we are confident represent the primary account of somebody. We're still interested in

personhood but we're not just trusting any person. We're trusting people whose integrity we believe we can rely on when it comes to sort of trading or dealing with them economically. And I think this is sort of an interesting way to look at it at least for me because um I think it builds sort of on the strengths of the approach right I mean first person to my knowledge is sort of pretty much a binary property that people either have or they don't but economic trustworthiness is super fuzzy depends on you know what you mean by it so it requires human judgment so you know that's exactly what a web of trust approach gives you and that's not something that an iris scan uh sort of can even attempt to to um

substitute. Um it's intrinsically relative, right? So the fact that different people have different understanding of what uh trustworthiness means isn't really a problem, right? It just means that you're going to be dealing with people who ideally share sort of a similar idea of this fuzzy concept. I think there's really a lots of secondary use cases. So the idea of us being able to produce a trust graph that isn't just proving proving personhood but something stronger is very interesting and whoever of you was here when Sebastian gave his talk and we talked about how can we sort of choose uh which nodes we should let uh expose our public IP address to and we could sort of choose to choose this this you kind of incorporate this graph then I

think this is already one interesting use case and I actually think that a lot of us are already doing that a lot of us are basing our trust decisions already not just on the question of is this a person or is this their primary account but you know how come to what extent can I rely on them so as a simple thought experiment um to sort of if you if you are not sure which of the two camps you would fall into what what is your sort of circle strategy you consider the following example let's say there's an account um that uh runs a whole bunch of civil accounts and that gets discovered so Now what do you do? Do you entrust all the civils and not the central

account or do you entrust all of them at once? If depending on where you fall, you already you've already made a decision. And I'm not saying one is necessarily better than the other. I just think that of both both vi of valid uh properties we might be after. All right. So that's a lot of theoretical blah blah. uh let's try and evaluate this question looking at the actual uh circles user base. So in as circles in the team we have a blacklist of um around 12,000 accounts and um these have been I mean they hold around 26 million circles right now and that was last week and uh we put together this list um essentially based

on trustworthy uh personhood. So for example, if we discovered a a network of puppets, we didn't just include the puppets. We also included the puppet master, the account that actually drove this thing. And just to clarify, this blacklist, I mean, is not limiting anybody on the protocol level. You know, we as Gnosis, we cannot censor what you guys are doing on circles. But of course, we own groups. We run groups. And as owners of these groups, we can make decisions about letting letting people on this blacklist in or not. Right? Right. So this is important to clarify that we have no sort of backdoor entrance in sort of uh sanctioning anybody here. Um right there's two groups that are kind of

prominent in the current scheme. There's the circles backers. So the group of those people that have put their money where their mouth is. Um and there's uh and sort of invested $100 and they hold around 1 million circles right now. And there's the metric core group which is a sort of a loose group of 800 people. I think today it's actually 1,200 people. Um, and they also hold around 1 million circles. And so we didn't weren't very careful and who we let into the metric core group. But the back is of course they have an incentive to be very conservative with their trust. And here's sort of the numbers for the adver adversarial exposure by which I mean how many circles could accounts on the blacklist today channel into either one

of these two groups? And we can evaluate this in terms of absolute numbers, but we can also evaluate this relative to the total holdings of the blacklist accounts and those of the two groups respectively. And um the answer is that for the backers, we're actually looking pretty good. The backers have successfully sort of shielded themselves from the blacklist. Um they can only there's only sort of 2K out of 26 mil that can go in there. For the core group, the numbers look slightly more concerning because the absolute number is 91,000 circles and that constitutes around 7% of the current holdings of the core group. So either we are pretty bad at putting our blacklist together or metric core group

isn't aligned on what they're basing their trust on or they're not doing a very good job in in in trusting accordingly. Right. Before I finish, I want to talk to you about um one way that if any of you was now sort of starting to be concerned about the web of trust or like you know sort of um does this mean that sort of it undermines uh the sort of circles project overall? I think the answer is a resounding no. Um and one of the reasons for this is the existence of groups that we introduced. So for example um projects like protocols like proof of humanity or self. DK they can create groups and circles that dynamically add all accounts to the

group that have gone through their protocol and now vendors or other accounts can start to decide to accept only their group circles. So by doing so, you can decide that you're only only ever going to get paid in coins that have been minted by people who've gone through some protocol, right? And so there's also of course a hybrid strategy where you can decide to rely to the web of trust to some extent. Um but you also want to kind of incorporate information from external protocols. Um so that goes to say that circles in my view is the language not the book, right? I mean of course we built the protocol based on sort of opinions and convictions but it's it's an open

protocol and you know everybody can build stuff on top of it. We can't force people to choose certain criteria for making their trust decisions but I think it's a good idea to start coordinating this uh to kind of drive the value of this project. And yeah with that I'm done. And uh if you still haven't created a metric account, please this is your chance. And I'm open for questions. [Applause] Thank you so much, Paul. Um before we open for questions, I just want to say that the next fireside chat will be about 10 minutes late. Not everyone, not every speaker is uh here yet. So, we'll

start about uh 320 more or less. >> Does that mean I have to take questions for 15 minutes? >> Yes, we're going to have to take questions. Uh let's go for it. I see many hands. Yeah. >> Uh hi, Ivan from Reactive Network here. Thank you very much for a clear and interesting presentation. So, uh the question is uh from my understanding uh trust cannot be expressed as just one number. So, let's say me and Bob has 10 transactions each worth of a,000 bucks, right? I can be confident that if I deliver the goods without an upfront payment, he will pay me later 1,000 bucks, right? But if I deliver goods for 100,000 bucks, in that case, Bob might reconsider and not pay. So, I think

you've probably thought about that and it would be great to hear your thoughts. >> Yeah. Uh I mean so I think in ripple pay and in trust lines this sort of additional degree of kind of quantifying your your your your confidence uh of the trust or something like this was present um and it's absent in the v2 of the protocol. So right now trusting somebody's a binary decision. I think we definitely have voices in the team that are in favor of of doing that. And I think the sort of Beijian view of looking everybody running around having s of these degrees of belief between zero and one about everybody else sort of pulls in that direction. But at the same time I think the protocol is complicated enough as it is uh both in terms of UX but also in terms of um uh

uh uh yeah just tech like technical implementation. And I would assume I wasn't the one making the decision about this. I would assume that we've made the decision in favor of sort of UX and and that and sort of we'll maybe see something like that on top of circles in the future. >> More questions then one there. >> Uh I I enjoyed how you talked about the the concept of trustworthy trustworthy personhood uh as a way to define humanness.

uh or or a form of humanness, right? There was a an opinionated view on what what constitutes humanness. Um in the instance where like let's say in the future I form a relationship with a aentic AI that feels aligned with me and that that agent then creates a circles account. I want to trust that agent. Does that does that pose a threat to the protocol to the circles protocol? >> No. I mean again it you know we don't write the rules we don't impose the trusting you know if if you get a if you get a collective like a a critical mass of people who share your feelings about how they should trust each other and what sort of sound tokconomics means for

them then you just do your thing right uh and so we we we can't control that we do have something we call the circles etiquette and we've made a decision to say that um circles is primarily a currency created by humans. Um, and so for now we say, you know, AI agents can be part of the economy, but they should have organization accounts and they can be paid and they can transact, but they shouldn't create. Um, and so this is, I think, our current stance on this, but uh, this is sort of what the future will see and whether you know anybody will move away from this. I mean, makes total sense to think about this. Yeah.

>> Okay. Maybe more. One more question. Oh, no more questions. Oh, >> okay. I see one there. No. Yeah. So my question is uh with the current graph uh so on the circles white paper there is this discussion of this possibility that maybe there's going to be a fractioning into different uh subgroups where this there's a subgroup of people who trust each other and their currency is worth a dollar and there's another one group that uh is currency is worth 20 cents and there's limited

liquidity between the two. uh uh this is a possibility mentioned on the white paper. I want to ask you with the real data is it actually happening or is it not happening? >> I think the short answer is is we see that it's it's kind of happening. Uh we definitely have groups on there that trade at different prices right now. Um and we're making sense of the the details of this. But fundamentally uh I mean what what what what Kelvin is referring to is something we refer to as liquidity clusters in in the in the paper. So basically any group of people where there's a trust graph between any two people we kind of have a guarantee that at equilibrium the prices of their tokens should be the same but you know when you don't have those trust graphs

between all connections then you can have this sort of bifocation or sort of triplecation and whatever and yeah I think we we have this right now um >> thank you very much I just want to comment that I think this is actually very interesting and not a problem I think it's actually very interesting that for this thing to happen it's like seeing economy >> in real world is >> I agree. I mean so in the white paper we like yes the main goal is for this to become a globally fungeible currency and it's all going to be one one price but it was sort of almost pedagogical the decision to present it as that because that's of the simplest way to think about it but of course reality is always more complicated and I think there's a an interesting future uh of circles in which we do have a handful of these

groups I think we shouldn't have as many as users that would be sort of uh you know not not the intention but there can definitely be be a handful. Thank you. >> Cool. Thank you. [Applause]