Laurens Hof 0:56 I'm Laurens Hof. 0:57 I write Connected Places, it's a newsletter about the atmosphere at Proto, Bluesky, Fediverse, and the ecosystems, the open social ecosystems. 1:06 I'm very interested in figuring out what are these systems actually? 1:10 There's a lot of cool narratives about what these systems can create, but I want to understand what are they? 1:18 And recently Paul Vergeer wrote an interesting article, Practical Decentralization, where he made two specific points. 1:24 The point of decentralization, he wrote, is to guarantee the rights of individuals and communities on the internet. 1:30 And secondly, he wrote, we use protocols to structure what— Speaker B 1:34 what? Laurens Hof 1:35 Who can do what. 1:36 Protocol designs are often about the how, but the consequence of the how is an authority model. 1:42 And I think that's super powerful because that really sells what's actually at stake here. 1:46 Like, building protocols is cool, but what we're actually building is authority models of like how social interaction happens on the internet. 1:57 Like, it's easy— like, many people have been getting interested in open protocols as a sort of response to big tech bad. 2:03 And well, obviously big tech bad. 2:05 But the reason big tech bad is because of the governance of the big tech platforms. 2:10 So that means very much like if we want to build different platforms, new ecosystems, systems, this is very much about what sort of governance and authority models do these new ecosystems actually allow. 2:23 And for that, I'm always very drawn to the statement by the cybernetician Stafford Beer with his great one-liner: the purpose of a system is what it does. 2:32 And I think that's both simple and powerful because it lets you cut through, like, all these normative statements and intentional language about what you want to be happening, but instead you can look at what is the system, what should be happening. 2:46 Like, what— not what should be happening, sorry, but what does it actually produce? 2:52 And for that it's also worthwhile to look at a little bit of the history of the internet. 2:55 Like, internet runs on email, the internet runs on open protocols, and the most famous one for emails is the SMTP protocol. 3:03 And that protocol just said very little about purpose or governance or anything at all. 3:08 It just says the goal of this protocol is to transfer mail reliably and efficiently. 3:14 And it turns out we've been getting extremely good at transferring email reliably and efficiently, and it also turns out that spam loves to be transferred reliably and efficiently. 3:26 So once you build an open protocol and, like, you have this statement of, like, hey, we want to do this thing, and then otherwise, like, you have a technical statement, but you don't say anything about the governance or the power that you create with this new system, You can have a decentralized open protocol all you want, but these gaps for power, they get filled by economic models. 3:48 And that's exactly what we see, we have seen with email, like spam filtering turns out to be a huge problem. 3:54 Google got very good at that and now email is basically a duopoly with Google and Microsoft. 4:00 So open protocols, still duopoly, still centralized power because the protocol itself did not account for how it generates power. 4:11 In general, that means power and value accumulates in the layer of a protocol that doesn't govern. 4:17 We've seen the same with HTTP. 4:19 Like, HTTP, also the spec of the protocol has, like, says nothing about power. 4:24 Like, Tim Berners-Lee made lots of blog posts around it about, like, great ideas of what you want the power to be. 4:32 But because that wasn't defined in the spec anywhere, then, um, that allowed that value and the power to be accumulated in the layers around it. 4:41 And that's how we got in this system of like, well, big tech bad. 4:45 Because these companies could accumulate this power in the layers around HTTPS. 4:53 And we've seen like, we've been doing open protocols for a long time, like since the early '80s, and now we've seen that, um, in the last decade or so, we've seen new protocols arise. 5:05 We've seen ActivityPub, we've seen Nostr, we've seen Matrix, and now at Proto as well. 5:09 And these protocols start to incorporate normative language in the protocol documentation. 5:14 They say stuff about governance. 5:16 They say stuff about what should this be doing? 5:19 What should this system create? 5:21 And I got 3 quotes from the Proto documentation here. 5:26 And I do think it's very interesting to see the normative statements pop up here, like speech and reach should be 2 separate layers. 5:32 Also the very normative Everybody should have— everybody has a voice. 5:36 And users are free to select their aggregators. 5:39 The protocol design sort of tradition sort of assumes a sequence. 5:45 First you build an architecture, the design specification. 5:49 Then you grow an ecosystem. 5:51 And then you add governance to that ecosystem. 5:54 But it turns out, like, growing that ecosystem is the same as adding governance to this ecosystem. 6:02 Because if you do not actually specifically specify the governance of the ecosystem, once you grow it, the implicit forms of governance, which are often like if it's not specified, it's just the most powerful economic actor who is there first, turns out to become the governance layer. 6:25 And the reason for that is that because If you grow an ecosystem or open protocol, you create shared resources. 6:32 And these shared resources are themselves governance structures because they compete, they involve competing interests. 6:39 For example, here on Alprotto, like if you build, if you run a relay, you immediately need to make governance decisions. 6:46 You need to decide, am I going to, which spam am I going to filter out? 6:49 Am I going to filter abuse out? 6:51 Am I going to filter copyright material out? 6:54 Or am I going to transfer these— like, am I just going to say I'm a neutral— neutral layer that just transfers all of this? 7:03 And like, there is not a neutral way to transfer spam or a neutral way to transfer abuse in your relay. 7:11 As soon as you operate a relay, you have made governance decisions because these are the shared resources. 7:21 This article I wrote recently about the purpose of protocols, and I got two responses from Paul on that that I think both are worth highlighting. 7:30 First, he said, like, my belief and hope is that we've opened the opportunities for other forms of communal resource governance to be implemented. 7:37 And, like, I very strongly agree with that. 7:39 Like, this is why I care about these open ecosystems, and this is why I care about, like, this conference, because, like, there's so many people around here that, like, that can— we can build these systems now. 7:51 We have created this infrastructure. 7:53 We can create this communal resource government. 7:56 Like, we have this open relays. 7:59 We can build the governance structures for it. 8:02 But Paul also says, I'm almost ready to say that the economics are determinative of the governance. 8:09 Well, I am actually ready to say that the economics are determinative, but if they are determined subjective, what do they actually determine? 8:22 For that, let's look a little bit more in detail on what App Proto actually does. 8:25 Basically, it creates two layers: a speech layer. 8:29 Speech is just like— it's cheap, it's permissive, everybody can publish, it's very easy to set up your own PDS. 8:35 And then there's the reach layer. 8:37 The reach is like— that's where you get the feed algorithms, that's where you get the app views, That's where you get the indexes. 8:43 That's where the people actually interact with your app. 8:46 And the reach layer, that's actually the expensive part of operating infrastructure. 8:50 And thus, that's where the economics are actually determinative. 8:55 And that's actually what you now see in the atmosphere in practice. 8:57 Like, Bluesky, the company, is like 3 orders of magnitude larger than any of the other operators because the economics are determinative. 9:06 And that's— they operate the expensive layers of the stack. 9:11 I want to zoom in even more. 9:13 I'm going to specifically zoom in on like the algorithmic choice here. 9:17 We do like— a proto allows for algorithmic choice, allows for everybody to run their own feed operators, etc. 9:24 But feed providers need users. 9:27 Users want engaging content. 9:29 And the thing is, what counts as engaging content is what everybody else is engaging with. 9:36 Like, our preferences for what we want to see, what we think is engaging, is not neutral, it's not defined by the individual, it's defined by the people around us. 9:49 Because we are, like, our preferences are shaped by other preferences, and our preferences are intrinsically memetic. 9:58 And for that, I want to zoom in on the For You feed by the independent developer Space Cowboy. 10:03 SpaceCow, it's an amazing feed. 10:05 And it's got— it has actually a fairly straightforward mechanism. 10:10 It looks at the post you liked, like, then it superset what other people also liked that post and what other posts they like, and it suggests then that post to you. 10:21 This is like this very explicit sense of like how we made it visible of like how our preferences mimic other people's preferences. 10:30 That is exactly in its most pure form what the For You feed does. 10:36 And actually, if you spend any time here in the ecosystem, the app, product developer ecosystem, you know that people actually really like the For You feed. 10:43 It is a very great feed and people recommend it all the time. 10:46 It's almost kind of a meme, especially if you compare it to the other popular algorithmic feed, the Discover feed by Bluesky itself. 10:56 And that's also a bit of a meme to almost hate on like the Discover feed. 11:00 Shout out to Dan for that. 11:02 Like, the reason for that is that— sorry, what's actually interesting about the Discover feed, BlueSky's Discover feed, is that it's an algorithmic feed, but it's not purely engagement-based because BlueSky is also trying to solve for other problems than just pure engagement recommendation. 11:23 They also solve for a problem of Hey, there's a new person signing up. 11:27 They— we don't know anybody, anything about that new person, but we don't want to show them an empty feed. 11:34 So how are we going to show them some, some interesting content via the Discover feed? 11:39 And Discover feed is very good at that. 11:41 It has multiple purposes and it's good at those purposes. 11:45 But what it reveals and what you can see in how the app pro, the developer community engages with both feeds is that The revealed preference is that people strongly prefer pure engagement-driven feeds over generically algorithmic feeds that also provide other features. 12:06 So now we start to see there becomes a sort of a loop. 12:10 Users engage with what other people engage with. 12:14 And what a proto does, it creates this single shared data space, like— This is the nature of this open protocol that everybody has an LPDS, like, and the relays, all the relays, all the app views connect to all that single data, the data space. 12:29 Like, this means there's this singular shared data space. 12:33 So users engage with, or other people engage with, and that gets captured by that shared data space. 12:39 Like, that gets captured by the likes on the lexicons, et cetera, et cetera. 12:44 And these feed providers then they look at this entire data space, pick out the most engaging content from that data space, because that's what the feed— that's what the feed providers want, because that's what the users want. 12:57 And then you see again, get back to the top, users engage with what other people most engage with. 13:05 So here we get this very interesting dynamic, what it means that if you have algorithmic choice in a single shared data space, that produces convergence. 13:17 And that means like you have— what I mean with that is that because of this loop, we get like we converge on this single centralizing point of the most engaging content. 13:30 And like this doesn't mean there's room for like niche content and niche feeds. 13:34 You can still always create the most feed all you want, but this is by definition niche. 13:40 And there's like— what you get is like this main set of feeds that are like highly engagement-driven because the underlying data space reflects this engagement-driven optimization. 13:53 And you have a very long tail of a whole lot of niches of algorithmic choices. 13:59 You can actually already see this in Blue Sky Sculpture where like all the data is open. 14:03 You can look at what content is the most liked on any day. 14:07 and that consistently converges on American left liberal politics. 14:11 And that's exactly what we would expect in this virtuous feedback loop of like the— that this diversity of feed providers selects for the most engaging content. 14:25 So the open system is competing on engagement and that's how you get convergence. 14:30 So you have an architecture that says pluralism, But the economics of it says, "No, you actually have convergence." So we have a protocol, like the protocols that focuses very much on individual rights, but these rights only matter as much as your choices to actually also are meaningful. 14:53 And that's how this openness produces convergence, because this governance is entirely absent in the protocol layer. 15:03 And that's exactly what we've seen in earlier dynamics for open protocols, for SMTP that also produced Gmail. 15:10 Like, the mechanism is different, like, that was spam filtering, and here it's instead of, like, engagement optimization. 15:17 Like, a protocol— the mechanism is that a protocol creates an open space, but because the governance of this open space is undefined, you get pushed towards economics, and the economics pushes towards concentration and not towards diversification. 15:35 And now we finally get to the point where obviously you all wanted to, uh, waiting for. 15:39 We can finally talk about K-pop, because like K-pop are like the, the fandoms are some of the most largest fandoms and the most coordinated engagement optimized driven optimization driven community. 15:52 And it actually works in both directions. 15:54 Like, you have the companies who produce the music, who are strongly commercially driven and deliberately optimized for impact and for engagement, because, well, they're companies, they want to make money. 16:06 And it's much more important to them than the artistic impression itself. 16:09 Like, not shitting on K-pop here, I love K-pop, like, I fucking love Jennie, like, we should all be more, well, like Jennie, but like, the companies, maximize engagement. 16:19 And the same actually is also true for the fandoms themselves. 16:23 And I think it's actually interesting to look at one YouTube comment section on a new K-pop song, like, to see what are the fans actually talking about. 16:30 And you see that they're very explicitly talking about listening to the song on repeat to make sure that— on multiple devices often— to make sure that the songs dominate the new charts. 16:40 Because, like, their they're deliberately participating in engagement hacking because the engagement is a validation of their fandom and of their idol. 16:53 Like, I'm guessing you understand that this isn't actually all about K-pop. 16:58 Like, this is really what happens when you have like an ungoverned reach layer on an open protocol. 17:03 And like, well, when there's— well, the governance is there, but the governance turns out to be economics. 17:09 And the economics then— sorry, how do you say— and the economics means that the community doesn't match the— blah, blah, blah. 17:29 There is governance on an open protocol, but it turns out that because the governance is not defined, the governance is economics, and the economics determines the outcome. 17:39 And that means that communities whose pattern doesn't match the dominant engagement pattern get structurally disadvantaged over the communities that do participate in, like, this engagement optimization. 17:52 Regardless of— irregardless of that the protocol guarantees your rights. 17:57 And the rights to choose is of your— to choose your own algorithm is only meaningful is, like, if the algorithms can actually if there is worth choosing in between them. 18:08 But because they all point to the single data space, like, they all converge on each other. 18:15 And there is still— that doesn't mean, like, there's still space, space for institutional governance. 18:22 And Black Sky actually gives a very good illustration of what that can look like. 18:26 These are two recent posts by Rudy. 18:28 Like, he showed trending, what was trending on on the Black Sky feeds, the Black Sky trending topics versus what's trending on Blue Sky, on the wider network. 18:41 And I think that gives a very good insight of like, okay, what does it actually mean to do create these sorts of divergence in topics and conversations? 18:50 Because that means setting very clear boundaries and very clearly defined communities, and those communities can have their own governance and their own cultures that create it. 19:02 But what we see is that when you have the implicit governance choices, they're like all the spaces that do not get governed by a specific culture, that do not have this clearly defined boundaries. 19:16 That's where you get economics determine the outcome. 19:19 And when economics determines the outcome, culture that is optimized for engagement like K-pop dominates. 19:27 Thank you. 19:39 Sure. 19:40 Questions? Speaker B 19:45 So what do we do next? Laurens Hof 19:46 Listen to K-pop. 19:48 Okay. 19:48 Like, it's very easy. Speaker B 19:52 Thank you. 19:53 Great. 19:53 I think we're done now. 19:57 You've written a great post about this. 19:59 I think a lot more about governance going forward generally. 20:05 And as you said, collecting funds for other entities in the network. Laurens Hof 20:10 Absolutely. Speaker C 20:11 Yeah. Laurens Hof 20:11 Thank you very much. Speaker B 20:12 Thank you. 20:19 Fig, come on down. 20:22 Beyond Blue Sky, community infrastructure, with your favorite bad example. 20:37 Apparently I'm saying the same thing again so online can hear my stunning introduction. 20:43 Yours and mine's favorite bad example, Fig. 20:50 Beyond Blue Sky: Community Infrastructure. 20:52 Thanks, Fig. Speaker C 20:54 Let's do extend instead of clear. 20:58 Oh, thank you. 20:58 Okay, awesome. Speaker B 21:03 Okay. Laurens Hof 21:09 Let's see if this works. Speaker C 21:14 And try really hard. Laurens Hof 21:17 Yes. Speaker C 21:18 All right. 21:22 Get my mouse back. 21:24 Okay. 21:28 If the text is small on some of these slides and you want to follow along or you want some spoilers, you can get the slides locally. 21:37 I also just Posted the link on my account. 21:42 Yeah, thanks everybody for coming. 21:43 I'm going to jump right in. 21:44 I'm Fig or Phil. 21:47 You might know me as bad example. 21:50 And last year when I was here, I had shipped Constellation. 21:56 And since then I've done a few other things.