We weighed several factors in making a final decision on which trade to accept. We care about more than just the economic value of a trade; we value the culture, story, and journey of the NFT as well. In Round 1, we picked the future. But the past always has a way of coming back around… And the 2 (ok 1.02) historic LarvaLabs NFTs we acquired bridge the past to the future beautifully.

This decision wasn’t easy; we received incredible offers and, as in Round 1, were sad to part with all the memorable NFTs that we couldn’t accept. Check out the full Round 2 offer thread to see all the amazing offers.

We only have time to highlight a few of our favorites. In no particular order, here is our homage to the ones that got away in Round 2:

• Several offers paid homage to @paperclipDAO. To immortalize the Parallel Trade from @bitcoinPalmer, urukai (discord link) created 2 Proof of Beauty $HASH pieces: One that represents the tx from Palmer to Planck ($HASH sent to Palmer in tx - 0x9d685696e1401a38eee957665f57a720212b409b373c8fe275608309c44da9cb) and a second that represents the tx from Planck to the PaperclipDAO address. What an awesome gesture! We were also offered a $CLIP Kitty by AnimalTPFR (discord link).

• We received several offers for Blitmaps, a really cool community started by Dom Hofmann. Blitmaps and their metadata are stored and processed entirely on-chain. There are 100 originals, created by 17 artists, which the community mixed to make 1,600 siblings — unique pieces that combine the composition of one original with the palette of another. We were offered a sibling: Pale Tower Warm Vibe (from avilés) and an original (!!!) #35 - Candy from itzler (discord link). Naturally, this was a finalist.

• Granolah offered Ghxst 006 (discord link), one of the original 6! Ghxsts is an NFT project designed and created by NFT artist, GxngYxng. Each item in the collection is hand-drawn and released one at a time in random order. There are currently 101 Ghxsts, 42 Immxrtals, 50 Demxns, 12 Zxdiacs, 25 Alixns, and 9 Sirxns. Granolah later upped his offer to include 3 cool cats as well.

• OhhShiny offered us Bored Ape 636, a zombie and dmt (and also our first BAYC offer!) The Bored Ape Yacht Club NFTs double as a PFP and a Yacht Club membership (aka a swamp club for Apes). We received a few other offers for PFPs: Sisyphus offered a crowned Pudgy Penguin and state (discord link) offered a bundle of a classy pengu & classy meeb.

• We already mentioned our beloved CryptoPunk #3744 but we also received an incredible offer from Andy8052 for 80,000 $DEAD tokens (currently valued at $200,000) which represent 6.66% of Zombie Punk #2066, (link to discord).

• Mr. bulldops offered the 0xmons Dza (discord link), a Lovecraftian “pixel monster” generated by a neural net. Though we find it hard to believe that the artist behind this amazing project is the same 0xmons who created our beloved sudoswap, we have been assured this is actually the case.

• We were also offered a FuckinTroll, a Shiny Nyan Cat (discord link), several Treeverse plots, and a few RTFKT NFTs. FunkySapienX offered a completed Budweiser Tom Sachs Rocket (discord link) as part of his proposed trade.

• We were offered several other ParallelNFT cards, which were tempting as always.

• A very fun offer was a pair of very clever ENS domains, twenti.eth and thirti.eth.

• We were offered a Gods Unchained Genesis Card, the 1st NFT Digital album KINGS OF LEON x YELLOWHEART NFTS, a membership-token to the Elektra DAO, a collaboration of musicians using the blockchain to create a community, and Chapter 3 and Chapter 4 of the Elektra Story: a story in the form of NFTs.

• Cliff Vandercave made an offer for a POAP token of a Rare Pepe created by Matt Furie himself, limited to about 500 participants who attended the event in the Metaverse. Cliff proposed that this swap would represent a unique intersection of PaperclipDAO, Parallel, Matt Furie, POAP, Metaverse DAO, and Cryptovoxels, forming a beautiful bond of NFT history (discord link).

Each of these offers adds to the storied history of the PaperclipDAO and we couldn’t be more excited to add our second trade to the history books. In Round 2, we looked to the past, what does the future hold for Round 3? 🖇🖇

We weighed several factors in making a final decision on which trade to accept. We care about more than just the economic value of a trade; we value the culture, story, and journey of the NFT as well. We also had to make a hard call about whether to honor the past or push towards the future. Our final poll after hours of discussion was a dead heat:

It wasn’t easy, but we ultimately decided to go with a trade that highlighted the future of NFTs.

PaperclipDAO now owns a 1/5 SE Earthen Concept Art Card, which can be used in Parallel, a sci-fi collectable game composed of digital collectible cards that can be combined into decks that dictate the game (think Magic at the Gathering or Pokemon). The Earthen Concept Art NFT was given only to early supporters of Parallel, and it's gratifying to see people taking the opportunity to recount the NFT's unique history.

It’s a promising future for digitally scarce, playable cards, and since the purchase of these NFTs funds the development of the game itself, it also demonstrates the wide range of utility of NFTs. Who knows, maybe the team will let us bestow some magical paperclip power? 💫

This decision wasn’t easy; we were blown away by the offers we received and quickly realized that the hardest part would be parting with the incredible NFTs that we couldn’t accept. Check out the full Round 1 offer thread to see all the amazing offers.

Given the quick turnaround, we only have time to highlight a few of our favorites. In no particular order, here is our homage to the ones that got away in Round 1:

• Our very first offer came from JPG’s Maria Paula Fernandez, who just plain got it and proposed a trade for simulacra before we had explained the project at all. Legend. EDIT: There was actually a tie for the first offer, with @AdrianLeb offering a lovely BlockArt at the exact same time as MP, making them co-legends.

• Adam Cochran offered this Cool Cat, complete with sunglasses and a great story. As competition heated up, he increased the offer to 4 Cool Cats. Adam later put forth an offer that absolutely blew his first two away! He proposed a collection of 14 historic NFTs, in a collection titled Moments in Our History. This collection represents unique fists, influential artists, and rare defunct collectibles that helped shape the NFT space and have led to the NFT renaissance we're living right now. It’s an excellent read.

• A $HASH of the @paperclipDAO UNIv3 NFT was also minted and proposed. Proof of Beauty is stunning. Just look at them. And to honor our project with a mint of the $PAPER/$CLIP NFT floored us. Sisyphus also offered an original Proof of Beauty, for Beeple's first Everydays mint on-chain in another historic NFT moment offered for the first trade.

• MoonCatRescue is absolutely one of the great NFT stories, with a community rediscovering and rescuing these Mooncats that have been “trapped” since the project began in 2017 (!!!). No way to do it justice here--you have to read about it. We were lucky to be offered several Mooncats (this one, this one, and this one).

• Folia’s Kudzu virus is the genius brainchild of Billy Rennekamp, one of the NFT OG’s (with the NFT to prove it). There’s nothing else like it--it’s a permanent NFT that will never leave your wallet. When you send it to someone it mutates and they get their own, permanent, NFT. We were offered 2 (this one and this one).

• Calvin Liu offered up a Non-fungible Pepe, which was a close contender (see final poll above). Creator Matt Furie is well known for creating Pepe the Frog back in 2005 for a comic called “Boys Club,” which subsequently went on to become the Internet meme that we all know and love.

• @JordanLzG splashed the pot by offering The Title Open Edition by Pak. Pak is an anonymous creator at the forefront of experience-based art. His work was recently auctioned by Sotheby’s and his collection The Title (from which The Cheap hails) was one of the best NFT-based experiences in 2020. We were also offered 3 in Pak’s The Flipper series.

• In a very special offer, devops199fan offered #404/420 of the EthereumFilm Infinite Garden Bloom NFT in collaboration with the one and only pplpleasr 🤩 . Each NFT is tied to select on-screen credits in the film, which will be the first feature-length Ethereum documentary and the first documentary funded via NFTs.

• Astrocryptids is a charming little project where a twitter transmission bot “beams” mysterious code to an artist who then creates algorithmic sprites with a unique star code. We were offered 7.

• Artblocks is the premier name in abstract NFT art, and among several Artblocks curated pieces we were offered was a gorgeous Rinascita.

• Jonathan Mann, the songadaymann himself, wrote us a song about the man that did/didn’t invent the paperclip! This ranked the highest in paperclip-iness! Truly the one that got away. He’s since started an auction for the song on Zora.

• For the real OGs, we were offered a very rare 5x symmetrical clover (from Clovers.Network) of which only 55 were ever found. It has symmetry in both diagonals, x & y axes, and rotationally. It’s also a very lucky four leaf clover!

• We were offered a Pudgy Penguin, a Meebit, and a baby Bored Ape - a nod to the many emerging icons of the NFT world.
  One interesting offer included all three NFT standards: an ERC-20 (an $XMON), ERC-721 (an Artblocks), and ERC-1155 (a Parallel)

• Pixel Portraits is a fun project with portraits of interesting people in the cryptopunks style. NFT OG Nick Johnson, who helped edit the ERC-721 proposal, offered his portrait of Alan Turing.

• Finally, we were given a choice between 1.) a rare 1/27 XCOPY piece from an obscure NFT project launched in 2018 or 2.) a 0xmons named Maznoth + their unique sound.

Each of these offers makes our story all the richer and we couldn’t be more excited about our first trade. In Round 1, we picked the future. But the past always has a way of coming back... Round 2 starts now! 🖇🖇

Propose a Swap for Round 2 sudoswap.xyz

↳ Only For: 0x87EE1158bEe297c381745284dcb2E54fA03EB5f2 (paperclipdao.eth)

↳ Want Type: ERC1155 ↳ Want Asset Address: 0x76be3b62873462d2142405439777e971754e8e77 ↳ Want Token ID: 42 ↳ Want Amount: 1.0

↳ Have: Your NFT or bundle of NFTs!

↳ Post it: in the #offers channel of the paperclipDAO discord.

It’s an amazing story and even an archetypal one---an old Buddhist folk tale tells of a man who traded from a single piece of straw until he had a rice field. The Legend of Zelda’s “trade up” quests took inspiration from this classic story, as have others.

With the incredible diversity of NFTs available today a similarly magical tale is possible. So let’s create it. Come trade with us and let’s tell the story of some amazing NFTs along the way. 


Today we are offering up our first trade which is, naturally, a paperclip. More specifically it’s a “$Paper/$Clip” NFT for a redeemed Uniswap position. You can see it here.

Here's how to trade with us:

1. Check our twitter @paperclipDAO for the pinned tweet telling you what NFT we're offering for trade.

2. Create an offer on Sudoswap to exchange your NFT for our NFT. Sudoswap will generate a trade link.

3. Tweet your trade link at @paperclipDAO, proposing the trade. $CLIP holders will then vote on whether or not to accept your trade.

4. If yes, we swap!

So about those $CLIP tokens... anyone who successfully trades with us gets $CLIP tokens so they can join the DAO and continue to create the story. The first to trade with us will get the most $CLIP, and as the story becomes richer and the NFTs more innately valuable the amount of $CLIP given will decline (in an interesting way perhaps…)

Where will this journey end? We think it might be cool to rescue an unobtainable NFT, maybe one from another dimension, and make it available to the community. But only time will tell.

Let’s start swapping and find out.

To keep up with this adventure, join our Discord and follow us on Twitter.

You might know this nice fable recounted by David Foster Wallace in a famous commencement address:

There are these two young fish swimming along and they happen to meet an older fish swimming the other way, who nods at them and says “Morning, boys. How’s the water?” And the two young fish swim on for a bit, and then eventually one of them looks over at the other and goes “What the hell is water?”

When you first read this, you might think the point of the story is that the young fish are basically idiots who don’t understand something obvious. So maybe, here in an essay proclaiming to be about NFTs, it might seem like we are setting the stage for a lesson like “lots of people don’t know what NFTs are even though it’s simple: NFTs are just ____________.”

Quite the opposite!

I’ll contend that you probably do know what NFTs are. But most everyone you disagree about them probably does too. And but so when people say “it’s simple: NFTs are just _________”, perhaps filling in the blanks variously with “property titles” or “status signals” or "examples of crudely mimetic speculation" or “pointers to a file” or “the artist’s signature” they’re probably right. Except for the word “just.”[1]

And I will try to prove it to you by drawing on an old study about -- what else? -- water.

"What the hell is water?"

Believe it or not, the answer to "what is water?" isn't simple at all. And perhaps summarizing evidence on this can help us all remain NFT value pluralists, especially here in these early experimental days. While it may be exciting and thought-provoking to speculate on what "NFTs actually are", the example of water can remind us just how complex and surprising a truly good answer might be.

Going back to the parable about the fish, suppose that instead of just swimming away one of the younger fish stops and musters the courage to ask the older fish, “wait, so what is water?” What would the older fish say? Maybe, “Oh water? That’s just H2O”.

"Just H2O" feels like the rigorous answer, but it turns out not to be true. Or rather, it's true except for the word "just." A remarkable experiment by B.C. Malt asked subjects to classify various liquids as being “water” or “not water” while also asking them to guess the H2O content.

Tables 1 and 2 report the results and the findings are instructive. There are a variety of things which the subjects class as “water” despite having substantially less H2O content than items classed as “non-water.”

Table 1: A Selection of items classed as “non-water” that have high H2O

Table 2: A Selection of items classed as “water” that have lower H2O

These findings point us to the complexity of our commonsense understandings -- if I dip a teabag into a mug of water it becomes tea, but if I dip a teabag into Hudson River it doesn’t become tea. And if Lipton polluted the Hudson River such that its “tea” content was even higher than the tea in my glass it still wouldn’t be tea. What’s the difference? Linguist Magdalena Sztencel summarizes thus: “whether we regard something as water or not depends on the intricate interaction of human interests, concerns, beliefs and intentions.” In this case, likely the fact that I intended to make tea and Lipton didn’t.

Is it so surprising, then, that NFTs can be variously art, property titles, signatures, and so on? An artist/creator/author/scientist’s intention to make an NFT “be” the work itself (or an inseparable component of it) may just be sufficient.

[1] Perhaps interesting to note that early Western visitors to Yap assumed the Rai stones were “just” size-denominated money and failed to understand why the stones had individual names and why the value could depend on “whether it was brought by a famous sailor, or whether people died during its transport”. But size mattered too! [a.]

[a.] Didn't feel right to have a David Foster Wallace-referencing article in here without at least one embedded footnote.

Thanks to awesome participants in a Kernel Junto for offering feedback and discussion (Vivek Singh, Diana Chen, Estefanía Ochoa, Paul Drouet, Robin Roy Thomas, Colton Brown, Jeet Raut, Mayank Dubey, Miguel Cabeza, Nuno Neto, Rev Miller, Kyle Smith). Simona Pop, Jamsheed Shorish, Michael Zargham, Simon DLR, and Matt G. Condon also offered characteristically brilliant suggestions/thoughts.

By Michael Zargham, Scott Moore, and Matt Stephenson (author order randomized)

Public Goods Problems and Coordination Problems describe some of the most fundamental and important challenges we face both in Web3 and the wider world. While they are related concepts, they are theoretically distinct. Is this a distinction without a difference? In this note we explore why game theorists and even behavioral economists (like one of your co-authors) make such a distinction. We will describe what the difference is and why it might matter.

Let’s begin with a simple example:

Suppose you’re at a concert and everyone is comfortably sitting down and enjoying the performance. Suddenly people several rows in front of you start standing up to get a better view, which makes everyone behind them need to stand. Now, while you’re still comfortable in your seat, you can’t see anything. So you give up and stand too.

Now let’s analyze the situation: nobody’s view has actually improved by standing instead of sitting--the backs of people’s heads are just as in-the-way as they were before. But now everyone is less comfortable. We have thus moved to a less optimal outcome. And worse still the situation is more sticky, more “equilibrium-ey”[1] if you will. Initially we all stood because just a single person standing could affect everyone behind them, totally changing things. But now if someone sits it doesn’t really matter--we all just have to stand to see over everyone else standing in front us. To solve the problem, perhaps we could get everyone to sit at the same time.[2]

This sounds like a coordination problem, right? Not so fast!

It’s only coordination if “everyone sitting” is a stable equilibrium. And so as we've defined it, getting everyone to sit again isn't actually a solution. This is the essential difference between Public Goods Problems and Coordination Problems: in a Coordination Problem the optimal outcome is stable, whereas in a Public Goods Problem the optimal outcome is not. More technically, we can say that coordination games exhibit multiple pareto-ranked equilibria which include the social optimum (Dutta, 2012) whereas public goods games have a non-equilibrium social optimum (Hichri & Kirman 2007).

If you find that confusing don’t worry-- there was literally an oscar-winning movie about John Nash that got this wrong. In A Beautiful Mind, when it came time to describe the Nash Equilibrium (Nash’s defining contribution) the movie instead discussed an unstable non-Nash outcome just like the “sitting down at a concert” example. You can watch it here.

The distinction to be made is that, unlike a coordination game, our concert example and Russell Crowe’s bar-room musings in the movie both feature an “incentive to defect” (aka the “free rider problem.”) In the concert example, when everyone else sits down and you stand you actually do get a better view.[2] Or using the movie’s dated example, when your friends go for the brunettes and don’t “block” you, you are actually clear to “go for the blonde.”

You can see in the illustration below that the difference between the two games depends precisely on the relative magnitude of the “defect” payoff. The Public Goods game on the left can be transformed into the coordination game on the right with a single change: reducing the payoff to the defector (circled in red).[3]

But this means that, having defined the concert problem as a Public Goods game, it doesn’t matter if you get your bullhorn out and coordinate everyone back into their seats. Someone will always stand back up. And soon we will all be standing again. That’s what it means to have a “non-equilibrium social optimum”--you can see it, you just can’t live in it.

But that’s just the problem as we’ve defined it. Is that actually the problem?

What game is it?

Let’s pause and reflect for a second.

We are not trying to convince you that you can’t make people sit down at concerts. Nor do we care about the semantic differences between “coordination” vs. “public goods” problems. This difference matters, we contend, because the public goods framework is good for stating problems and the coordination framework is good for conceptualizing solutions.

The likely reason that A Beautiful Mind got the Nash Equilibrium wrong is that Public Goods problems almost always present to us humans as, well... problems. That is, when we see them we are often drawn to solving them. And here’s where you’re going to start to feel the edges of not just game theory but any sort of human-regarding theory.

The mind balks at Public Goods Problems. “Don’t you see” you want to ask, incredulous, “that if you stand up, soon everyone will stand up and your view will be the same as before but now you’re less comfortable?” That’s what a public goods problem feels like. Let’s live in them for a little bit and feel their power before we move on and discuss how to solve them.

The prototypical Public Goods game has been run in a laboratory setting countless times. Run it with more than a few players and “players do not, in general, manage to coordinate on cooperative behaviour” (ibid.) Worse still is that, unlike some two-person games, repeating these games doesn’t help. In fact, cooperation typically gets worse over time as you can see in the figure below:

The way a laboratory public goods game works is: everyone gets some money, say 10 people get $20.00 each, which they can contribute to the public pool or keep. The experimenters then increase the money everyone contributes by e.g. another 20% which is split among everyone in the game. Crucially, this split happens for everyone, whether they contributed or not.[4]

On the graph above you can see the average “contribution” on the y-axis, with rounds on the x-axis.[5] And have a look at period 1 up there on the left, where most everyone is hopeful and optimistic and so the average contribution is quite high. Everyone does pretty well. What goes wrong to make everything unravel?

Having personally run, and participated in, these public goods experiments many times one of your co-authors can explain what’s largely going on here. To get a feel for it, here’s what this game looks like with four players:

Look familiar? It’s that annoying “incentive to defect” again (circled in red). What’s happening is that the free rider is not excluded from receiving the “common pool” split. And since they also get to keep the $20 they didn’t contribute, this means they always make the most money. And then in the next rounds this happens again and again, the gap growing ever wider.

After a few rounds your fellow contributors are starting to get a little pissed off. They believe in the common good, sure. But you can’t just sit back and allow these free riders to make everyone a sucker like this can you? The unraveling of cooperation that you see in experimental chart is often the “we’re not going to be suckers” feeling spreading through a population.

That may look a bit depressing, but there’s some good news too. For one thing, even if you repeat this for a very long time, there is typically ~10% of the population who never give up the faith and just continue to contribute no matter what. These are the saints. For another, if you just shuffle the players and start the whole game over you’ll notice something amazing; most everyone regains their optimism. It looks about like this:

That is, in each period 1 you get this “restarting” effect as everyone tries to jump start cooperation again. Hope springs eternal! Of course, because they are playing a true Public Goods game (unfortunately) cooperation devolves again. But this behavior is a crucial building block of a real-world solution. This hope we observe is why we get to try and fail and try again.

How do we solve these things?

We saw that a public goods problem is characterized by an unstable social optimum, vulnerable to individual incentives to defect. But we also saw the experimental evidence that some people never give up, and that in a new game most everyone will try again to reach the social optimum, hoping that maybe this time the unstable outcome will be stable. They are hoping, we might say, that this time the Public Goods game will turn out to be a Coordination game.

With that in mind, we can propose an ad hoc hierarchy for solving these problems. Speaking roughly, a public goods problem is solved by transforming/reimagining it to be a coordination problem:

Starting from the top right you have the best possible solution concept, called a “Prisoner’s Delight.” It means that the socially optimal outcome is the only stable equilibrium! This is not even a coordination game--it’s a solved problem. Whereas we saw that Public Goods Problems almost always strike us humans as problems to be solved, the Prisoner’s Delight “problem” really doesn’t seem like a problem at all.

As a result, our example is going to feel a little silly. A good example might be “setting your house on fire”. Most people don’t want to set their house on fire and so “everyone’s house not on fire” is stable with no incentive to defect. This is the social optimum. And what about the situation where everyone else’s house is on fire, does that make you want to set your house on fire too? Of course not! Which means there’s not even an equilibrium at “everyone sets their house on fire” because now the temptation is to, well, “not set your house on fire”. Absent insurance shenanigans, “don’t set your house on fire” is the strictly dominant strategy and any deviations from it do not destabilize the system.[6]

So let’s move down the chart to proper coordination problems (with multiple equilibria). In this world, the equilibria are at least stable once people are in them and so we “just” need to get them there. Making people choose the “good” equilibrium in a coordination problem can be described as making it “focal.”

Here is a (non-exhaustive & ad hoc) hierarchy of coordination games ranked by how “focal” the equilibrium tends to be, ranked from best to worst:

1. Payoff Dominance. A preferred equilibrium which provides the highest payoff for all players in the game is extremely focal.[7] If you play a game like this in the lab it will feel silly and hardly like a game at all because everyone does the preferred thing.

2. Risk Dominance. A preferred equilibrium which is risk dominant is more fragile but can be naturally coordinated on. Picking an action that is risk dominant roughly means that if other players don’t do what you expect you’re still relatively better off than you would have been otherwise (mutatis mutandis).

3. Inertia. If the preferred equilibrium isn’t payoff dominant (as in #1) or risk dominant (as in #2), you can still make use of the fact that people will just stay with what they’ve done in the past. Thus if you can start there or get people there they may well stay.

If we keep only to monetary utilities, leaving the behavioral mechanism design out of it, these solution concepts are basically: “Everybody gets rich” (1), “Everybody avoids losing money” (2), and “Who cares about getting rich, let’s just do things the old fashioned way” (3). And, speaking somewhat loosely, you can actually use the commitment aspect of smart contracts to change the game along these dimensions.[8]

Expanding to the behavioral sphere our options really open up. Now we can grant, say, social status to coordinators. We can signal disapproval to those who, say, stand up in front of us at a concert. We could even make “doing things the old-fashioned way” have a sort of identity bonus, an additional utility stemming from the embracing of tradition.

We might be revealing our bias, but real solutions will often live in the behavioral realm at least to some degree. When you think about solving the “concert problem” from earlier you might be inclined to say to the stander, “Excuse me but would you mind sitting? The rest of us would prefer it.” And when they then sit and everyone is better off, whatever kindness, reciprocity, or even shame aversion that person felt that made them sit is what drove the coordinating equilibrium.

Which is all to say that “transforming” a game along these lines is a fundamentally creative act. And Lin Ostrom’s work reminds us that creative solutions abound, and that communities can solve what look to outsiders like Public Goods problems (thereby demonstrating that they are actually coordination problems.) Ostrom was the essential inspiration for our solution concepts above, reimagining Public Goods games as Coordination games.[9]

Do Public Goods Problems Actually Exist?

The Public Goods framing remains invaluable, at least insofar as it captures what a social problem feels like before it is solved. Each of us knows there are situations in which we can all see the social optimum but can’t quite figure out how to get there yet. The sink full of dishes that all the roommates would like to have washed but would rather someone else do it.

And we also know there are situations where we think we’ve reached a solution, only to find it’s unstable--we can feel the frustration after we whip all the roommates into a Sunday morning cleaning frenzy to finally get all the dishes washed... only to watch over time as the sink fills back up with the roommates nowhere to be found. This is the frustration of the would-be coordinator discovering that they’re still playing a Public Goods game.

On the other hand we can’t help but feel -- watching people unhappily standing up at a concert, writing valuable code in a private repository, or failing to develop scientific ideas -- that there must be solutions. And it’s comforting to know that earnest attempts to solve these problems may be met by the hopefulness we saw in the experiments, the inextinguishable belief that maybe this time we can all get to the social optimum and stay there.

In the end, “what game are we playing” is not really an answerable question. To the pure game theorist, the idea that you can “reimagine” a public goods game as something else is nonsensical--it’s either a public goods problem or it isn’t. In that light, let’s choose to imagine that all Public Goods problems are just Coordination Problems in disguise. And so let’s solve them.

Endnotes [1] Zargham would like his discomfort with this phrasing noted in the record. The concert example is adapted from Stephan Meier. [2] And, to be slightly technical, the utility you get from the better view is greater than the disutility from not sitting. [3] This is a solution concept that we will return to later. And note that you could also, say, transform the game by raising the cooperative payoff above (15, 15). The stylized facts about the formal relation between coordination-type games and public goods/PD type games descend from Luce and Raiffa 1957. [4] This feature, called non-excludability, is fundamental to what a public good is. [5] The different colored lines represent outcomes across different national populations (almost always students). We’d suggest not reading too much into those differences unless it’s to rib our Aussie friends. Chart from https://www.core-econ.org/. [6] Problems like “who pays for the fire department” bring us back into public goods land of course, but that’s not what we’re talking about here. [7] Assuming this payoff is not risk dominated, in which case see #2. [8] This article was an elaboration on this piece and emerged from discussions with Cathy Barrera and the ethresear.ch community, later elaborated on well by Virgil Griffith. [9] And there is thoughtful and interesting work being done on “Ostrom Compliant” organizations. See also this excellent twitter thread on ways to think about what these games are and how they can be transformed (and thank you to Oliver Beige for pointing us to this).

Look how flat the curve is before ~1850. That curve is a measure our ability to do more with less, to meet our human needs without simply forcing everyone to work harder. And so it's interesting that IR 1 didn't really improve our lot, at least not for decades and decades after it occurred. What happened?

Let's observe that the curve actually changes with the appearance of a wave of major inventions that had quite a different character. Broadly speaking, we can say that whereas IR 1 brought us together with connecting inventions like the steam engine, the second wave had great livability innovations in areas like heating, sanitation, electric lights, elevators, motion pictures, etc.

The IR 1 world was a newly connected one, but it was also polluted and dangerous and kind of miserable. And so we didn’t actually produce much all huddled together, drinking dirty water and breathing fumes. But then, once we figured out how to make this newly connected world more livable and pleasant, things got vastly better. Only then did we get the growth explosion that the Industrial Revolution is famous for.

In this light, it might be interesting to read top economists today pondering over the stagnant growth and missing productivity of the internet era dating back to the 1970s. Perhaps we can imagine a similar economist during IR 1.0 puzzling over the missing productivity that the steam engine should have wrought.

What if today’s economists are wrong for the same reasons — what if the internet is indeed revolutionary and we just haven't gotten the 2.1 patch?

The internet brought our minds together in a great network to rival the 19th century network of railways and steamships. If this 1800s network could take you to undeniably thrilling — but also crowded and disgusting — cities, perhaps the internet too feels a bit like this now. Thrilling but awful, alluring but somehow inhumane. And so perhaps some optimism is available in the story of the 19th century, and the fact that its network showed a lot of promise but failed to deliver for a very long time until, suddenly, it did.

What if the same thing is true now?

NFT

SplitStreamees, claim your funds here:

R1 Level Split

or here:

Planck Root Split

A huge thanks to mirror for helping us implement this (despite a misstep or two I may have made in the process...) Mirror did not request, nor did their build require, that they be included in the SplitStream. But of course we included them, if for no other reason than that we ran it on their technology! Patrick Riviera, in particular, was incredibly helpful throughout. Also thanks to Aleo and Harry Crane and Ryan Martin. We think that Zero Knowledge Analysis has a big future.

And a special thank you to Michael Zargham, the winning bidder, who described the NFT beautifully as a "a unique digital pointer to a node in the directed acyclic graph we call science."

The two professors of statistics who ran the independent data analysis, Harry Crane and Ryan Martin, have produced an elegant violin plot of the results to be auctioned off. You can see (and bid on!) this auction directly below this paragraph, but you are welcome to keep reading beyond if you'd like to better understand the SplitStream and, thus, where the proceeds will be going.

Token #2837

The SplitStream

You might know the quote “If I have seen further, it is from standing on the shoulders of giants”. You might also know that it’s from Isaac Newton, a giant if there ever was one. So in science, giants tend to look down and see other giants. Citations, when they work, map those dependencies backwards through time.

Citations on citations.

Giants all the way down.

If you send funds through these citations, you get a cascade. A stream of splits. A SplitStream.

The SplitStream is a system in which portions of an NFT sale may flow to some or all of the works the NFT cites, with those cited works then sending some of their funds further along to the works they cite, and so on.

Here’s what it looks like:

Independent data analysis is a really valuable thing, and it is a cutting edge Open Science best practice. Thus we value Professors Crane and Martin's contributions greatly and have requested that they keep 50% of the NFT sale from the auction above. They have also agreed to test the SplitStream and for the purposes of this incentive test, their analysis “cites” two NFTs:

• The NFT of the Open Science Test of Seth’s Appetite Theory (currently owned by Molecule)

• The NFT of this Essay Outlining the Protocol (owned by Planck)

Planck will then split our proceeds further to what we are citing:

-Mirror because we are using their amazing platform and tech. -This Artwork is Always on Sale, suggested by Simon De La Rouvier as the proper target for the citation of his shared idea of Harberger taxes for NFT ownership (which is an important aspect of our protocol.)

And so the Split you saw in the Block above also Splits to this:

Planck Root Split

And we encourage the recipients of these proceeds, if they are at all substantial, to split back to those they would cite. Let's also note that this is a simple test of the mechanism and certainly does not represent the full range of actual citations we would use.

Special thanks to Patrick Riviera for his help in implementing this. The NFT SplitStream design goes back to a 2018 paper co-authored with Michael Zargham on DAGs for attribution networks, e.g. see this excerpt :

It's a thrill to begin testing it live. If you'd like to read the full essay that describes more about Planck and the creation of the NFT, you should check this out.

Believe it or not, humanity is completely capable of ignoring a $1,000,000,000,000 bill sitting in plain sight. It happened in 1747, when James Lind ran a controlled scientific study — maybe the first ever — and discovered that citrus fruits cured scurvy.

In Lind’s day, scurvy killed more British sailors than "shipwreck, storms, all other diseases, and enemy action combined”. Which is to say that Lind's cure was not just going to save countless lives; it was an incomparably powerful military technology. The stakes couldn't have been higher. And yet, despite having been proven with the most advanced scientific methods the world had ever seen, it was promptly lost for many decades after.

According to British Historian C.C. Lloyd, the British might have “lost the American War of Independence thirty years [after Lind’s study] because his cure was not adopted”. If Lloyd’s suggestion is correct, the discounted net assets of America is what gives you a roughly $1,000,000,000,000 bill that the British may have just left lying on the ground.

We will return to why and how this happened later. But for now let’s just observe that the incentives for the production and dissemination of scientific truths are often really, really poor. And so, as a result, humanity can lose even the most consequential truth.

Enter NFTs

The idea that NFTs could help rescue enormous scientific truths from obscurity might strike you as a little fanciful. You might even think... "aren't NFTs just some hyped-up blockchain art thing? Why should they help science funding at all?" So to start with let's take the simplest argument, and here we'll just quote it from our 2018 essay on NFTs for Science:

Historically, great knowledge is valued like great art. Bill Gates paid $40 million for Leonardo Da Vinci’s Codex Leicester. Einstein’s manuscripts sell for millions. And a single page of Darwin’s writing fetches hundreds of thousands of dollars[...] People buy Darwin’s original pages because they are connected to his idea — the fact that information from The Origin of Species is freely available is not a bug for its high value; it’s a feature. Today’s Darwin would type The Origin of the Species in a Google Doc or a versioned LaTeX file... But now with Planck, and the digital scarcity blockchain enables, she would create a unique Glyph [NFT] that serves as that first manuscript copy.

This "science as art" argument received some validation last month when we sold the first scientific result NFT (for $24,000). But we believe that this is just the beginning, and have been testing ways in which funds and proceeds from NFTs can be channeled to improve science funding more broadly. The aim, ultimately, is to enable progress and to try to help save some of the consequential ideas we might otherwise lose.

Within this essay we are auctioning off an NFT as a small test of the SplitStream, and incentive design for funding science through citations. To explain, let us first outline the project this NFT is a part of. Last month, after designing and crowdsourcing the first ever randomized control test of a long-untested theory, Planck sold the result as the aforementioned first science NFT. These funds will help us run a replication of the study we ran. Here is something nice that a very smart person said about the project:

Because we are interested in incentives for consequential ideas that it seemed possible we might lose, we looked for a promising candidate for the test. The most promising candidate we found was the late Berkeley Professor Seth Roberts' appetite theory.

Testing Seth Roberts' Appetite Theory

In 2004, Berkeley Professor Seth Roberts discovered that consuming flavorless calories reduced his appetite. Consuming flavorless or unfamiliar calories made his eating habits more consciously controllable and helped him lose weight. And beyond weight loss, such a tool for conscious eating seemed to have the potential to help people eat more nutritious food, more easily go vegan, etc. Though preliminary, it was an enormous discovery.

Seth was a serious empirical scientist and the evidence he published for his theory was intriguing, if unorthodox. But some very credible sources recognized the merit of his work and he was featured positively in the NYTimes. His book became a bestseller.

Glowing anecdotes appeared, including a notable one from Reddit co-founder Aaron Swartz. In that essay, Swartz confidently alludes to the "clinical trials" that would surely be carried out on Seth's Theory. His essential optimism, his confidence that the world would obviously figure out a way to run a clinical test on something so promising, is striking.

But the lab studies never came.

Within 5 years of its publication Seth’s idea had become little-discussed, never having undergone a single clinical trial. Some important outlets like Marginal Revolution LessWrong, and StatModeling kept the flame alive, but the discussion of Seth's theory all but vanishes:

By 2017, a few years after Seth had passed away, Neurobiologist Stephan Guyenet wrote that he expected to remain forever “puzzled” by Seth’s theory because “some sort of research” on it was “unlikely to ever happen.” Stephan’s answer reads more than a bit tragic; obesity kills millions each year, interest in using conscious eating to help improve the world, as in vegetarianism, is skyrocketing. Failing to follow up on a promising theory in such a world feels a bit like an echo of our tragic failure to follow up on James Lind's scurvy cure.

Why Do We Lose Ideas?

"Show me the incentive and I'll show you the result." - Charlie Munger

James Lind's scurvy cure didn't mesh well with the science of 1747. Science was then 150 years away from discovering vitamins and so, naturally, it would have been hard to understand how it was the vitamin C in citrus that was the cure. The top minds of the day, viewing Lind's results, quickly came to believe that the acid in the juice must be melting some big black scurvy blob that sailors got in their stomachs. "Great!" they said, "let's boil the juice to make it more acidic and work even better!"

Unfortunately, as we now understand, boiling the juice just destroys the Vitamin C content. Which means the boiled "cure" was no cure at all. Now there is nothing wrong about this; it's just good old normal science seeking understanding and trying out hypotheses. And 150 years later this did give us understanding, and that understanding was bigger than a simple cure for scurvy. The problem is that somehow for the intervening 150 years everyone didn't just go back to using the limes that were proven to work.

If Seth’s Theory proves out I think the story will be much the same as Lind's. Theories, like those of Seth Roberts and James Lind, which happen to integrate poorly with existing science of their day are bound to suffer. By failing to integrate into science they lose out on what is surely humanity's best protocol for rewarding, preserving, and developing openly shared knowledge. Patents might offer an alternative, but Seth's and Lind's theories were also hopelessly unpatentable. Citrus fruits are freely available and "flavorless calories" are easier to come by still; like a good scientist, Seth even set about demonstrating that a person could just hold their nose as they ate and get the desired effect. Good luck writing that patent.

Demonstrating How NFTs can Help Fund Unpatentable Science

When we first wrote about using NFTs as a unique way to fund science, Seth's was one of the major motivating cases. Here's how the simplest mechanism was intended to help fund such research:

1. NFTs of high-potential scientific work are sold

2. These NFTs, like a collectible, could grow in stature and value as the scientific work was validated

3. Prospective NFT sales of early scientific results could thereby profitably fund the validation of that research

As mentioned earlier, our current project is bearing this out: Planck crowdsourced the first ever randomized control trial of Seth Roberts' appetite theory, sold an NFT of the result, and are now using the proceeds to run an independent lab replication of the findings.

It's important to keep in mind the bigger picture here though. We hope Seth's theory is true (who wouldn't?), but our fundamental concern regards the incentives themselves. To become a full-fledged scientific truth a theory needs to be exposed to falsification. So it's worth remembering that, while our preliminary results on Seth's Theory are promising, every step along the journey is important, as are the incentives to take those steps.

In this essay, we are introducing a novel incentive structure for scientific funding that uses citations as a channel for funding. We were calling this a "CitationStream" but piggybacking on Jon-Kyle's terminology in his excellent essay, we are going to call it a “SplitStream”. The SplitStream is a system in which portions of an NFT sale may flow to some or all of the works the NFT cites, with those cited works then sending some of their funds further along to the works they cite, and so on.

The SplitStream

You might know the quote “If I have seen further, it is from standing on the shoulders of giants”. You might also know that it’s from Isaac Newton, a giant if there ever was one. So in science, giants tend to look down and see other giants. Citations, when they work, map those dependencies backwards through time.

Citations on citations.

Giants all the way down.

If you send funds through these citations, you get a cascade. A stream of splits. A SplitStream.

Here’s what it looks like:

We ran a test of this with an NFT of an independent data analysis of Seth’s Appetite Theory, selling for $4,200. We suspect this was the first ever funding of an independent data analysis! As a part of this independent analysis we were able to demo a powerful cryptographic technology from Aleo which we believe will be very useful to further open science. We used a Zero-knowledge Proof in Leo to enable independent statisticians to effectively "query" our dataset and see certain results without revealing the data itself.

Independent Analysis is a really valuable thing, and it is a cutting edge Open Science best practice. The analysis was conducted by two esteemed professors of statistics, Harry Crane and Ryan Martin, and thus the NFT was theirs with proceeds directed according to them. We requested that they keep 50% of the NFT sale but they agreed to test the SplitStream and, for the purposes of this incentive test, their analysis “cites” two NFTs:

The NFT of the Open Science Test of Seth’s Appetite Theory (currently owned by Molecule) The NFT of the Splitstream Protocol (owned by Planck)

Planck then split our proceeds further to what we are citing:

1. Mirror because we are using their amazing platform and tech.

2. This Artwork is Always on Sale, suggested by Simon De La Rouvier as the proper target for the citation of his shared idea of Harberger taxes for NFT ownership (which is an important aspect of our protocol.)

We encourage the recipients of these proceeds, if they are at all substantial, to split back to those they would cite. Let's also note that this is a simple test of the mechanism and certainly does not represent the full range of actual citations we would use. Here is the NFT, an elegant violin plot of the results from the study we ran:

Token #2837

Design Challenges for the SplitStream

As a trained academic, I could hardly discuss a mechanism like the SplitStream without noting some potential pitfalls. Properly done, this has great potential to reward an effective division of labor in for open science and more. But it does not create obligations, or promises, or contracts, or anything like that. Participants are playing, roughly speaking, a live trust game.

And in fact, these incentives cannot become too enshrined and formal because citations are a fragile system. A person’s inspiration is purely their private knowledge and thus it must be shared voluntarily. A system which can't elicit honest attributions will fail.

For example, you could imagine that many people might appreciate being credited as the essential inspiration for a new Nobel-prize winning discovery in physics. Someone with sufficient resources, some prestige-hungry Jeff Bezos, might even be willing to pay for that honor. And then, of course, there’s nothing to stop our Nobel-winning physicist from claiming that her passing conversation with the dear leader Bezos was the fundamental inspiration for everything. Who could say otherwise? This sort of thing is absolutely going to happen sometimes, just as it sometimes happens in academia.

I’m going to call these types of behaviors “Mao effects”: the seeking of favor from those with status or power by over-attributing to them. Mao of course was named the “great helmsman”, the “great leader”, etc. and anything good that happened was often attributed to him. A network overtaken by these Mao effects breaks down, a Ponzi-scheme for those who claim complete originality.

In an evolutionary simulation it roughly looks like this:

These effects can get more subtle as well. I can’t do much more here than sort of gesture at this and signal that I take these ideas seriously (e.g. I actually coauthored a Behavioral Economics literature review called “When Do Monetary Incentives Backfire”). But a simple step toward preventing Mao Effects is observing the following two rules:

1. Favor citing things which are publicly shared.

2. Favor citing things which also cite.

The first condition helps provide a level of transparency and sense-making to the system. So, for instance, you can understand why I cite Mirror because you can clearly see that I'm using their tech. The second condition helps ensure that cited works offer further attribution to the work they've built on. Together these rules help ensure that a would-be Mao openly shares their knowledge while also citing that which contributed to it. More is needed if we are to one day get this right, but we hope it's a start.

Twitter @stephensonhmatt p1anck.com