Authors: E. Glen Weyl, Puja Ohlhaver, Vitalik Buterin

——Chapter 62 of Laozi

"The Taoist is the mystery of all things, the treasure of the good man, and the protection of the bad man"

——Chapter 62 of Laozi

Please check the previous article:

Please check the previous article:More broadly, SBTs allow us to efficiently represent and manage assets and commodities anywhere between fully private and fully public. In reality, even goods consumed by individuals have positive spillover effects, just as enabling consumers to better contribute to households or communities is inevitable even with the most globally available public goods such as climate Land is more useful to some people than others (e.g. Seychelles to Siberia). Likewise, human motivations are rarely entirely selfish or entirely altruistic, and there are many pre-existing patterns of cooperation that are less common in some communities and more in others.

4.8 From private and public goods to composite network goods

More broadly, SBTs allow us to efficiently represent and manage assets and commodities anywhere between fully private and fully public. In reality, even goods consumed by individuals have positive spillover effects, just as enabling consumers to better contribute to households or communities is inevitable even with the most globally available public goods such as climate Land is more useful to some people than others (e.g. Seychelles to Siberia). Likewise, human motivations are rarely entirely selfish or entirely altruistic, and there are many pre-existing patterns of cooperation that are less common in some communities and more in others.

The key is to acknowledge that it actually reflects a partial collaboration that we should take advantage of and compensate for. After all, we are in the business of encouraging collaboration. The trick is to make quadratic mechanisms work with pre-existing cooperative networks, correcting for their bias and tendency to over-coordinate. SBTs provide a natural way for us to tip the scale in favor of cooperation across differences. As the Nobel laureate Eleanor Ostrom has emphasized, the problem is not coordinating public goods per se, but how to help communities of imperfectly cooperating but socially connected individuals overcome their social differences and can coordinate at scale across a wider network.

But instead of seeing pre-existing collaborations as we should"rewrite"The key is to acknowledge that it actually reflects a partial collaboration that we should take advantage of and compensate for. After all, we are in the business of encouraging collaboration. The trick is to make quadratic mechanisms work with pre-existing cooperative networks, correcting for their bias and tendency to over-coordinate. SBTs provide a natural way for us to tip the scale in favor of cooperation across differences. As the Nobel laureate Eleanor Ostrom has emphasized, the problem is not coordinating public goods per se, but how to help communities of imperfectly cooperating but socially connected individuals overcome their social differences and can coordinate at scale across a wider network.

5 Compound Meaning Construction

By revealing membership relationships between different Souls/soulsets, SBTs allow us to discount pre-existing collaborations and expand quadratically in emerging networks, empowering composite items to a wider range of interest groups, And by the consent of diverse members, rather than the consent of innocently over-coordinated (or willfully colluded) special interest groups that give objects a narrow meaning. The precise formulation of the "best" relative discount depends on model details and has not been studied, but we provide experimental first-hand data for further investigation in the appendix.

5 Compound Meaning Construction

Prediction markets are designed to aggregate beliefs based on wealth and risk appetite from those willing to bet. But this "survival of the fittest" is not an ideal way to aggregate beliefs. In a zero-sum game, where one trader's gain is another trader's loss, it assumes that a general predictive ability is wrestled with the "smart ones" rather than the "dumb ones." While wealth may be a proxy for certain abilities and expertise, other forms of related expertise may be more reliable predictors. Participants who lost bets in one domain may have more accurate beliefs in another domain. But prediction markets have the unfortunate effect of instilling conviction in those prone to gamble, enriching those who win bets and impoverishing others, and preventing the general participation of the risk-averse.

Prediction markets take the opposite approach, where people bet on outcomes in the hope of economic gain, relying entirely on the economic incentives of financial speculation ("fructus"), without a comprehensive analysis of bettors' beliefs to produce composable models. At the same time, the conclusions generated by both paradigms are described as"objective"truth. AI models are described as "general purpose" or "universal intelligence," while prediction markets are described as summarizing all beliefs of market participants into a single number: an equilibrium price.

A more fruitful paradigm is to avoid these extremes, and to draw on the strengths of both while compensating for their weaknesses to be richer in breadth. We propose to combine the complexity of nonlinear AI models with the market incentives of prediction markets to transform passive data workers into active data creators. With this wealth of information rooted in the sociality of data creators, DeSoc is able to unleash a web of composite intelligence far more powerful than either approach.

5.1 From prediction market to compound forecast

Prediction markets are designed to aggregate beliefs based on wealth and risk appetite from those willing to bet. But this "survival of the fittest" is not an ideal way to aggregate beliefs. In a zero-sum game, where one trader's gain is another trader's loss, it assumes that a general predictive ability is wrestled with the "smart ones" rather than the "dumb ones." While wealth may be a proxy for certain abilities and expertise, other forms of related expertise may be more reliable predictors. Participants who lost bets in one domain may have more accurate beliefs in another domain. But prediction markets have the unfortunate effect of instilling conviction in those prone to gamble, enriching those who win bets and impoverishing others, and preventing the general participation of the risk-averse.

, and privacy-preserving laws for machine learning, these approaches need to give meaningful economic and managerial benefits to those who generate the data and incentivize them to collaborate in producing models that are more powerful than those they could build alone.

SBTs can unlock a new class of rich models and enable experiments in terms of predictive power and relative expertise. Prediction markets come up with just one number, the price of the contract, and quadratic voting gives each participant the exact belief in the probability of a certain event. SBTs are able to further compute these beliefs in the context of participants' educational credentials, membership, and general sociability to develop better weighted (or non-linear composite) predictive models, likely in new, unforeseen circumstances. A new generation of expert forecasters has emerged at the intersection. So even if polls don't aggregate beliefs well, polls can be studied retrospectively to reveal the characteristics of "more correct" participants and to call in more targeted "experts" in future polls , perhaps in the context of the deliberation team. These mechanisms are closely related to those we advocate in this paper. Quadratic mechanisms discounted by correlation scores can transform poorly coordinated top-down public goods into powerful bottom-up composite network goods. Likewise, they can transform governance systems based on zero-sum prediction markets into more positive-sum decisions that encourage the discovery and synthesis of new and better information.

5.2 From artificial intelligence to composite intelligence

Large-scale nonlinear "neural network" models (such as BERT and GPT-3) can also be converted by SBTs. Such models leverage large amounts of public or private monitored data to generate rich models and predictions, such as codes based on natural language cues. Most of the monitored data creators were unaware of their role in the creation of these models, retained no residual rights for themselves, and were seen as "incidental" rather than key players. Furthermore, data collection takes models out of their social context, which masks their biases and limitations and impairs our ability to compensate for them. These contradictions have come to the fore with increasing demands on data availability and new initiatives such as the"Data collection table", and privacy-preserving laws for machine learning, these approaches need to give meaningful economic and managerial benefits to those who generate the data and incentivize them to collaborate in producing models that are more powerful than those they could build alone.

SBTs provide a natural way to create economic incentive schemes for well-sourced data while giving data creators residual governance rights over their data. In particular, SBTs allow careful and targeted incentives for their data (and data quality) based on the characteristics of individuals and communities. At the same time, modelers can track the characteristics of the collected data and its social context, as reflected in SBT, helping to find contributors who can counteract bias and compensate for limitations. SBTs can also provide customized governance rights to data creators, allowing them to form cooperatives, pool data and negotiate usage. This bottom-up programmability by data creators enables future composite intelligence, where model makers compete to negotiate how to use the same data to build different models. As a result, we move away from a standalone, single "artificial intelligence" paradigm detached from human origins, centralizing unsourced surveillance data, and toward collaboratively constructed composite

Rather than viewing privacy as a transferable property right, a more promising approach is to view privacy as a programmable, loosely coupled bundle of rights that allows accessing, changing, or monetizing information. Under such a paradigm, each SBT (e.g. an SBT representing a credential or accessing a data store) would ideally also have implicit programmable property rights, with access to some of the underlying information that constitutes the SBT such as the holder, their agreements between parties, shared property (such as data), and obligations to third parties. For example, some issuers will choose to make SBTs fully public, but some SBTs, such as passports or health records, will be private in the sense of self-sovereignty, and Souls/soul clusters carrying SBTs have the right to unilateral disclosure. Others, such as SBTs that reflect the membership of data cooperative organizations, involve multiple signatures or more complex community voting permissions, and all or most SBT holders must agree to disclose.

Over time, just as SBTs individualize the Soul/Soul Cluster, they also individualize the Model. Embed data provenance, governance, and economic rights directly into the model's code. Thus, multi-agents, like humans, build a soul embedded in human sociality, and over time, humans are embedded in multi-agents, each with a unique soul that complements the other souls and cooperation. And, at this point, we see a convergence of prediction markets and artificial intelligence paradigms, moving together towards compound sense-making. Combining widely distributed incentives and careful tracking of social context creates diverse models that combine the best of both approaches into a technological paradigm more powerful than either.

5.3 Programmable Composite Privacy

Composite agents raise important questions about data privacy. After all, building such powerful agents requires pooling data across individuals from large datasets (such as health data), or capturing data that is not interpersonal but shared (such as social graphs). Advocates of “self-sovereign identity” tend to treat data as private property: because the data of this interaction is mine, I should be able to choose when to disclose it to whom. However, the data economy is even less understood than the real economy when it comes to simple private property. In simple two-way relationships, such as extramarital affairs, the right to disclose information is usually symmetric and usually requires permission and consent from both parties. As the scholar Helen Nissenbaum has emphasized, the concern is not "privacy" per se, but rather the lack of a complete understanding of the context in which information is shared. The "Cambridge Analytica" scandal is mainly about people leaking their social graph attributes and friend information without their friends' consent.

Rather than viewing privacy as a transferable property right, a more promising approach is to view privacy as a programmable, loosely coupled bundle of rights that allows accessing, changing, or monetizing information. Under such a paradigm, each SBT (e.g. an SBT representing a credential or accessing a data store) would ideally also have implicit programmable property rights, with access to some of the underlying information that constitutes the SBT such as the holder, their agreements between parties, shared property (such as data), and obligations to third parties. For example, some issuers will choose to make SBTs fully public, but some SBTs, such as passports or health records, will be private in the sense of self-sovereignty, and Souls/soul clusters carrying SBTs have the right to unilateral disclosure. Others, such as SBTs that reflect the membership of data cooperative organizations, involve multiple signatures or more complex community voting permissions, and all or most SBT holders must agree to disclose.

and"usus"、"abusus "and"fructus "Combined, they create a subtle cluster of access rights. For example, SBTs could allow computation over data stores (possibly owned and managed by multiple Souls/soul clusters) using specific privacy-preserving techniques. Some SBTs may even allow access to data in such a way that certain calculations are performed, but the results cannot be proven to third parties. A simple example is voting: the voting mechanism needs to count votes for each Souls/soul cluster, but votes should not be proven to anyone else to prevent vote buying.

6 Decentralized society"usus "and"abusus"), while drawing the user's attention ("fructus") auction to the highest bidder, even if it is a robot. SBTs have the potential to manage healthier"attention economy", giving Souls/soul clusters the ability to filter spam from outside their social graph, and possibly even bots, while elevating communication from real communities and desired intersections. Listeners can better know whose voice they are listening to and can better assign credit to those works that inspire insight. This economic model is not optimized to maximize user stickiness, but to create more valuable common goals through positive sum collaboration. This communication channel is also important for security. As mentioned above, "high-bandwidth" communication channels are critical to helping communities build a secure foundation.

6 Decentralized society

Web3 hopes to transform society broadly, not just the financial system. However, today's social structures, such as family, church, team, corporation, civil society, celebrity, democracy, etc., if within the virtual world of broader relationships they support (often called the "metaverse"), If the natives have nothing to represent the human soul, then all this is meaningless. If Web3 eschews persistent identities, models of trust and cooperation, and composable rights and permissions, we'll see Sybil attacks, collusion, and fully transferable private property in limited economic domains, respectively, all of these hyperfinancial trends .

However, DeSoc's greatest strength lies in the composability of its network. Continuously increasing returns and network growth do not simply avoid the danger of rent extraction, but also encourage the proliferation and crossover of nested networks. A road may form a network between two cities. But if cut off from the broader partnership, the two partnering cities end up hitting a ceiling of diminishing returns -- either because of congestion (roads and housing) or exhaustion (reaching the limit of the population they can serve). Only through technological innovation and increasingly extensive cooperation, even if this cooperation is loose. Value continues to grow exponentially only through the cooperation of adjacent networks to obtain new sources of rewards. Some collaborations will be tangible, gradually expanding physical trade across space. But more connections will be informational and digital. Over time, we will see new matrices of collaboration between physical and digital networks, building on and extending the social interconnections they create. It is this intersecting, partially nested, ever-growing network of collaborative structures that span the digital and physical worlds that DeSoc facilitates."Decentralized Society (DeSoc)": A co-determined sociality in which Souls clusters and Communities clusters come together bottom-up as emergent properties of each other to generate composite networked items at different scales.

We emphasize compound network goods as a feature of DeSoc, as the network is the most powerful engine of economic growth, but also the most easily captured by private actors (such as Web2) and powerful governments. Most significant economic growth comes from increased network revenue, i.e. each additional unit of input produces more output. Examples of simple physical networks include roads, power grids, cities, and other forms of infrastructure that are built using labor and other capital inputs. Examples of powerful digital networks include markets, predictive models, and composite intelligence built on data. In both cases, network economics differs markedly from neoclassical economics, which is all about diminishing returns, where output diminishes for every additional unit of input, and private property produces the most efficient outcomes. Private property applied to the situation of increasing returns will have the opposite effect, leading to the phenomenon of limiting the development of the network by extracting rent. A road between two cities can unlock increasing returns from trade gains. But that same private ownership of roads can also stifle growth if landlords choose to extract rents in trade between the two cities. Public ownership of the network also has its own dangers of being easily captured by regulators or underfunded.

Having increasing returns works best when the network is viewed neither as a purely public nor as a purely private good, but as partial and composite public goods. DeSoc provides a social basis for disaggregating and reconfiguring rights--use rights ("usus"), the right to consume or destroy ("abusus") and usufruct ("fructus") -- and enable effective governance mechanisms for these rights to enhance trust and cooperation while checking for collusion and capture. We explore several mechanisms in this paper, such as community-based SALSA and quadratic funding (and voting) with associated score discounts. This act of making compound ownership a third way avoids Charybdis for private rents and Scylla for public regulation.

In many ways, DeFi today is a private property model with diminishing returns transformed into a network with increasing returns. Built on the premise of trustlessness, DeFi is essentially limited to the realm of fully transferable private property (e.g., transferable tokens) that mostly bundles “usus”, “busus” and “fructus”. At best, DeFi risks stifling network growth by charging rent, and at worst, could lead to a dystopian surveillance monopoly dominated by “whales” who harvest and absorb in a race to the bottom Data, just like Web2.

DeSoc transforms DeFi's race to control and speculate on network value into bottom-up coordination to build, participate and govern the network. At the very least, DeSoc's social foundation can make DeFi anti-sybil (support community governance), anti-vampire (internalize positive externalities to build an open source network), and anti-collusion (keep the network decentralized). With DeSoc's structural fixes, DeFi can support and expand a multi-network, broadly empowering interests, as most diverse members agree, rather than further consolidating a network controlled by narrow interests.

However, DeSoc's greatest strength lies in the composability of its network. Continuously increasing returns and network growth do not simply avoid the danger of rent extraction, but also encourage the proliferation and crossover of nested networks. A road may form a network between two cities. But if cut off from the broader partnership, the two partnering cities end up hitting a ceiling of diminishing returns -- either because of congestion (roads and housing) or exhaustion (reaching the limit of the population they can serve). Only through technological innovation and increasingly extensive cooperation, even if this cooperation is loose. Value continues to grow exponentially only through the cooperation of adjacent networks to obtain new sources of rewards. Some collaborations will be tangible, gradually expanding physical trade across space. But more connections will be informational and digital. Over time, we will see new matrices of collaboration between physical and digital networks, building on and extending the social interconnections they create. It is this intersecting, partially nested, ever-growing network of collaborative structures that span the digital and physical worlds that DeSoc facilitates.

secondary title

While we have selectively highlighted the potential that we believe will hopefully be unlocked by DeSoc, it is even more important to remember that almost any technology with this transformative potential will have a similar potential for disruptive change: flames burning, wheels Crushing, TV brainwashing, car pollution, credit card debt framing, etc. Here, the same SBT that can be used to compensate within-group dynamics and enable cooperation across differences can also be used to automatically redline undesirable social groups and even target them for cyber or physical attacks, enforce restrictive immigration policies, or engage in predatory loan. Such possibilities do not stand out in the current web3 ecosystem, as they are not meaningful concepts on a current basis. The benefits of enabling DeSoc also enable the harms. Just as the bad thing about having a heart is that the heart can be broken, the bad thing about having a soul is that it can go to hell, and the bad thing about having a society is that society is often driven by hate, prejudice, violence and fear. Humanity is a great and often tragic experiment.

While we have selectively highlighted the potential that we believe will hopefully be unlocked by DeSoc, it is even more important to remember that almost any technology with this transformative potential will have a similar potential for disruptive change: flames burning, wheels Crushing, TV brainwashing, car pollution, credit card debt framing, etc. Here, the same SBT that can be used to compensate within-group dynamics and enable cooperation across differences can also be used to automatically redline undesirable social groups and even target them for cyber or physical attacks, enforce restrictive immigration policies, or engage in predatory loan. Such possibilities do not stand out in the current web3 ecosystem, as they are not meaningful concepts on a current basis. The benefits of enabling DeSoc also enable the harms. Just as the bad thing about having a heart is that the heart can be broken, the bad thing about having a soul is that it can go to hell, and the bad thing about having a society is that society is often driven by hate, prejudice, violence and fear. Humanity is a great and often tragic experiment.

drving license"drving license") social proof. DeSoc empowers Souls to encode their own relationships and co-create multiple properties, while web2 mediates or monetizes social relationships through opaque algorithms that can create polarization, division and misinformation. DeSoc eschews a top-down, opaque social credit system. Web2 forms their basis. DeSoc sees Souls/soul clusters as agents, while web2 sees Souls/soul clusters as objects."peer to peer") social proof. DeSoc empowers Souls to encode their own relationships and co-create multiple properties, while web2 mediates or monetizes social relationships through opaque algorithms that can create polarization, division and misinformation. DeSoc eschews a top-down, opaque social credit system. Web2 forms their basis. DeSoc sees Souls/soul clusters as agents, while web2 sees Souls/soul clusters as objects.

Using DeFi for social control (without any identity basis) is less risky, at least in the short term. But DeFi has its own dystopia. While DeFi overcomes explicit forms of centralization — i.e., specific actors having a super-level of formal power in a system — it has no built-in way to overcome implicit centralization through collusion and market forces. Monopolies don't always emerge the way Standard Oil used to. Collusion can even occur at higher and more distant levels of an ecosystem. We can see this today with the rise of a group of institutional asset managers. Vanguard, BlackRock, State Street, Fidelity, etc., are the largest shareholders of all the major banks, airlines, auto companies, and other major industries. Since these asset managers hold stakes in all competitors in an industry (e.g., stakes in every major airline), their incentive is to make the companies they hold look like a competitive industry, but their Behaving like a monopoly instead, maximizing the profits and stability of the entire industry at the expense of consumers and the public. [11]

whale"whale"refer to"have"What is actually a bidding war between multiple people for the data of human relationships (such as their social graph) to build a separate private AI that competes with humans, avoiding future competition for multiple AIs that augment human capabilities.

Thus, DeSoc does not need to be perfect to pass the test of acceptable non-utopia. To be a paradigm worth exploring, it just needs to be better than existing alternatives. While it is possible that DeSoc needs to guard against a dystopian scenario, web2 and existing DeFi are slipping into an inevitable dystopian pattern, concentrating power in the hands of elites who either decide social outcomes or own most of the wealth. The direction of web2 is deterministic authoritarianism, accelerating the capacity for top-down surveillance and behavioral manipulation. The direction of DeFi today is nominally anarcho-capitalist, but has been mired in network effects and monopoly pressure, which threatens to turn its mid-term path into authoritarianism in the same way.

DeSoc, by contrast, is a stochastic social pluralism, a network of individuals and communities that, as emergent attributes of each other, collectively determine their own future. From the perspective of web2, the development of DeSoc can be compared to the rise of participatory government popular in monarchies for centuries. Participatory government did not necessarily lead to democracy, it also led to the rise of communism and fascism. Similarly, SBTs do not make digital infrastructure inherently democratic, but compatible with democracy according to what Souls/soul clusters and Communities/community clusters decide together. Opening up this space of possibility is a clear step up from the authoritarianism of Web2 and the anarcho-capitalism of DeFi.

refer to

[8] We say"innocent", because highly cooperative groups will naturally seek to advance their interests, likely for the sake of their collective interest.

[9] Under the quadratic rule, team members can buy a contract that pays $X conditioned on the occurrence of the event, but at a cost of (X^2)/$2. For example, if the event occurs, an individual who sets X=0.5 will receive $0.5, an amount paid by the voter, and in any event pays at least $0.125.

[10] If a person evaluates the probability p, their expected reward Λ is pX and the cost is X^2/2. Taking derivatives on X, the optimal condition is p=X, assuming risk neutrality, which is reasonable for small bets (reward Λ and cost can be arbitrarily reduced or increased, and the same argument still holds).

[11] See Eric Posner, Glenn Weil, Radical Markets: Uprooting Capitalism and Democracy for a Just Society, Princeton University Press, 2018.