How Crypto Solves the Problem of Public Goods (Whitepaper)

Toward a Decentralized Abundance Economy

Table of Contents

  1. Introduction
  2. Background
    - The function of money
    - The problem of public goods
    - Regenerative economics
  3. Theoretical Framework
    - The value of public goods
    - Value-preserving coin inflation
    - Game-theoretic equilibrium
  4. Mechanism
    4.1. Incentive alignment for accuracy
    4.2. Modular protocol
    4.3. Bad actors
    4.4. Expertise Categories
    4.5. Investing in Public Goods
  5. Protocol
    5.1. Step 1: Project Post
    5.2. Step 2: Impact Estimate Post
    - 5.2.1. Project Hash
    - 5.2.2. Timestamp
    - 5.2.3. Estimated Impact Score
    - 5.2.4. Credibility Score
    - 5.2.5. Project Categories
    - 5.2.6. Validation Urgency
    - 5.2.7. Validation Effort Level
    - 5.2.8. Comments
    5.3. Step 3: Waiting Lists
    5.4. Step 4: Validators Selection
    5.5. Step 5: Periodic Validation
    5.6. Step 6: Coin Issuance
  6. Implications
    6.1. Incentivizing Innovation & Collaboration
    6.2. Decentralized Economy
    6.3. Building Capacity
    6.4. Currency Sell Pressure
    6.5. Regional & Community Currencies
  7. Conclusion

1. Introduction

2. Background

The function of money

The problem of public goods

  • Economic efficiency: while this strategy allows a creator to be compensated for their work, it comes at the cost of reduced economic efficiency, since a good that could have been accessible to everyone at virtually no additional cost — an abundant resource — is now only accessible by some. This strategy also stifles further innovation in the area as the original creator can restrict others from capturing value from derived work.

    Not only does this strategy reduce economic efficiency by turning an abundant good into a scarce good, but it also requires ongoing expenditure of resources to preserve the scarcity of the good (and maintain the monopoly power of the good’s creator). In the case of software licenses, for example, various techniques must be implemented to prevent unauthorized individuals from using or copying the software. This is often a never-ending cat-and-mouse game (and thus a never-ending drain on resources), where developers continually design new security schemes that are then promptly foiled by hobbyists and hackers. In addition to private resources, public resources must also be continually expended within the legal system and on law enforcement to preserve the creators’ monopoly power.
  • Limited application: in addition to its economic inefficiency, the strategy is only effective for a subset of public goods (and for a subset of regions). Consider for example a team of researchers that has been working on a cure of a particular disease. After a few years of work the team finds a cure that can lead to extending the lives of 5 million people. Now consider 2 scenarios: in both scenarios the amount of effort by the team is the same and the impact on people’s lives is the same. The only difference is that in Scenario 1 the cure is in the form of a pill, and in Scenario 2 the cure is in the form of a combination of carefully measured ingredients that are readily available in stores.

    Based on this difference alone, in Scenario 1 the team could be making billions, while in Scenario 2 the team may be struggling to cover the costs of conducting the research. The reason for this disparity has nothing to do with the additional effort to produce the pill — it could have been a simple (but non-obvious) tweak to an existing pill. It has everything to do with enforceability — it’s relatively easy to penalize a pharmaceutical company that illegally manufactures a pill; it is however impractical to track and penalize millions of people who “illegally” buy ingredients in specific amounts from stores.

    Now you may say that the team in Scenario 2 can still make money by writing books about their discovery and getting good paying jobs thanks to their research. This is true, but these are all options that are also available to the team in Scenario 1!

    Just like the strategy can only be practically enforced in some cases, it may also not be uniformly enforced everywhere. Countries may have different IP laws, or may not recognize IP claims from another country. Similarly, countries may have limited capacities in enforcing such laws, and pursuing IP claims in such countries may be futile.
  • Perverse incentives: since the market mechanism cannot monetize abundant resources, the advertising model monetizes a scarce resource instead: people’s attention. The problem is that there is no obvious relation between the quality of content and its popularity; a scientific breakthrough may have incredible value but may only catch the attention of a few dozen people. On the other hand, an inane tweet by a celebrity may generate millions of views.

    Content that grabs the most attention tends to be emotionally charged; surprising, outrageous, divisive, or hateful content tends to generate a lot more attention than emotionally neutral or factual content. It also takes a lot less effort to generate factually-inaccurate outrageous content than well-researched quality content — making such content easier to monetize.
    At the same time, social media platforms design their algorithms to maximize profitability; they direct audiences toward content that would make them stay on the platform longer to watch more ads.

    Since everyone in the Attention Economy is competing for limited advertising money, everyone has the incentive to produce (and in the case of platforms, promote) low-quality, attention-grabbing content — not high-quality content.

    The result is that while content creators in the Attention Economy are technically able to monetize content that is available for all to access as a public good, they are in fact economically incentivized to create toxic and socially polarizing content — the exact opposite of a public good!

Regenerative economics

3. Theoretical Framework

The value of public goods

Value-preserving coin inflation

Game-theoretic equilibrium

4. Mechanisms

4.1. Incentive alignment for accuracy

4.2. Modular Protocol

4.3. Bad actors

  • Funding validations: to maintain a permissionless system while avoiding sybil attacks, contributors (or Estimators) will be required to provide funds for the validation process. These funds should be in proportion to the expected impact of the project (since higher impact projects need to be scrutinized more carefully), and would go toward validating the project. If a contributor overestimates the expected impact of the project, she would simply lose the extra funds. If she significantly overestimates the impact of the project (or if the project has no value) she is likely to lose more than she’s likely to make. It is therefore in her economic interest to accurately estimate the expected impact of the project. There is also no benefit to creating multiple accounts in such a system, since the contributor’s expenditure will always be in proportion to the expected impact. The protocol will also have a mechanism for contributors to get funding for submitting projects, so that no one is restricted from submitting legitimate projects due to financial difficulties.
  • Random selection: to prevent bribing or collusion with validators, the protocol will select validators at random, which means that a contributor will not have control over who validates the project.
  • Merit-based validations: Now what about creating multiple accounts to increase the chance of ending up on the list of validators? While it’s true that in a permissionless system any user can create as many accounts as she wants, creating multiple accounts in the Abundance Protocol would bring no benefit to a user since validators are selected based on merit — their domain-specific Impact Score (or “expertise”) in a relevant category (for assessing a project’s credibility and impact), and general Impact Score (for assessing overall impact). Validations are then weighted by the Impact Score of each validator. These Impact Scores are non-transferable between users, which means that the only way to acquire these is by earning them: by either creating public goods or reviewing public goods projects as a Validator. Having one account or three accounts would therefore make no difference, since the amount of effort to generate an Impact Score will still be the same. Similarly, since Validators are selected based on their Impact Score, 3 accounts with an Impact Score of 100 would have a combined equivalent chance to be selected to validate as 1 account with an Impact Score of 300.
  • Time-locked funds: the protocol allows a certain time for anyone to challenge validations after the validation process is concluded. A challenger must provide funding for a new randomized set of validators, as well as present sources for the challenge (merely not liking the results is not enough). During the challenge period funds will be locked in the contract to prevent contributors from “cashing out” their funds.
  • Periodic reviews: following the initial estimation of a project’s impact, there are periodic reviews of the actual impact of the project during that time period. This provides an additional level of integrity to the protocol and allows validators to further refine their estimates based on new data.
  • Ecosystem dynamics: so far, we’ve discussed protocol-based solutions to bad actors, what is equally important however are the ecosystem dynamics that stem from the incentives that the protocol creates; since all participants in the ecosystem have an incentive to keep the integrity of estimates, and people are compensated for creating public goods, participants have an incentive to create AI, ML, and other powerful tools to detect fraudulent activity throughout the ecosystem. This means that even if bad actors develop their own tools to attack the ecosystem, there will always be greater economic incentive to develop public countermeasures.

    Another ecosystem dynamic has to do with collusion among bad actors; the ecosystem creates a strong disincentive to collude because there is a clear incentive in the ecosystem to expose fraud (this too is a public good after all). Since anyone can expose fraud, and be rewarded for doing so by the ecosystem, anyone who participates in a conspiracy can defect and expose all the other bad actors. This makes collusion in the ecosystem very risky and impractical.

4.4. Expertise Categories

4.5. Investing in Public Goods

  1. A proposer (or team) creates a funding request specifying (a) the proposed public goods project (with a detailed description of the work involved), (b) the expected impact of the project once completed, © timeline, (d) project categories, (e) contributors, (f) influencing sources and their expected share of the project (g) other project-relevant details. Proposer also specifies (h) the requested funding amount and (i) maximum percent contribution of the project that the investor will receive. Additional terms may be stipulated regarding milestones and payments.
  2. Funding Request is submitted to a decentralized validation mechanism (that works similarly to the validation process on Estimate posts) along with a validation fee. Validators then estimate the Credibility Score and Expected Impact Score (along with a risk factor) for the project.
  3. Investors can then use the input of validators, along with the on-chain track record (Credibility Scores and Impact Scores) of the proposer (or team) and bid on the project by offering to receive an equal or lower percent of the final project.

5. Protocol

  1. New public goods project is posted to the protocol.
  2. Each estimate for a project is posted to the protocol.
  3. Estimates are sorted by credibility, highest expected impact, and required expertise.
  4. Validators are selected at random to review the estimate.
  5. Validators are periodically selected at random to review realized project impact.
  6. Coins are issued to public goods contributors following each validation (and challenge) period, and based on realized impact.

5.1. Step 1: Project Post

5.2. Step 2: Impact Estimate Post

  1. Project’s on-chain hash.
  2. Timestamp of impact estimate post.
  3. Overall estimated economic impact score of the project.
  4. Project credibility score.
  5. Categories that are most relevant to the project, and the relative importance of the category to the project.
  6. Urgency of validation.
  7. Validation effort level.
  8. Comments

5.2.1. Project Hash

5.2.2. Timestamp

5.2.3. Estimated Impact Score

5.2.4. Credibility Score

5.2.5. Project Categories

5.2.6. Validation Urgency

5.2.7. Validation Effort Level

5.2.8. Comments

5.3. Step 3: Waiting Lists

5.4. Step 4: Validators Selection

5.5. Step 5: Periodic Validation

5.6. Step 6: Coin Issuance

6. Implications

6.1. Incentivizing Innovation & Collaboration

6.2. Decentralized Economy

6.3. Building Capacity

6.4. Currency Sell Pressure

  • Business reputation: the protocol’s integrated on-chain reputation system can facilitate commerce by allowing credible reviews of products — unlike the easily-manipulated reviews we have in online commerce today. The protocol would also allow the development of decentralized dispute resolution mechanisms to minimize fraud, and provide potential customers with data on the proportion of disputed transactions for businesses.
  • Tooling: participants in the ecosystem can expect consistent improvements in freely-provided open-source tools, products and services that facilitate commercial activity, and an active community of developers working to improve these tools.
  • Attracting innovation: since products and services using the protocol are more likely to have credible data available, it would also make it more likely that public goods are developed through the protocol to improve these products and services (since validators will prioritize public goods projects that have more data and are easier to review). This creates an incentive for more and more products to be denominated in the protocol’s native currency.
  • Native currency: since the protocol creates a sustainable business model for open-source projects, it is likely that many of the open-source projects funded through the protocol would integrate its currency into their products, or may even use the currency by default.

6.5. Regional & Community Currencies

7. Conclusion

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How crypto can transform the economy and solves the problem of public goods. Abundance Protocol Whitepaper: http://shorturl.at/lqV37

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Mike Natanzon

How crypto can transform the economy and solves the problem of public goods. Abundance Protocol Whitepaper: http://shorturl.at/lqV37