+1 -1

Decentralized Protocols.md

··· 55 - Self-sovereign identity: the user is in control of their identity. 56 - Privacy-preserving: the user's identity is not shared with third parties. 57 - Sybil-resistant: identity is subject to scarcity; i.e., creating more identifiers cannot be used to manipulate a system. 58 - - Two big unsolved problems on decentralized mechanism design are identity (making sure that the same person can't have multiple identities) and collusion (making sure groups cannot coordinate to manipulate the system). 59 - Identity can be delegated to a community. E.g: Gitcoin uses Passport because they know what the identity requirements are for that community. Solving identity at a global scale means "[seeing like a state](https://newsletter.squishy.computer/p/soulbinding-like-a-state)" and distorting the messy reality. 60 - What we call "on-chain identity" is really "on-chain legibility" - a standardized, certified, registered system that simplifies complex human identity into quantifiable data points, similar to how scientific forestry reduced complex ecosystems to countable rows of trees. 61 - The solution is "Keys not IDs" - focus on what users are authorized to do rather than who they are, using public-key cryptography for authorization without the baggage of permanent identity tracking.

··· 55 - Self-sovereign identity: the user is in control of their identity. 56 - Privacy-preserving: the user's identity is not shared with third parties. 57 - Sybil-resistant: identity is subject to scarcity; i.e., creating more identifiers cannot be used to manipulate a system. 58 + - Two big unsolved problems on decentralized [[Mechanism Design]] are identity (making sure that the same person can't have multiple identities) and collusion (making sure groups cannot coordinate to manipulate the system). 59 - Identity can be delegated to a community. E.g: Gitcoin uses Passport because they know what the identity requirements are for that community. Solving identity at a global scale means "[seeing like a state](https://newsletter.squishy.computer/p/soulbinding-like-a-state)" and distorting the messy reality. 60 - What we call "on-chain identity" is really "on-chain legibility" - a standardized, certified, registered system that simplifies complex human identity into quantifiable data points, similar to how scientific forestry reduced complex ecosystems to countable rows of trees. 61 - The solution is "Keys not IDs" - focus on what users are authorized to do rather than who they are, using public-key cryptography for authorization without the baggage of permanent identity tracking.

+1 -1

Evolution.md

··· 7 2. Heredity 8 3. Selection 9 - Evolutionary systems often generate unexpected solutions. [Nature selects for good enough](http://gordonbrander.com/pattern/evolution/). It affects almost everything (life, [[ideas]], communities, [[systems]], ...). 10 - - Nature ended up: resilient to disturbances, decentralized, redundant, diverse, and self-healing. 11 - Every [[culture]] is the gradual accumulation of useful environmental adaptations combined with random memetic drift. 12 - [[Systems]] that evolve organically are usually, [but not always](https://slatestarcodex.com/2017/03/16/book-review-seeing-like-a-state/), well-adapted to their purpose. Cultures, ancient traditions, and long-lasting institutions contain irreplaceable wisdom that's hard to pin down if you're designing them from scratch.

··· 7 2. Heredity 8 3. Selection 9 - Evolutionary systems often generate unexpected solutions. [Nature selects for good enough](http://gordonbrander.com/pattern/evolution/). It affects almost everything (life, [[ideas]], communities, [[systems]], ...). 10 + - Nature ended up: resilient to disturbances, [[Decentralized Protocols|decentralized]], redundant, diverse, and self-healing. 11 - Every [[culture]] is the gradual accumulation of useful environmental adaptations combined with random memetic drift. 12 - [[Systems]] that evolve organically are usually, [but not always](https://slatestarcodex.com/2017/03/16/book-review-seeing-like-a-state/), well-adapted to their purpose. Cultures, ancient traditions, and long-lasting institutions contain irreplaceable wisdom that's hard to pin down if you're designing them from scratch.

+1 -40

Incentives.md

··· 6 7 > _"Simple, clear purpose and principles give rise to complex and intelligent behavior. Complex rules and regulations give rise to simple and stupid behavior"._ Dee Hock. 8 9 - - To reach a [[Goals|goal]], reduce friction or increase incentives/rewards. 10 - To build better institutions, alter the incentive landscape. Great incentives create great outcomes. 11 - Humans are astonishingly bad at establishing incentives—we consistently invite manipulation and unintended consequences. 12 - You can't force other people to change. You can, however, change just about everything else. And usually, that's enough! ··· 30 4. **Stakes & Effects**. Consider the stakes. If the failures are costly and the decisions hard to reverse, conduct a heavier analysis. 31 5. **Skin in the Game**. To avoid principal-agent problems, the incentive designer should have skin in the game. Never allow an incentive to be implemented where the creator participates in pleasure of the upside, but not the pain in the downside. Skin in the game improves outcomes. 32 6. **Clarity & Fluidity**. An incentive is only as effective as the clarity of its dissemination and the ability and willingness to adjust it based on new information. Create even understanding playing fields for all constituents and avoid plan continuation bias. 33 - 34 - ## Mechanism Design 35 - 36 - Mechanism design is the study of how incentives are created to achieve desired outcomes. It focuses on the design of [[Systems]] and [[Processes]] to achieve desired outcomes. [Mechanisms are algorithms plus incentives](https://balajis.com/p/credible-neutrality). 37 - 38 - A mechanism is a tool that takes in inputs from multiple people, and uses these inputs as a way to determine things about its participants' values, so as to make some kind of decision that people care about. In a well-functioning mechanism, the decision made by the mechanism is both efficient - in the sense that the decision is the best possible outcome given the participants’ preferences, and incentive-compatible, meaning that people have the incentive to participate "honestly". 39 - 40 - - Software is eating Mechanism Design. Incentives can be encoded in [[blockchain|blockchains]]. 41 - - The simpler a mechanism is, and the fewer parameters a mechanism has, the less space there is to insert hidden privilege for or against a targeted group. If a mechanism has fifty parameters that interact in complicated ways, then it's likely that for any desired outcome you can find parameters that will achieve that outcome. 42 - - Fewer knobs makes it more resistance to overfit (to your world view and use case) and corruption. 43 - - The best engineering designs are those that remove things and make them implicit. 44 - - Remember to keep fast [[Feedback Loops]] in mind when designing mechanisms. 45 - - Mechanism design flips game theory: choose rules (outcomes & payments) so strategic agents reach desired outcomes. 46 - - An agent's "type" is their private information that determines how much they value each possible outcome (e.g: a bidder's valuation for an item). 47 - - In quasilinear settings (utility = value − payment), mechanisms map reported types to decisions and transfers. 48 - - The Revelation Principle lets us focus on direct, truth-telling mechanisms: DSIC (dominant strategies) or BIC (Bayes-Nash). 49 - - Gibbard–Satterthwaite impossibility: with three or more options and unrestricted preferences, only dictatorial DSIC choice functions exist. 50 - - Top Trading Cycles yields Pareto-efficient, individually rational, strategyproof allocations in exchange problems. 51 - - Most bits of information in the output of a mechanism should come from the participants' inputs, not from hard-coded rules inside of the mechanism itself. 52 - - A good mechanism is also a mechanism that actually does solve the problems that we care about. If it can't be done completely neutrally, it doesn't mean it should not be done at all. 53 - - Any mechanism that can help genuinely under-coordinated parties coordinate will, without the right safeguards, also help already coordinated parties (such as many accounts controlled by the same person) [over-coordinate](https://vitalik.eth.limo/general/2019/04/03/collusion.html) with potential ways to "do wrong" (e.g: extract money from the system). 54 - - You can increase mechanism complexity if you trade it off for identity or collusion resistance. If you figure out a way to make it the mechanism identity resistant then, it'll support more complex setups. 55 - - [Truthtelling games](https://jonathanwarden.com/truthtelling-games/) can incentivize honesty through coordination games where participants win by giving the same answer as others, with truth serving as a powerful Schelling point (truthtelling is the winning strategy only if everybody else tells the truth). Information elicitation mechanisms can get people to reveal private/subjective information truthfully even without verification. 56 - 57 - ### Examples 58 - 59 - - Democracy. The input is votes, the output is who controls each seat in the government that was up for election. 60 - - Blockchain-awarded incentives for proof of work and proof of stake. The input is what blocks and other messages participants produce, the output is which chain the network accepts as canonical, and rewards are used to encourage "correct" behavior. 61 - - Auctions. The input is bids, the output is who gets the item being sold, and how much the buyer must pay. 62 - - [Vickrey–Clarke–Groves auction](https://en.wikipedia.org/wiki/Vickrey%E2%80%93Clarke%E2%80%93Groves_auction). 63 - - [Second-price auction](https://en.wikipedia.org/wiki/Generalized_second-price_auction). 64 - - Quadratic voting and funding as a way of coming to agreement on matters of governance and [[Public Goods Funding]]. 65 - 66 - ### Resources 67 - 68 - - [Jonathan Warden's blog](https://jonathanwarden.com) 69 - - [Sam Harsimony's Substack](https://substack.com/@splittinginfinity) 70 - - [Victor Sint Nicolaas' blog](https://victorsintnicolaas.com/) 71 - - [Allocation Mechanisms](https://www.allo.expert/mechanisms)

··· 6 7 > _"Simple, clear purpose and principles give rise to complex and intelligent behavior. Complex rules and regulations give rise to simple and stupid behavior"._ Dee Hock. 8 9 + - To reach a [[Goals|goal]], reduce friction or increase incentives/rewards (basic [[Mechanism Design]]). 10 - To build better institutions, alter the incentive landscape. Great incentives create great outcomes. 11 - Humans are astonishingly bad at establishing incentives—we consistently invite manipulation and unintended consequences. 12 - You can't force other people to change. You can, however, change just about everything else. And usually, that's enough! ··· 30 4. **Stakes & Effects**. Consider the stakes. If the failures are costly and the decisions hard to reverse, conduct a heavier analysis. 31 5. **Skin in the Game**. To avoid principal-agent problems, the incentive designer should have skin in the game. Never allow an incentive to be implemented where the creator participates in pleasure of the upside, but not the pain in the downside. Skin in the game improves outcomes. 32 6. **Clarity & Fluidity**. An incentive is only as effective as the clarity of its dissemination and the ability and willingness to adjust it based on new information. Create even understanding playing fields for all constituents and avoid plan continuation bias. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

+38

Mechanism Design.md

··· 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

··· 1 + # Mechanism Design 2 + 3 + Mechanism design is the study of how incentives are created to achieve desired outcomes. It focuses on the design of [[Systems]] and [[Processes]] to achieve desired outcomes. [Mechanisms are algorithms plus incentives](https://balajis.com/p/credible-neutrality). 4 + 5 + A mechanism is a tool that takes in inputs from multiple people, and uses these inputs as a way to determine things about its participants' values, so as to make some kind of decision that people care about. In a well-functioning mechanism, the decision made by the mechanism is both efficient - in the sense that the decision is the best possible outcome given the participants’ preferences, and incentive-compatible, meaning that people have the incentive to participate "honestly". 6 + 7 + - Software is eating Mechanism Design. Incentives can be encoded in [[blockchain|blockchains]]. 8 + - The simpler a mechanism is, and the fewer parameters a mechanism has, the less space there is to insert hidden privilege for or against a targeted group. If a mechanism has fifty parameters that interact in complicated ways, then it's likely that for any desired outcome you can find parameters that will achieve that outcome. 9 + - Fewer knobs makes it more resistance to overfit (to your world view and use case) and corruption. 10 + - The best engineering designs are those that remove things and make them implicit. 11 + - Remember to keep fast [[Feedback Loops]] in mind when designing mechanisms. 12 + - Mechanism design flips game theory: choose rules (outcomes & payments) so strategic agents reach desired outcomes. 13 + - An agent's "type" is their private information that determines how much they value each possible outcome (e.g: a bidder's valuation for an item). 14 + - In quasilinear settings (utility = value − payment), mechanisms map reported types to decisions and transfers. 15 + - The Revelation Principle lets us focus on direct, truth-telling mechanisms: DSIC (dominant strategies) or BIC (Bayes-Nash). 16 + - Gibbard–Satterthwaite impossibility: with three or more options and unrestricted preferences, only dictatorial DSIC choice functions exist. 17 + - Top Trading Cycles yields Pareto-efficient, individually rational, strategyproof allocations in exchange problems. 18 + - Most bits of information in the output of a mechanism should come from the participants' inputs, not from hard-coded rules inside of the mechanism itself. 19 + - A good mechanism is also a mechanism that actually does solve the problems that we care about. If it can't be done completely neutrally, it doesn't mean it should not be done at all. 20 + - Any mechanism that can help genuinely under-coordinated parties coordinate will, without the right safeguards, also help already coordinated parties (such as many accounts controlled by the same person) [over-coordinate](https://vitalik.eth.limo/general/2019/04/03/collusion.html) with potential ways to "do wrong" (e.g: extract money from the system). 21 + - You can increase mechanism complexity if you trade it off for identity or collusion resistance. If you figure out a way to make it the mechanism identity resistant then, it'll support more complex setups. 22 + - [Truthtelling games](https://jonathanwarden.com/truthtelling-games/) can incentivize honesty through coordination games where participants win by giving the same answer as others, with truth serving as a powerful Schelling point (truthtelling is the winning strategy only if everybody else tells the truth). Information elicitation mechanisms can get people to reveal private/subjective information truthfully even without verification. 23 + 24 + ### Examples 25 + 26 + - Democracy. The input is votes, the output is who controls each seat in the government that was up for election. 27 + - Blockchain-awarded incentives for proof of work and proof of stake. The input is what blocks and other messages participants produce, the output is which chain the network accepts as canonical, and rewards are used to encourage "correct" behavior. 28 + - Auctions. The input is bids, the output is who gets the item being sold, and how much the buyer must pay. 29 + - [Vickrey–Clarke–Groves auction](https://en.wikipedia.org/wiki/Vickrey%E2%80%93Clarke%E2%80%93Groves_auction). 30 + - [Second-price auction](https://en.wikipedia.org/wiki/Generalized_second-price_auction). 31 + - Quadratic voting and funding as a way of coming to agreement on matters of governance and [[Public Goods Funding]]. 32 + 33 + ### Resources 34 + 35 + - [Jonathan Warden's blog](https://jonathanwarden.com) 36 + - [Sam Harsimony's Substack](https://substack.com/@splittinginfinity) 37 + - [Victor Sint Nicolaas' blog](https://victorsintnicolaas.com/) 38 + - [Allocation Mechanisms](https://www.allo.expert/mechanisms)

+1 -1

Public Goods Funding.md

··· 7 - All funding mechanisms involve trade-offs between simplicity, robustness, and theoretical optimality. There is no mechanism that [can simultaneously achieve four desirable criteria](https://www.jstor.org/stable/2298018)- 8 - [[Plurality|Different public goods require different funding approaches based on their characteristics and communities]]. 9 - Mathematical optimality matters less than perceived fairness and historical precedent. Ideal funding methods that don't work in practice are not ideal. 10 - - Mechanisms which satisfy different constraints have already been discovered, and it seems unlikely that a different approach will radically change the landscape. Instead, the **bottleneck seems to be in popularizing and scaling existing mechanisms in the real world**. 11 12 ## Desirable Criteria 13

··· 7 - All funding mechanisms involve trade-offs between simplicity, robustness, and theoretical optimality. There is no mechanism that [can simultaneously achieve four desirable criteria](https://www.jstor.org/stable/2298018)- 8 - [[Plurality|Different public goods require different funding approaches based on their characteristics and communities]]. 9 - Mathematical optimality matters less than perceived fairness and historical precedent. Ideal funding methods that don't work in practice are not ideal. 10 + - [[Mechanism Design|Mechanism]] which satisfy different constraints have already been discovered, and it seems unlikely that a different approach will radically change the landscape. Instead, the **bottleneck seems to be in popularizing and scaling existing mechanisms in the real world**. 11 12 ## Desirable Criteria 13