Community Update — November 16, 2018

The journey through Incentivized Voting Systems

BlockCAT
BlockCAT
Nov 16, 2018 · 5 min read
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Design, design, design.

We’ve been hard at work on the finishing touches for Rewards and the initial steps for the ERC20 creator. Primarily, this has meant heavy UX review, testing with less experienced crypto users and working with the graphic design team to get all the details right.

Photo by geralt from Pexels.
Photo by Pixies from Pexel
  • No incentive to vote in the “plainly obvious” case. This is a more subtle variant of no incentive to vote. If the model relies on redistributing the stake of the incorrect actors, it may be the case that paying gas and the required intrinsic trust in the functionality of the system (i.e., is the code even correct?) disincentivizes participation unless it is likely to be contentious.
  • No (or partial) incentive to share information. In many staking models, the system works best if individuals who possess unique insight are motivated (incentivized) to place their stake and then share their unique insight with other users. An ideal outcome contains a marketplace of information, where better informed users are rewarded for participating in the vote and then sharing their information. In many designs, because users are compensated either solely or partially from the value of the incorrect stakers, the incentive is to convince enough people to win, but not enough to win nothing (optimally convincing just 51% of people). This is a similar misincentivization as the “plainly obvious” problem.
  • Malicious experts. For sufficiently complex problems with certain architectural design, a malicious expert can utilize accrued trust to mislead the community — for example, they may create a subtle, unsecure smart contract, stake a large amount on it and “market” their expertise, causing others to also stake on it. Then, at a future time, they remove their stake and reveal the issue.
  • Privacy and bandwagon effects. In many environments, we would like to see users share their information, but a model which requires a majority vote at some time to decide how to make distribution is subject to bandwagoning effects, especially with a smaller number of participants. For example, if the model distributes stake proportional to the fraction of non-majority voters, if you can observe the current vote state, you may be incentivized to merely vote with the majority, without putting any analytical effort in to the problem at hand.
  • In the iterated model, we can do that repeatedly, where the votes from a second round of voting determine the distributions for the first round — this achieves a strong incentive to reveal and widely distribute the best information, solving both the “plainly obvious” and “51%/49%” problems).
  • By adding delegated votes and allowing users to allocate their value to copy the votes of some expert, we prevent the malicious expert from being able to throw their weight around.

BlockCAT

BlockCAT lets anyone create, manage, and deploy smart…

BlockCAT

BlockCAT lets anyone create, manage, and deploy smart contracts on the Ethereum blockchain — no programming required.

BlockCAT

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BlockCAT

BlockCAT lets anyone create, manage, and deploy smart contracts on the Ethereum blockchain — no programming required. http://blockcat.io

BlockCAT

BlockCAT lets anyone create, manage, and deploy smart contracts on the Ethereum blockchain — no programming required.