SingularityNET

RFP Owner

Reputation and voting simulation tool

Type SingularityNET RFP
Total RFP Funding $50,000 USD
Proposals 0
Awarded Projects n/a

Overview

Est. Execution Time
⏱️ Up to 3 months
Proposal Winners
🏆 Single
Max Funding / Proposal
$50,000 USD

RFP Details

Short summary
Main purpose
Long description
Preconditions
Main evaluation criteria
Other resources

Short summary

We are rethinking our design for voting weights and Community Engagement Scores, based on a wide range of parameters.

Main purpose

We are rethinking our design for voting weights and Community Engagement Scores tool, based on a wide range of parameters. The tool will help us make better, grounded decisions on the design and help us to define optimal configuration in the first and following Deep Funding Voting rounds. Use cases:

Experiment with the impact of different data sets, algorithms, and configurations to get a better understanding of how they influence each other.
Simulate the outcomes, so we can detect risks and determine the best configuration of weights before using it in a production environment.
After the first launch, we can continue to improve the simulations and test new data sources, algorithms, and configurations.
The tool can be used as a ‘marketing instrument’ to explain to third parties what the benefit is of our approach to voting weights and reputation/contribution scores, why we are using certain metrics and configurations, and enable them to experiment based on their own context.

Long description

In our new design, we are considering to introduce fundamentally new parameters to calculate the outcome of a voting event. We would like to have a better understanding of how different metrics may influence each other. Some examples: Scenario 1: Measuring ‘strength of conviction’ We may introduce ‘strength of conviction’ by giving every voter a limited number of credits to distribute over the proposals, to indicate what proposals they feel most sure or passionate about. We will apply a quadratic rebalancing of the weights so that very singular strengths (all credits on one proposal) will lead to a lower overall voting weight than more equal distributions. At the same time, we are currently also using ‘grade voting’, scoring each proposal from 1-10. This initiative would align our voting methods with the Quadratic Voting research results that demonstrate facilitation of collaborative plural communities through accurate balancing of majorities making modest investments in their convictions with minorities making strong investments. Questions to research:

How will these different metrics influence each other?
How will this impact vary when having smaller or larger voting groups?

Scenario 2: Discovering correlations We are aiming to introduce ‘correlations’ as a metric for voting weights. Correlation can be measured based on outcomes (voting behavior) or based on wallet interaction between voters. (Transactional behavior). Potentially also based on interactions on the Proposal portal. We expect that such measurement will help us to indicate sybil attacks (wallet splitting to increase voting weight) and other ‘group’ behavior. We would like to give individuals who form their opinions independently a higher weight than organic or orchestrated group actions. Questions to research:

How should these different metrics be balanced
What impact should they have on voting weight?

Scenario 3: We are currently using a pretty simple algorithm for ‘contribution scores’. Based on points that are assigned to certain activities. What would be the impact if we applied a ‘Weighted Liquid Rank’ to these interactions? Questions to research:

How will Weighted Liquid Rank influence contribution scores?
What are the optimal configurations for this

Other questions to assess:

With these metrics in place, is there still a need for identification? (identifying as a unique human being)
What risks are there for gaming the system? How can we make the system optimally resistant to gaming strategies?
Use case-specific advice: what are the best metrics to use under different circumstances?
Often success comes from well-functioning teams or groups rather than just individual contributions. How can we leverage ratings for groups that collaborate successfully ‘as a group’ (and offset this against the lower weights related to correlated behavior?)

Available resources apart from funding

Research and advice from SingularityNET and the Photrek team

Preconditions

The simulation tool should be aligned with the design of the Customer Engagement Score tool, currently worked on by Photrek. This means initially the specified data sources, configurations and approaches of the team should be part of the simulation process. But it can also work the other way around where insights or ideas from the simulation team will incur changes in the design of the CES tool.

Functional requirements

Ideally, the tool would be able to consume historical data for running simulations. But this is not a hard requirement
The tool should be able to consume future real data sources, to run alternative scenarios based on this data
Ideally, a business user should be able to make different configurations on a dataset and assess the impact on the outcomes. This is not a hard requirement and could be done in the next iteration.
Ideally, the tool should be able to work with the following datasets
- Voting results including wallet collections from our wallet-linking tool
- Output from our new Proposal platform in CSV format

This is not a hard requirement, since synthetic data could be used and should be used to simulate events with more participants

Other datasets such as blockchain transactions could be synthetic or real, to be specified in the proposal
The tool should be able to assess all scenarios outlined above.

It is ok to define a proposal with a smaller scope than outlined above, as long as this is clearly defined and reflected in a good value for cost balance (simpler tools should have lower budget requirements References Lalley, Steven P., and E. Glen Weyl. 2014. “Quadratic Voting.” https://www.aeaweb.org/conference/2015/retrieve.php?pdfid=3009&tk=BHDG8H2E. Miller, Joel, E. Glen Weyl, and Leon Erichsen. 2022. “Beyond Collusion Resistance: Leveraging Social Information for Plural Funding and Voting.” SSRN Scholarly Paper. Rochester, NY. https://doi.org/10.2139/ssrn.4311507. Posner, Eric A, and E Glen Weyl. 2015. “Voting Squared: Quadratic Voting in Democratic Politics.” Vanderbilt Law Review 68 (2). https://scholarship.law.vanderbilt.edu/cgi/viewcontent.cgi?article=1176&context=vlr. Posner, Eric A., and E. Glen Weyl. 2018. “Radical Markets: Uprooting Capitalism and Democracy for a Just Society.” In Radical Markets. Princeton University Press. https://doi.org/10.23943/9781400889457.

Preconditions

Main evaluation criteria

Functional requirements

Ideally, the tool would be able to consume historical data for running simulations. But this is not a hard requirement
The tool should be able to consume future real data sources, to run alternative scenarios based on this data
Ideally, a business user should be able to make different configurations on a dataset and assess the impact on the outcomes. This is not a hard requirement and could be done in the next iteration.
Ideally, the tool should be able to work with the following datasets
- Voting results including wallet collections from our wallet-linking tool
- Output from our new Proposal platform in CSV format

This is not a hard requirement, since synthetic data could be used and should be used to simulate events with more participants

Other datasets such as blockchain transactions could be synthetic or real, to be specified in the proposal
The tool should be able to assess all scenarios outlined above.

Technical requirements

The technical scope of the tool can vary, and we want to keep this open for the proposers. Different strategies would be:

Purely mathematical tool based on synthetic data
Mainly mathematical tool with real-world data
Agent-based simulation scenarios (preferred)

Non-functional requirements

The solution should be well documented and have a high flexibility for future extensions and changes, potentially by third parties.
The tool is well-tested and reliable.
The tool is coded in a common programming language
There should be no proprietary code involved or other vendor lock-ins. Open source is preferred.

Description of the main assessment criteria of this RFP

There is a wide variety of solutions possible. We invite all proposers to come up with their own approaches and ideas, but we expect a reasonable balance between cost and value. We reserve the right to filter out proposals from the voting process that are -in our subjective opinion- not offering enough value or are too highly-priced for the value they are providing.
Willingness to work closely with Photrek and other teams that are working on components of the Reputation and Voting platform

Other resources

Research results and advice from SingularityNET and the Photrek team

RFP Status

Completed & Awarded

The community and public are invited to view the full proposals and give feedback. During this time the RFP committee will doing their formal selection process to award winning proposals.

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