Contributor time incentives
Incentive approach for compensating contributors time spent on executing any idea
Last updated
Incentive approach for compensating contributors time spent on executing any idea
Last updated
Overview
Contributors would provide their personal, professional, contribution history information and expected compensation and suggested duration of contribution when submitting their contributor proposal. If selected the contributor would be paid their compensation amount over the defined period of time such as monthly for six months. Contributors would need to submit a proof of contribution log to provide evidence of the work they’ve done over that period of time to be eligible to receive the next round of compensation. Contributors would be help with addressing priorities by executing ideas that have been suggested and maintained in a separate process. Contributor salary ranges could be suggested as guidance for contributors to consider when making a proposal. Salary lower and upper bound ranges could also potentially be mandated through system parameters. For this example no mandated salary ranges would be applied due to the inherited governance complexity and limitations it could cause in how contributors want to participate.
Very low budgeting complexity (Score - 5)
Budget planning complexity - Contributors only need to state what their expected compensation will be for the period that they would be contributing for. The complexity for budget planning for salaries is reduced by the fact that there is already a lot of market data available about the different roles that exist and the salary ranges they get paid. It is ultimately up to the contributor to determine what they are happy with and the community to decide whether they accept or decline that budget. Contributors will also be able to provide evidence of previous roles and the attached compensation or provide contribution history to help with justifying their compensation request.
Execution scope risks - The scope is time based and only focussed on one individual, meaning there are no risks of the proposal taking longer or shorter than expected. The contributor will simply be compensated for the contribution time that was requested and approved. If the contributor provides evidence that shows their month of contribution effort they will be eligible to receive the next round of compensation.
Voter decision complexity (Score - 5)
Ease of understanding - Voters only need to understand who the contributors are along with any education, professional background and contribution history to make a judgement on how impactful each contributor could be for the ecosystem. Voters would be able to see existing market data about salaries and experience levels and then can compare this information with all of the different contributors. The voters can reuse the same market information to determine if the contributor matches up with the compensation requested and also can easily compare contributors to better inform their decisions.
Ease of comparison - The information being requested by each contributor is similar and easy to structure for making it very easy to compare many contributors. This ease of comparison will make it much easier for voters to select the most promising candidates from a large list of options.
Low governance complexity (Score - 4)
Incentive distribution risks - There aren't any risks around incentive distribution with a contributor time incentive approach as the entire incentive is allocated to a single individual. All of the compensation would be released to the individual after each month's worth of execution efforts are verified. This removes the governance complexity of managing any of the allocated assets as the incentive is not moving through an intermediary step and being distributed between many contributors.
Size of compensation risk - The compensation would only cover an individual's salary meaning there would be less opportunity or incentive for corruption and misuse of funds as the incentive is targeted to one individual's compensation.
Community moderation complexity - There is at least moderate complexity for a community to remove bad actors as the community will need to compare the individuals contribution logs and determine which of those is the worst and of those which do not meet the expected standard. One way to reduce the potential impact of bad actors being selected is to adopt some form of probation period to more easily prevent those contributors from receiving future funding without the need for any community intervention. A key benefit of attaching the incentive directly to the contributors is that if a contributor isn’t performing well on one idea they could redirect their efforts to another idea immediately. This increases the impact of community engagement and feedback with contributors as they could more easily identify any ongoing issues and provide constructive feedback that supports those contributors in generating impact in other areas.
Low game theory risks (Score - 4)
Proposal submissions - It would be difficult to post multiple proposals as a contributor without lying about their background in the other proposals as otherwise all the proposals would be duplicates. If a contributor did try to make multiple submissions it would become more obvious once they start trying to receive funding due to any onboarding checks, video calls or contribution logs. Any attempt to receive funding from duplicate proposals would cause long lasting damage to their reputation.
Proposal details - Contributors are incentivised to exaggerate or lie about their credentials and background to increase their chances of being selected. Some of these claims could be verified by checking with educational entities or previous employers. Over time if verifiable credentials are adopted more widely this will offer one potential solution to this problem around verification. If a contributor lies about their background there is at least a moderate chance that this becomes more obvious during any onboarding or initial contribution outputs.
Execution timeline - Contributors would only be able to request an amount of funding that is based on the time they would be contributing. To receive compensation they would also need to provide contribution log evidence to prove that they had executed work over the previous month so they become eligible for future months. The only thing the contributor could easily do is lie about how much work they did in the month by potentially using other people's efforts masked as their own or exaggerating how long it took to complete their own work. Once caught the contributor would be unlikely to be selected in the funding process again and could also damage their prospects in other ecosystems across the industry.
Execution verification - Contributors could lie about their contribution efforts to attempt to get compensated for work they didn’t do. If this work can be proven to be someone else’s efforts the contributor would have a high risk of causing long term reputation damage that they can’t remove.
Malicious voters - If a handful of voters were trying to benefit themselves or other people they know through their voting behaviour they would struggle to get more funding than they are able to allocate to the individuals that they are trying to support. Those individuals would only be able to request compensation to pay for their salaries.
Voting outcomes - There is a much lower risk of contribution efforts not being directed to novel research and innovation as contributors would not be prevented from identifying and working on any of these areas themself. Contributors are who would be responsible for selecting the most impactful opportunities to work on. Attaching the incentive to contributors helps to remove the need for the wider community to approve every idea that will get executed and gives more autonomy to the contributors who should be well informed enough to judge what areas are most worth spending their time on to try and generate impact for the ecosystem.
Very high contribution flexibility (Score - 5)
Changing an existing idea - A contributor could change an idea as many times as they like as they are being paid for their contribution time. There is no added complexity for contributors to change how an existing idea gets executed.
Contributing to a different idea - A contributor could redirect their efforts for any amount of time to other ideas in the ecosystem if they believe another idea will generate more impact than the current one they are working on. There is no added complexity for contributors to start contributing towards a different idea.
Contributing to a different priority - Same as the above. There is no added complexity for contributors to start contributing towards a different priority.
Incentive complexities - Contributors wouldn't need to come to agreement with any other initiative or spend time considering how much they should be compensated as they will already be allocated the amount the requested for helping with execution efforts.
Moderation complexity - No approval process is needed for contributors to change an existing idea or when they allocate their contribution efforts towards a different idea or priority.
High income stability (Score - 4)
Likelihood of future income - If contributors are selected based of their merits, such as their contribution history and professional background, the chances of being selected for future compensation could be quite high for well performing contributors. Providing contributors are able to provide evidence about their contributions made the chance that high performers get selected again should increase over time as the ecosystems ability to measure contributors performance and impact generated is improved.
Compensation accuracy - Contributors would be paid for their time spent executing ideas that help to execute the funded idea. The compensation would be agreed ahead of time and the contributor could expect high stability over the income they receive whilst they are contributing to the ecosystem.
Total score = 28 / 30
