Non-actionable/non-deliberated (spam) proposals can be created that diminish the governance system, either with toxic content or impaired usability, and/or lead to unfair voting reward distribution.
Provide a solution that:
- efficiently and effectively detects and removes such proposals.
- is decentralised, scalable and has a clear route for implementation.
- minimises additional network complexity, traffic, and risk.
The problem with reviewing everything
Attempting to remove spam by reviewing every proposal means that everything is suspected of being spam until it is shown to be ‘ham’. Conversely, spam proposals are seen as part of the signal until they are classified otherwise. Both of these come at the cost of increased network traffic and a step toward centralisation by reducing the population size that may have access to a proposal.
Another way to view spam
This proposal aims to reframe spam proposals as a kind of malfunction, or disease, within the system, as they offer no benefit to the network and only act for individual reward or interest.
To efficiently detect this malfunction, every neuron must be able to flag its presence, with the goal of removing it as quickly as possible. Since the infection can be local or systemic, thresholds that trigger a response could be based on the overall number of reports of spam as well as their frequency. In this way, both sudden spikes and steady growth (of spam reports) can indicate that an infection is present.
I suggest creating a separate, parallel pathway that acts to inhibit governance in situations where it would be undesirable for it to function normally. It is triggered by neurons, via a ‘report spam’ button and, when sufficiently activated, acts to prevent the governance system from passing the proposal, until a review process has been completed.
How does it work?
On creation, each proposal has three elements. Two buttons: ‘Accept’ and ‘Reject’ and a ‘Spam’ toggle. The ‘Spam’ button does not vote, but rather flags a proposal as problematic or in need of review. As the number of spam flags rises, or certain conditions are met, the inhibition level rises.
What happens next depends on how many spam reports a proposal has received. If it is the first one, it can trigger some automatic checking for null content, excessive obscenity, or other warning signs.
If the scanning detects something that may be problematic, the proposal is immediately elevated to level 2, which can also happen if it receives more than 10 spam reports (for example). At this level, a group of people (chosen randomly or perhaps named neuron owners) are notified that the proposal may be problematic. This group is invited to perform a quick check of the proposal.
If one or more people in the level 2 group finds an issue, or if the proposal reaches the highest threshold for reporting (say, 100 reports) the proposal is elevated to level 3. At this point the proposal is frozen, its content is blocked and replaced with “under review”, removing it from public view.
Proposals that have been through the review process will have the ‘report spam’ button disabled.
- It is fully responsive. Even a single spam report can trigger action.
- Its implementation does not increase the complexity of the governance system.
- It is only active when triggered by people and can have configurable activation thresholds.
- There is more work upfront to add this layer, compared to simple tweaking the existing governance system.
- The system could be exploited by those who report every proposal, regardless of whether they think it is spam. If enough people regularly did this, we end up with a 100% review system. The threshold values for level 2 and 3 can be adjusted to partly mitigate this risk.
Thoughts and implications
There are many, but here are a few that came to mind while writing this:
- The ‘report spam’ button is only really usable by people who vote manually.
- Known neurons are a good source of checks in level 2, as they (their members) will have exposure to all proposals and are likely to be paying attention.
- The separation from the governance system is important, because:
- Prinicples guiding spam removal do not need to align with those for governance
- The system can be fine-tuned without needing to modify governance-related code
- This logic could form the basis for a prototype ‘inhibition neuron’ with broader utility.