Meta-Memory (Fmrly Fed. Debate)

Break ideas/statements into digestible parts. Debate each sub-point, voting, logic analysis, idea linking, commenting, and meta-analysis.

Attorney 10 years, skilled in the art of persuasion and logical analysis.
Project manager, telecom, 5 years+
Rudimentary coding background

Proposal - Meta-Memory
Build a Meta-Memory into our discussions so that even brand new submittals/drafts would be enhanced by discussions and arguments hashed out years past.
The Meta-Memory is a browser extension/database that acts as a second layer to text that is inputted through the Catalyst Ideascale site. Meta-Memory will be blank to start, but fill up with data as Catalyst users tag and discuss proposals. Then, as ideas are submitted, proposals will be automatically processed, cross-referenced with any previously tagged discussions and then an overlay of the text may appear if any concepts appearing in the proposal/comment have been discussed before.
K(nowledge) Score
Underpinning each assertion, along with the ability for breakout discussions on each particular sub-aspect, there will be a K value, representing a combination of community proof and acceptance, which will be a product of 3 numbers between 0 and 1 representing:

• Justification for believing in the truth of the assertion (i.e. evidence or logic).
• Truthiness for the overall 1:1 vote from the entire community on whether the statement is true or false or somewhere in between.
• Belief for percentage of users who believe in this assertion is correct independent of both Justification and Truth.
  K = J*T*B. For instance, "1=1" should have a K approaching 1 as it is calculable, generally accepted and believed to be true (excepting that some may troll or misclick). A lizard person conspiracy might have a K approaching 0, low justification, low number of people who think that is correct, and low to moderate number of people who believe it.
  Compartmentalization
  Each word, statement, sentence, paragraph, or larger unit of text (a "Compartment") can be isolated and analyzed independent of the overall concept. This allows both for an in-depth analysis of every aspect of a Catalyst proposal and to catalogue good ideas and concepts buried in otherwise unusable proposals.
  Memory
  A text parser would be run against new proposals to see if the same concepts and phrases appear in the new proposal from the existing database, marking up the new proposal with notes from every previous discussion if relevant. For any phrase matches, the tags can be applied to the matching phrase and knowledge/discussion from the last time the idea was discussed can be automatically pulled into the new discussion.
  Breakout Debates
  Debates can be associated with a Compartment and a pro/con side will be created for users to present arguments and evidence for each position which is then voted upon by the community. Breakout debates would often be created under each leg of support for the main debate.
  Expert Analysis
  Along with a crowd driven analysis, a user may want to know what another user thinks about a proposal and either delegate their decision to the other user or at least see their opinion on the topic and perhaps all topics. By selecting which opinions you value more than others, you can automatically see what a person or organization feels about any particular. This might be especially useful in grading/assessing whether Justifications are legitimate.
  Meta-Analysis
  Beyond the argument level, data would be collected and could be explored on its own, seeing overall what statements people agree with and what evidence they find persuasive. Allows to identify consensus and issues of concern.
  How Meta-Memory Improves Crowd Decision-Making and Grows Ecosystem of Contributors
  There are 5 key areas in which the Meta-Memory continuously improves massive group decision-making and naturally grows an ecosystem of informed contributors:

1. Preventing dissemination of false or misleading information.
2. Accessing both primary sources and trusted expert opinion on any particular topic.
3. Knowing known unknowns and known knowns.
4. Having a means to settle/sharpen arguments for and against each topic presented.
5. Seamlessly integrating of the above into the Catalyst ecosystem
   Preventing Dissemination of False or Misleading Information
   By tracking statements at the assertion level, once an idea is shown to be false or otherwise dubious, either the text parser or a user can tag the reappearance of this idea in the new location so future users are made aware of issues (or positive information) surrounding an argument or assertion.
   Accessing both primary sources and trusted expert opinion on any particular topic.
   Users can select other users and organizations that they trust (and mistrust). When information is approved by, for example Charles Hoskinson, the user will see that the Hosk approves of the assertion and give it more consideration they otherwise may not have. Users will be able to determine for themselves which sources they deem influential and not.
   In order for an assertion to have high K value, it must be justified and thus primary source information (or logical analysis in the case of mathematics or something calculable) will be tagged as associated with the idea as well as the opinions from the other users whether the evidence is persuasive or not.
   Knowing known unknowns and known knowns.
   Ideas and supporting concepts that have been discussed previously (known knowns) are identified at the outset of a new proposal. On the other hand, new ideas and issues will be presented as a blank slate (known unknowns).
   Having a means to settle/sharpen arguments for and against each topic presented.
   Breakout debates for assertions will allow for sub-arguments on individual words, statements, sentences and ideas. Under each breakout, pros and cons will be presented and all each judged in the same manner as the original assertion, assigned a K value. The community will be able to specifically identify what aspects of problems are the heart of the issue in order to then identify solutions.
   Seamlessly integrating the above into the Catalyst ecosystem.
   Making this into a browser extension would allow for this to be built on top of Ideascale while also allowing an option for applications outside Ideascale. We could expand this to cover the Cardano forums as well and perhaps beyond.
   Mockup / Visualisation (attachment)
   See the attached diagram for a crude mockup of what the overlay might look like on a paragraph on a discussion page about gas fees..
   In the example the poster describes what they see as issues with bitcoin and etheruem. By default, each sentence and paragraph will be a distinct object that can be "debated" which includes: voted on, disputed, "expounded on" and each subsequent meta statement can also be debated on. Ideas can also be tagged so discussion from previous debates can be referred back to or imported.
   Highlighted in green in the example paragraph are ideas that the community strongly agrees on (high gas fees on etherueum) while others are color-coded which indicates the point is disputed and links to further discussion. One sentence has two points and has been broken into two different discussion points. In yellow, a reviewer disputes the claim about bitcoin while in brown a more interesting sub-discussion has broken on out how we should define what level of gas fees are acceptable in transactions. Below the three proposed definition of what "high" gas is, there are columns with arguments in favor and in opposition to each definition.
   Second Screenshot - Diigo
   Diigo is a browser extension similar in concept to what I am describing. It allows for groups to highlight and leave sticky notes on top of an existing website. This is a good jumping off point for how one might interact with the second layer of the site, but it does apparently lack some of the most exciting aspects of the Meta-Memory, the text parsing, voting, recursive commenting, and structured debate.
   Spending Breakdown:

• $5,000:
• Hosting fees for information storage
• Software development fees
• Front end - designing the user experience/integrating with browser plugin
• Back end - storing information, performing cross-referencing/text-parsing operation
• Graphic design fees
• Unanticipated fees
  Measuring Success:
• Has the software been built?
• Is it being used?
• Is it enhancing debate or clogging it?
• Are the collected metrics yielding new insights?
  Seeking:
• Developers to help implement.
  For the community: I'm open to suggestions on amount of capital that could be spent on this to bring a working prototype to a later funding round.

Note: lowered ADA requested based on conversation with developer friend on budgeting.