Consensus out of Controversy Use Case

Traditional surveys measure lack of consensus. The purpose of Canonizer is to build consensus out of controversy. While traditional surveys or petitions require everything to be thoroughly vetted before the survey starts. Canonizer’s use model is more like Wikipedia, where the crowd does the vetting. Wikipedia works great if everyone agrees, but if someone disagrees, currently, you end up with polarizing edit wars. Canonizer can solve this problem. When disagreement shows up in Wikipedia, instead of an edit war, you just say: OK, we’ve discovered disagreement, so let’s move the disagreeable part over to canonizer – where both competing camps can be represented in multiple camps, concisely and quantitatively – everyone getting what they want in a win win way. The ultimate goal being to build consensus out of controversy.

Canonizer.com works well in theoretical fields where there is not yet a scientific census. Consciousness is a good example field. Currently, in this field, everyone writes a book or article. First, they classify the field into the way they perceive the various competing camps, then they point out the flaws they think they see in these camps. However, they often get this wrong, their ideological religions polarize everyone. Criticisms are usually just talking past each other.

They present their own theory, in their own language (different than everyone else’s language) and from their own unique religious (including atheism) point of view. Since every expert has their own book, in their own language, from their own point of view – it gives the perception that nobody agrees on anything. Because everyone is using different ambiguous language, it is near impossible to communicate. Nobody talks about what people agree on. And everyone ends up focusing on minor disagreements – completely missing any consensus that may exist.

With canonizer, the first person starts the consensus building by creating their own camp on a topic. You never fork into competing camps unless absolutely necessary. When a disagreement is discovered, you build as much consensus as possible (canonizing the best terminology and so on through continued negotiation) and build a super camp on what people can agree on (usually the most important doctrines where most people do agree, like “approachable via science”). The still disagreeable issues can be pushed out of the way of consensus, down to supporting sub camps. Everyone is highly motivated to find some terminology to agree on, because forking the camp reduces the consensus and influence of your camp. More and more competing camps can show up, pointing out different yet to be falsified theories. With theoretical work, the more diversity the better, as you want to capture and test for all theoretical possibilities.

The focus is always on falsifiability. Everyone is encouraged to come up with and describe experiments that could falsify their camp. We ask everyone: “What would falsify your theory, and force you into a competing theory? With this theoretical information, the experimentalists can then perform the experiments being described that people agree would falsify their camp.

Good arguments also work. You can measure the quality of new arguments and evidence, by how many people it converts - these can rise to the top and be focused on. Ultimately, the experiments are done till there is only one remaining camp that can’t be falsified. We’ve already seen multiple camps being falsified for some, including one being falsified by data coming from the large hadron collider. Being able to track things like this makes it better than a very dramatic sporting competition, with definite leaders and losers in the competition as more camps are falsified for more people.

Once you get everyone into the same single camp, by experimentally falsifying all the others, you know, rigorously and definitively, you have finally achieved a “scientific consensus” from controversy. Then, you can throw it back to Wikipedia, where the additional complexity of Canonizer.com is no longer required.