Perhaps an alternative is to split into guilds - many of them - and pose an Epic Quest; game moves are contributions to a dialogue (conversation) map which, first, responds to the quest (a deep question) with position/answer statements to be followed by evidence fields the guilds collect to support their position. Other guilds can come in and gain game points by adding support to the game moves of others, or, for that matter, challenging them with evidence to the contrary. Game moves include Questions, as well as answers and pro and con arguments. Thus, this is not a simple Pro-Con ecosystem, but, instead, a conversational one. This, in theory, can be viewed through several lenses, two of which are "debate" and "learning conversation". To the extent that the epic quest is one which, effectively, crowd sources the world views expressed by guilds, and to the extent that rules of engagement mean that the pugnacious arguments remain inside the guilds and what comes out forms valuable contributions to the conversation which is the quest, then "all boats rise". John Seely Brown did a 6 minute Youtube with the opening sentence: "I would rather hire a high-level World of Warcraft player than an MBA from Harvard", and that point is evidence to support the model I'm suggesting here, something like "World of Warcraft meets Global Sensemaking". JSB's point is that guilds perform magic on humans; less tendency to argue, more tendency to find ways to remain on truth seeking missions rather than "selling" personal versions of truth.
There is an open source "concept map" platform known at Compendium available from the Open University's Knowledge Media Institute. It was invented precisely to help tame conversations in a conceptual space known as "issue-based information systems". Let me explain: Compendium is for "dialogue mapping", not "argument mapping". Dialogue mapping grew up in the fast-moving arenas of town hall planning meetings which frequently turn wicked ("over my dead body you'll put that freeway through this town"). There, the cognitive overhead of recording what is being uttered must be at an absolute minimum. Jeff Conklin invented the approach and described it in a paper about "gIBIS", and that approach eventually became the open source Java platform Compendium. As an alternative to explore this space, consider visiting http://debategraph.org/
I wrote and defended a thesis proposal on this topic in which the goal was to automate, to the greatest degree possible, merging nodes which mean the same thing. One example is "CO2 causes climate change" and "Climate change is caused by carbon dioxide", both saying the same thing, but neither of which would submit to a simple string comparison. As it turns out, there are Watson-like agents beginning to emerge in the open source arena, including OpenSherlock, my project, which is taking forever to complete owing to the enormous amount of experimental work that must be accomplished.
I,OTOH, which I had had my 23&me results years ago since what they tell me now might have prevented a costly experience back then. I totally get the "health privacy" issue, what with Google looming in the background along many dimensions, but for me, that was not a big issue. I also think that there is an aspect of 23&me that is being ignored in the NYTimes piece, the social network growing around real phenotypes in the context of genotypes.
Bacon was the dissertation project of Pat Langley under Herbert Simon. It was one of several dissertations exploring rational reconstruction of previous discoveries.
https://www.ijcai.org/Proceedings/81-1/Papers/025.pdf
[1] https://www.semanticscholar.org/paper/Pattern-recognition-an... [2] https://www.osti.gov/biblio/6742527 and http://soton.mpeforth.com/flag/jfar/vol5/no3/article7.pdf