[JimmyBuckets]

Related: https://pol.is/home

Pol.is is a tool that uses ML to synthesize these shared views and provide inisght into both areas of consensus and discordance.

I am not sure of the specific relationships but it has been championed by Audrey Tang (Taiwan's minster of digital affairs) and other Pluralist people.

I think this is a worthy tool but slightly narrower than pol.is because it's just as important to understand where there is disagreement.

[simurgh_beau]

Apologies for the very slow reply; I had mistakenly assumed this thread was inactive.

Thank you for sharing this; it's a fantastic reminder. I was actually introduced to the concept behind Pol.is a few years ago on a BBC Click Persian segment, and your comment prompted me to take a much deeper look into their work. The connection to Audrey Tang and Taiwan's digital democracy work is particularly inspiring.

You make a very sharp point about the importance of understanding disagreement. In my proposal, the primary mechanism for this is the public vote count. While it doesn't have the sophisticated ML clustering of Pol.is, the goal is to make the final vote tally on all candidate messages transparent. This way, you see not only the ideas that reached consensus but also the exact level of support for minority or dissenting opinions, creating a clear map of both agreement and discord.

Thanks again for the excellent and very helpful comment.