An update based on some more experience with pol.is:
I just tried out pol.is for a small FB group and discovered a few bugs and misfeatures. The devs were quite responsive, fixing a few on the fly and explaining what was going on. I think some UX tweaks are still needed to make it more intuitive for newbies and reduce friction.
In reading about how it’s been used in Taiwan, it seems that one use pattern is to encourage the various groups that emerge to develop statements that gain significant agreement across groups, and then use those “consensus” statements as the basis for f2f deliberation. So, as always, there’s important stuff that’s not captured by the software per se.
A key tenet of pol.is is that “responses don’t scale” in large conversations. Better that you either agree/disagree with my point or post your own. Of course, that’s amusing to write here, of all places, in a community that’s dedicated to scaling responses and is doing pretty well at it. It’d be interesting to find out if there’s a line of demarcation (i.e. if X>A and Y is true, go with a Discourse type process, if not, use pol.is. Shift between pol.is to and Discourse as X and Y change.)
My excitement about pol.is is in how it provides a kind of filter for large scale discussions. It seems to me very useful to be able to say that, in some large hubbub of discussion, there are roughly these two/three/five subgroups. This is a little more sophisticated than Reddit-style upvoting, in two ways. First, in distinguishing between a statement that got, say net 5 upvotes via 5 up minus 0 down and one that got 105 up vs 100 down and thus clearly represents a pretty large subgroup. Second, in the grouping.