That's a great point. I suspect though, the critique applies to decision making by consensus more broadly.
Decisions made by consensus are not necessarily the optimal strategy (as defined by efficacy to achieve targets). This method simply reflects that.
However, the benefit of this method is that all participants are forced to be more rigorous about why they hold certain beliefs, and then making an attempt to aggregate those preferences to drive an outcome.
I attended a talk about this recently, and I honestly think it's a revolutionary / game changing way to do contact tracing.
TLDR is to understand the spread of COVID-19 around you (through second-order network connections and beyond). This makes it much more similar to a weather forecast (e.g. the virus is approaching your vicinity through people in your network). This makes it a much more effective way to systematically identify, isolate, and contain further spread.
The idea is so simple and effective, I can't believe this isn't front and center over the news as a way to effectively contain the spread of COVID (beyond the existing measures of wearing masks, social distancing, etc).
This post was inspired by a question Richard Hamming asks in "You and your research" (paraphrasing): "What are the most important problems in your field?". When I thought hard about this question, I realized that I didn’t have a satisfying answer. This post is an ongoing attempt to remedy this.
Since solving these challenges is a collective pursuit, I’d appreciate suggestions on content to add, general feedback, and comments! :)
Decisions made by consensus are not necessarily the optimal strategy (as defined by efficacy to achieve targets). This method simply reflects that.
However, the benefit of this method is that all participants are forced to be more rigorous about why they hold certain beliefs, and then making an attempt to aggregate those preferences to drive an outcome.