1 HN user recommended this explainer1 month2013–2016score 1
Years with an HN recommendation, 2007–2026
Used as a quick, convincing demonstration of crowd estimation when discussing aggregated judgment.
Marcus du Sautoy of the BBC demonstrates the wisdom of the crowd, showing that averaging many guesses of jelly beans in a jar lands near the true count.
This is brilliant and immediately reminded me of "wisdom of the crowd" [this video] (start at 2:00 if TLDW). Basically average crowd > individuals. 160 people guess # of jelly beans in a jar. Few are close, but averaging all the guesses leads to 4 away from actual. Would be fascinating if applied to this as well...
Averaging 160 jelly bean guesses lands near actual count.
While I agree with your critique about headline but "pessimistic" is wrong word as well. Question about wind and solar energy indicates that they are optimistic. People are simply wrong quite often. Here is "related" video about wisdom of crowd: [this video] I wonder if we could apply idea of "wisdom of crowd" to those quiz questions.
There are plenty of services that offer interview prep advice and numerous independent consulting services in feedback. These don't scale and not what I want to do. I'm doing more research and think there is something to "collective intelligence" or wisdom of the crowd. I'm not going to argue if a crowd is wise or not, but data show that the crowd gets it right within a fraction of the right answer. What I'm proposing is a type of feedback, but one that can scale globally. The crowd should be able to predict closely what a person is like to work with, or so I think. This addresses the extreme cases we've discussed on the thread here. I'm still researching this - can crowds predict with the same accuracy as it is at arriving at an already known answer like how many jelly beans are in a jar etc. Here is some examples of what I'm talking about: [this video] [link] [link]
Example of crowd estimates landing near true answers.
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