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Because the concept seems too simple, most of the websites implementing the idea can't avoid the common pitfall: [[informational cascade]] in soliciting human preference. For example, [[digg]]-style implementations, pervasive on the web, heavily bias subsequent human evaluations by prior ones by showing how many votes the items already have. This makes the aggregated evaluation depend on a very small initial sample of rarely independent evaluations. This encourages many people to game the system that might add to digg's popularity but retract from the quality of the featured results. It is too easy to submit evaluation in digg-style system based only on the content title, without reading the actual content supposed to be evaluated.
A better example of a human-based selection system is [[Stumbleupon]]. In Stumbleupon, users first experience the content (stumble on it), then can submit their preference by pressing a thumb-up or thumb-down button. Because user doesn't see the number of votes given to the site by the previous users, Stumbleupon can collect relatively unbiased set of user preferences, and evaluate content much more precisely.
===Human-based evolution strategy===
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