Google uses the wisdom of everyone on the internet. They count links as votes. That is
an example and you are going through convoluted hoops to deny it.
Sure, some engineers write the code to extract the crowd wisdom, but they obviously don't provide the wisdom themselves. That comes from the crowd.
Now I think you are really just trying to bash the voting system here, and wouldn't cede any cases of crowdsourcing being legitimate (especially after having staked out the silly absolutism that there is no
wisdom in crowds) but in case you aren't and you really want examples:
recaptcha - This is a program to digitize books while users fill out a captcha form. They are presented with garbled words scanned from books and type them to help digitize old manuscripts.
ebay feedback - This is a reputation system that used collective feedback to help users choose between safe transactions and potentially risky ones. The idea is that users with great feedback ratings from a diverse selection of the crowd are less likely to defraud you than ones without.
Amazon mechanical turk - A platform to buy and sell "Human Intelligence Units". Can be used for crowdsourcing or not.
Google Image Tagging game - two people play a word game where they tag an image till they use the same tag. Then this data is used in aggregate to categorize images for image search.
Now you excluded collaborative filtering, which is pointless in your criticism because you are criticizing the attempt to use the wisdom of the crowd on able2know, and that's pretty much the only thing it's being used for. So what's the point? Are you looking for examples of systems that don't do what this system is trying to do as an example of how it won't? Collaborative filtering does a great job at content recommendation when done right and here are some examples:
Netflix Movie Recommendations - Based on your rating of movies, it tries to recommend additional movies. They even have a million dollar contest for better ways to harness this crowd data. http://www.netflixprize.com/
StumbleUpon - Site recommendations based on crowd ratings.
Digg - News articles and internet links based on user popularity.
Last.fm - the Audioscrobbler music recommendation engine