Researchers have found that good information doesn’t always drown out bad in recommender systems. In fact, the research done by the creators of movielens shows if you give (for example) a movie a higher rating than it “deserves” other people will also be inclined to give it a high rating. So “innocent” people will unconsciously “play along” with people trying to influence the system and reinforce their dirty work. Unfortunately for the creators of recommender systems, users will notice when overall a recommender system’s results are poor. The writers of the academic paper (available in full here) suggest one way to avoid this problem would be to hide the rating of a film from users who want to rate it themselves so they aren’t influenced by others’ ratings.
I didn’t find collaborative filtering useful when I did use it, but that was nearly ten years ago when the MIT Media Lab was playing about with what became Firefly. Perhaps if my DVD Recorder was smarter and networked with other such recorders to compare my TV/film preferences with others’ without my needing to enter the details by hand it would have enough data to be able to adequately predict my viewing tastes. Personally I suspect mine are atypical enough that it would be difficult to predict what I would like mathematically. Then again, most people probably think they are unique in this respect!