Many computer science conferences have made a number of innovations such as a rebuttal phase, multi-tiered program committees, a hybrid journal/conference model with submission deadlines spread through the year. Not theoretical computer science which hasn't significantly changed their review process in the major conferences since allowing electronic submissions in the early 90's and an ever growing program committee now at 30 for FOCS.
Suresh Venkatasubramanian learned this lesson when he ran a double blind experiment for ALENEX (Algorithmic Engineering and Experiments) and laid out an argument for double blind at broader theory conferences to limit the biases that go along with knowing the authors of a paper. The theory blogosphere responded with posts by Michael Mitzenmacher, Boaz Barak and Omer Reingold and a response by Suresh. I can't stay out of a good conference discussion so here goes.
Today major orchestra auditions happen behind a screen with artists even told to remove footwear so sounds won't give away the gender of the musician. On the other extreme, the value of a piece of art can increase dramatically in price if it is discovered to be the work of a famous artist, even though it is the same piece of art. Where do research papers lie? It's more a work of art than a violinist in a symphony.
Knowing the authors gives useful information, even beyond trusting them to have properly checked their proofs. Academics establish themselves as a brand in their research and you learn to trust that when certain people submit to a conference you know what you get, much the way you would more likely buy a new book from an author you love.
Suresh rightly points out that having authors names can and do produce biases, often against women and researchers at lesser known universities. But we should educate the program committee members and trust that they can mitigate their biases. We can completely eliminate biases by choosing papers at random but nobody would expect that to produce a good program.
Having said all that, we should experiment with double blind submissions. Because everything I said above could be wrong and we won't know unless we try.