Customized Search and Information Delivery=Censorship

I recently came across an interesting TED Talk about “filter bubbles” while doing research on critical literacy in a digital age.

In it, Eli Pariser reveals the extent to which the combined use of algorithms and consumer/user-mined demographic information is leading (perhaps inadvertently) to significant degrees of censorship by omission, as individuals receive search results reflective not of information most relevant to what they are looking for, but filtered by companies like Google according to information as seemingly irrelevant to a topical search–say, about coverage of the uprisings in Egypt for example–as the kind of purchases a person makes, the make and model of the computer they use, their geographic location, etc.

Essentially, Pariser’s research suggests that the quest to deliver customized, highly targeted information to individuals is currently resulting in unanticipated dangers with regard to the Internet’s claim to provide equal access to information for all. What Pariser advocates is that users be informed, and put back in control, of the kinds of filters search engines like Google are using such that individuals—not algorithms and databases—determine what details are deemed relevant and made available.

This subject is particularly important if/when we consider the fact that Google search has become a first line go-to source for information and everyday research.