ASPEN, Colo.—David Weinberger, a senior researcher at the Berkman Center for Internet and Society, mused briefly Saturday on the difference between getting a recommendation on the next book to read from Amazon.com... or a skilled librarian.
The Amazon.com algorithm is very good at using what you've just bought to recommend things that you'll want to buy, he observed, but it can be hard to tell why. Perhaps you'll be attracted to the content of the recommendation–or perhaps it's the fact that the cover is also green, or that the print is in Helvetica font.
In contrast, a skilled librarian is usually going to recommend a book solely because of its intellectual value, without any lurking, contentless variables. The librarian is therefore likelier to send a person in a direction they wouldn't otherwise have gone in a way that will advance their thinking, education, or aesthetic taste, because they're not just meeting needs that have already been expressed.
As someone who is paid to recommend nonfiction reading, I can certainly appreciate the value that humans add in this realm. I have, at the same time, discovered a lot of wonderful books, movies, and songs through the respective algorithms of Amazon, Netflix, and iTunes. It's hardly a surprising insight to suggest that human and algorithmic recommenders both have their respective roles to play. But I wonder if we couldn't tease out the strengths and weaknesses of both approaches by sharing some stories. Consider this a solicitation of your experiences. What are the best or worst recommendations you've gotten from humans or algorithms? Did those experiences teach you anything? How do you decide which type of recommendations to seek out in a given instance? I look forward to your emails. My contact information is listed in the bio box below this article.
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