These complaints notwithstanding, my bet is that recommendation algorithms and interfaces will rapidly branch out. In the future, perhaps Google’s Gmail will tell you whom you should forward that urgent e-mail to, or remind you to keep in touch with a friend you’ve inadvertently ignored. Marrying Gmail’s context-sensitive advertising to a decent recommendation engine would boost the value of both. What’s more, it’s easy to imagine Facebook suggesting what information should be shared with whom–or who should be sharing more with you.
The rise of the social graph (an abstract representation of the social connections between users of digital networks; see “Between Friends,” March/April 2008) should enable different companies’ recommendation engines to work together, offering financial advice, travel options, and more. Wouldn’t it be intriguing to see what stocks and funds people like you bought? Perhaps these technologies will ultimately go meta, with some startup offering recommendation engines that let you pick the best recommendation engines for you. Advice about advice might be a great business.
For all my excitement about the future of recommendation services, I can’t help feeling the way I felt about search in 2001. Existing recommendation engines have a lot of value, but they’re still primitive. Distinctions between browsing and comparison (that is, between looking at products and choosing between them) are poorly understood. We’ve yet to see how user-generated tags make product and service descriptions more precise and useful. The more specific, explicit, and time-sensitive the tag, the better the potential recommendations will be.
Smart people all over the world are working on these problems. Billions of dollars are at stake. Netflix is offering a million dollars to anyone who can improve the efficacy of its (exceptionally successful) recommendation engine. That’s a small price to pay for a company whose future depends on its ability to compete with Blockbuster and the digital video delivery companies of the future. It is an interesting and important problem, because it’s not only individuals who watch the movies, but couples, families, and friends. Perhaps the winning algorithm will be optimized for the preferences of groups.
When I get good recommendations, I spend my time and money differently. Even better recommendations will dramatically increase the value of that time and money. That’s a digital future I crave and expect. I hope Internet innovators take my recommendations as seriously as I take theirs.
Michael Schrage is a consultant on innovation, a researcher at MIT’s Sloan School, and the author of Serious Play: How the World’s Best Companies Simulate to Innovate.