Thanks to the BingTweets program, I’ve been asked to opine on search and decision engines. I’m kind of proud of my third and final post, which riffs on the first two and goes a bit, well, meta. I’d love to know what you guys think of it. I’ll repost the first half here, and link back to the whole post on the original site that commissioned the work.
Over the past two posts I’ve outlined my hopes and frustrations around search and decision making, using my desire to acquire a classic car as an example of both the opportunity and the limitations of web search as it stands today. As an astute commentator noted on my last post – “normally a 30 minute conversation is a whole lot better for any kind of complex question.”
Which leads me to my last post in this series. What is it about a conversation? Why can we, in 30 minutes or less, boil down what otherwise might be a multi-day quest into an answer that addresses nearly all our concerns? And what might that process teach us about what the Web lacks today and might bring us tomorrow?
Well the answer is at once simple and maddenly complex. Our ability to communicate using language is the result of millions of years of physical and cultural evolution, capped off by 15-25 years of personal childhood and early adult experience. But it comes so naturally, we forget how extraordinary this simple act really is.
I once asked Larry Page, co-founder of Google, what his dream search engine looked like. His answer: The computer from Star Trek – a omnipresent, all knowing machine with which you could converse. We’re a long way from that – and when we do get there, we’re bound to arrive a with a fair amount of trepidation – after all, every major summer blockbuster seems to burst with the narrative of machines that out think humans (Matrix, Terminator, Battlestar Galactica, 2001, I Robot…you get the picture).
But I have hope. Given this is my last post in the series, allow me to wax a bit philosophical. While we in the search and Internet industry focus almost exclusively on leveraging technology to get to better answers, perhaps we might take another approach. Perhaps instead of scaling machines to the point of where they can have a “human” conversation with us (a la Turing), perhaps instead (or, as well), we might leverage machines to help connect us to just the right human with whom we might have that conversation?