On Saturday, I realized that my old wireless router had died of old age. Not knowing what model to buy next (I had bought the first one because it was the only one compatible with my old iPAQ Music Center), I turned to my social graph for an answer. I used Twitter to ask my 375 “followers”: “just realized my wireless router at home died. Any advice as to purchase of a new one?”
In a matter of a few hours, I quickly received many valid answers both from Twitter and from Facebook where my “tweets” are broadcasted to my 612 “friends”:
- A Montreal web entrepreneur told me to buy the Linksys WRT160N with a link to the product page
- The partner at the VC firm who funded Praized Media said I should buy an Airport Extreme if I’m using a Mac
- A former Ubisoft colleague told me to make sure I update the firmware before declaring my router dead
- Another former Ubisoft colleague suggested a SonicWall router along with a link
- A high school friend told me to buy Linksys and said I shouldn’t pay more than $80.00
Now, I could have easily queried Google for such a search. I could have looked for “how to buy a wireless router“, found relevant web sites like About.com or eHow, and identify important product criteria that way (and associated brand/models). But you know what? Research takes time. Pinging my social graph took me 1 minute and I got five valid answers in a very short time.
It got me thinking about how the social graph is structured, in terms of ease of access. It’s very easy to access friends & family. You usually have their e-mail address and phone numbers handy. It’s a bit harder to reach the people that have a shared interest with you (community members, neighbors, former colleagues, etc.) and it’s usually very difficult to directly ask experts for their opinion (have you tried pinging a movie critic lately?). What if you could easily reach all these people to ask them anything? And what if everyone had tools to make it easy to answer?
It also got me thinking about the whole Man vs. Machine debate. Who do you trust most for information/recommendations? Man (a real human being answering your query) or Machine (an algorithm that’s surfacing relevant information)? It’s Facebook/Twitter/Friendfeed/Mahalo vs. Google/Yahoo/MSN. Coming from the business directory industry where word-of-mouth is often considered the biggest “competitor” (with social media, it’s becoming the biggest opportunity!), I tend to find human recommendations more relevant and more interesting.
In an article about social media monetization yesterday, eMarketer says that word-of-mouth might be a key way to monetize social media as “62% of marketing professionals told TNS Media Intelligence and Cymfony that creating word-of-mouth or viral campaigns has great potential to impact their business.”
That Man/Machine debate is age-old as you can see from this quote from a 1968 Time magazine article: “With the Depression, the machines that had once seemed so heroic to the prosperous ’20s were suddenly transformed into villains. As production lines slowed to a crawl and millions were thrown out of work, surrealists depicted nightmarish phantom treadmills and airplanes that were trapped like dragonflies.”
As we get closer to the singularity (defined as “a hypothesised point in the future variously characterized by the technological creation of self-improving intelligence, unprecedentedly rapid technological progress, or some combination of the two.”), I think we’ll get into more debates around the value of Man versus Machine (or maybe I’ve been watching too much Battlestar Galactica).
Update: Danny Sullivan talks about “Search 4.0: putting humans back in search“.