Powerset crosses the Uncanny Valley

In case you haven't heard the news, Powerset launched today.  Since I can't sleep due to launch adrenaline, I suppose it's time to weigh in on Powerset unofficially.  It's fun to write a press release, but it's more fun to philosophize on my own time!

Last year, I came across the concept of the Uncanny Valley though an employee of PARC.  The basic concept runs something like this: as you make a robot more like a human being, people tend to respond with more empathy.  However, there's a dip in the empathy curve when the robot looks enough like a human, but has behavior incongruent with what we'd expect from a real human being.  We tend to forgive weird mannerisms (jerkiness, oddities in speech, etc.) when a robot looks like a robot.  When a robot looks like a human, we expect it to act like a human.

As an example, cartoon characters are usually more believable than computer generated characters, unless the CG is so perfect as to be indistinguishable from reality.

Keyword search engines sit somewhere on the left of the curve.  We're willing to accept the choppy "keywordese" language of a search engine because we appreciate the results that come back and we can make excuses when it goes awry: "It's just a computer.  It doesn't really understand me."  As with most technology products, the utility curve and the expectation curve are aligned exactly because we treat keyword search engines as an unfeeling technology.

Oddly enough, when a system is endowed with an understanding of meaning (call it "semantics"), we suddenly demand that the system act, think, infer, and comprehend just like another human.  Instead of just being a cold of technology, we begin to treat the system with agency and want it to act like other agents (i.e., humans). 

The question shouldn't (and can't) be about releasing a system that has a perfect understanding of language, because that perfect understanding is many years down the road.  How is it that companies like Radar, TrueKnowledge, and Powerset believe that we can create products based on imperfect technology?

There are two ways to stay out of the Uncanny Valley.  First, create unique features that are so compelling that users are willing to deal with imperfection.  Keyword search hasn't survived because we always get the right answer - plenty of searches yield nothing.  But, though we may get wrong answers, we often enough get answers that would never have been possible before keyword search.  Second, access to semantic features shouldn't require a significant change in user behavior.  No matter how good (or "natural") a feature is, if a user has trouble finding it, it won't get used.

People often think that NL search is doomed to failure both because computers don't understand enough and, even if they did, users won't start entering natural language queries.

I think Powerset has scored on both counts.  As an example, for topical queries like moses or machiavelli, Powerset assembles a summary of Factz based on our deep linguistic analysis of each sentence.  This kind of automatic aggregation of content just wasn't possible before Powerset.  But, users don't have to do anything special.  They just get Factz "for free" by using their keyword usage paradigm.

I'm really proud of Powerset's first product.  The debate on whether or not we've crossed the valley will continue, but one thing is certain: a better, more natural way of interacting with technology is coming. (Of course, whether we sit to the left or the right of the Uncanny Valley is the subject for another post.)

Bed time, finally!