From Information to Understanding: Moving Beyond Search In The Age Of Siri

Since the launch of Siri on the iPhone 4S last year, the media has been abuzz with the potential implications of what’s next – from Google’s Eric Schmidt commenting that Siri poses a great threat to Google, to countless articles by VCs and thought leaders.
Has artificial intelligence finally come of age? And is it ready for broader applications in industries ranging from travel to finance? Are we destined to grapple with fast-following Siri clone after Siri clone, or will the category evolve?
Siri excels at setting reminders (and a little less so at ordering Scottish lunches). But is she ultimately more than a better front-end for basic smartphone functions?
This post is about changing how we use computers to manage knowledge, and not just information.
Knowledge = Information + Meaning
You may “know” that it’s 100 degrees out there today, but unless you also know that 100 degrees equates to meaning that it’s hot, that piece of information is pretty useless.
To understand the concept of “100 degrees”, one has to know the meaning of 100 degrees and the concept of hot. That sophistication is called domain knowledge. Domain knowledge allows one to give meaning to information. As a result, the value one gets from knowledge helps make better decisions. The cashmere sweater stays home today.
With knowledge comes understanding, which helps users make better choices. Better choices mean fewer mistakes, and an increase in productivity.
Better Search Through Understanding
This focus on meaning is the foundation of semantics and semantic search (an oft-abused term), which ultimately means searching for concepts, not keywords.
Over the last 10+ years we’ve all been conditioned to expect search engines to basically match keywords to documents. We then receive a list of a gazillion links of pages that include some permutation of our keywords. It is then the user’s job to manually sift through all of these listings in the hope that one of them is a good match.
It goes without saying that this is a lot of work. A semantic search engine, on the other hand, would attempt to understand what we’re looking for, and then retrieve the best results, whether or not the specific words we used are mentioned or not. The real promise of this approach is that by understanding our intent, we will get more relevant and more accurate results.
Part 1 is to understand what the user is asking for, and part 2 is to understand what is discussed on a particular page. Siri has made strong headway into literally understanding you (voice to text) but more importantly about deriving meaning from what a user has just said.
The Holy Grail is to take this ability to understand what people asked for and to also understand what’s written across the billions of pages comprising the Internet.
Instead of “organizing the world’s information” you’d be organizing the world’s knowledge.
Understanding what people are asking or saying and converting it into usable meaning is a huge first step towards making heads or tails out of the billions of pieces of information scattered across the web.