The Future of Search is Not Google Glass, But Natural Language Processing

The Future of Search is Not Google Glass, But Natural Language Processing

In April of 2012 Google announced  Google Glass, their augmented reality glasses that many believed would change how we search for and obtain information and even change internet marketing as we know it.

If the torrent of tech media coverage of Google’s new eyewear were to serve as any indicator of adoption, I’ll likely soon find myself on the subway in New York wondering why everyone was talking to themselves only to find they are all addressing their new eyewear. (I’m sure there’s a joke in there somewhere about NYC subway riders already talking to themselves before the arrival of Google Glass.)

Despite the media coverage, you can count me among those who are skeptical about how Google Glass will be adopted.

3 Reasons Why Google Glass Won’t Succeed

1. Form Factor:

Several years ago I paid several thousand dollars for Lasik surgery to never have to wear glasses again.  It’s going to be really tough to convince the mainstream consumers Google is hoping will adopt the technology to wear a pair of glasses all the time.

2. User Experience: 

Google Glass’s user experience sounds like something that was thrown out there in a design meeting but actually made it into a product release.  “Let’s make a pair of glasses that will pop up alerts in front of people’s eyes every few seconds!”

If the eyes really are the window to the soul, or at least to the mind, do we really want things constantly popping up in our peripheral vision?  Are we so sure we aren’t toying with our neurology?  Thanks, but no thanks.

3. Voice Control:

As many of the early challenges with Apple’s personal assistant Siri showed, getting a machine to understand a human in a noisy, poor cell reception area is hard.  Importantly, consumers tolerance for technology that doesn’t work is low—they will move on if the tech does not work as advertised.

Google Glass Fails the Adoption Test, but Signifies the Future of Search

I’ve done a bit of raining on Google’s parade when it comes to Glass, but I just don’t see it being adopted by mainstream consumers.  Still, I don’t want to throw out the baby with the bathwater, because there are important takeaways about the future of search that we can take from Google Glass, Apple’s  Siri and Google Now, Google’s information manager.

Siri and Google Glass

The early days of search required that users query a search engine in query -> database format.  That is, to extricate relevant results, the user must phrase the query in such a way that the machine can understand the request, query the database and return results.  Along the way there have been many who claimed to have solved this machine language problem, promising users can use ‘natural language processing’—the normal every-day language humans use as opposed to the ‘query a database’ language search has traditionally required. (Remember ‘Ask Jeeves?’)

Natural language processing has real benefits to the end user.  Being able to talk to a machine and get back highly relevant results has been on our minds since the days of Star Trek’s hologram.   But it’s only now, with Google Glass and Now, and Apple’s Siri, that the world’s biggest and most successful tech companies signal to the industry that we are closer than we have ever been to a world where that happens.

The image below is from Google’s Glass site and signifies how they see humans interacting with search in the future.

google glass ad

The last few (turbulent) days in the search space with the rollout of Google’s latest algorithm, Hummingbird, has seen us take additional steps toward this future.  Hummingbird essentially replaces the old algorithm engine that sought to map words in a query to content with the same terms, to a new engine that seeks to actually understand the meaning behind the query and (hopefully) return more relevant results.

As a user, it’s hard not to be excited about the prospect of simply asking a computer a question in conversational language and getting back a relevant answer, rather than struggling to formulate a query in a format a machine can use to query a database.

As data owners, we must be prepared by ensuring our data is organized in the most accessible ways possible, conforming to relevant data conventions and organized logically so the ever evolving spiders can access and make sense of it.

At the end of the day I don’t know if Glass will achieve widespread adoption or if Siri will ever evolve to be more useful than entertain my three year old with its “I don’t understand” responses when he asks it to fetch him a snack from the kitchen.  What I do know, is that they tell us the future of search is Natural Language Processing.

 

This article originally appeared in Search Engine WatchCover image via Auto Guide.

About Nathan Safran

Nathan is the Director of Research at Conductor and leads Conductor’s research and content team. Nathan is a monthly columnist at Search Engine Land and Search Engine Watch. Nathan’s research on digital marketing has been widely covered in both industry publications and mainstream media such as Techcrunch, Venture Beat and the Washington Post. Prior to joining Conductor, Nathan was an analyst at Forrester Research.

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  • Christopher Guayasamin-Brownle

    Really awesome read. Do you know where I can find some links on statistics for use of NLP?

    • Nathan Safran

      Thanks! Hmm, haven’t seen a collection of statistics that specifically addresses the prevalence of NLP, but I’ll keep my eyes open.