Tset Gnirut: The Reverse Turing Test


SPTM.jpgThe Turing Test is a well known question considered by computer scientists, especially those studying artificial intelligence.  It's a basic question that helps us understand whether or not machines can think.  Essentially, the Turing Test asks,"Can you tell if you are conversing with a person or a computer?"  We've philosophized about this problem for 60 years.  I think it's becoming increasingly difficult to tell.  Consider Siri on the iPhone.  Is there someone behind the query that is manually figuring out the answers to your questions?

While at Pubcon this past week, I've realized that there is a reverse problem that many are trying to solve.  A problem that is equally interesting and perhaps becoming more difficult as well -- the Reverse Turing Test (which I call "Tset Gnirut").  Tset Gnirut is also a question:  Can a machine figure out if you are a human or a machine?  There is an on going effort to solve this problem, mostly around spam.

CAPTCHA popped onto the scene a few years ago.  Certainly, this was one form of the Reverse Turing Test.

However, after listening to Matt Cutts,  I realized Google's search quality group (well, at least those fighting index spam and defining search relevance) is all about answering Tset Gnirut. Detecting link spam is all about solving this problem.  Figuring out if link strategies are created by machines, deciding whether or not text has been created by humans or not,  understanding if a bot is clicking on links, or understanding if a tweet or facebook post is automatically generated are all problems of Tset Gnirut.

Machines are getting smarter and we are off-loading more and more of our consciousness to machines.  Machines are making more decisions for us.  Soon, the machines will figure out decide if you are a machine or not.  When that happens, it will be an interesting world when the machines decide they would rather talk to each other than talk to us.

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This page contains a single entry by published on November 16, 2011 2:29 PM.

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