Elementary, my dear Watson!

It isn’t a spoiler any more to reveal that Watson walloped Ken Jennings and Brad Rutter at Jeopardy; its final take, after two full games, was greater than the two other totals put together. Charmingly, Ken Jennings referenced a Kent Brockman quote from The Simpsons in his final Final Jeopardy answer slide. Below “Who is Bram Stoker?” Jennings scribbled in parentheses: “I, for one, welcome our new computer overlords.” Brockman, in the 1994 episode Deep Space Homer, announces on air when he learns of an an invasion of Earth:

One thing is for certain: there is no stopping them; the ants will soon be here. And I for one welcome our new insect overlords. I’d like to remind them that as a trusted TV personality, I can be helpful in rounding up others to toil in their underground sugar caves

I’ve been waiting for this ever since I read this about Watson, the computer that IBM was building to beat human beans at Jeopardy. And it wasn’t going to be easy — because Jeopardy relies as much on wordplay as on data, in its questions, to give its participants clues. A machine can crunch pure data easily to come up with the answer to a question; figuring out puns means figuring out how we think through language, which is far harder, almost Turing Test-ian in its implications.

Watson’s wang-bang days are now in the past, to the point that the machine now competes with the best human players in the history of the game. IBM is rolling out the red carpet for its new star-child with a big publicity campaign, but for all the hype, it insists Jeopardy! is just a convenient exhibition. They have a much more important goal: teaching a machine to understand language written for humans, not computers. This is one of the holy grails of artificial-intelligence research, and a technology that would revolutionize any industry plagued by the fact that computers are still miserable at understanding what’s known as “natural language.”

Let’s assume that it’s only a matter of time before IBM irons out the few imperfections remaining in Watson, and they pass the Turing Test with flying colours. So I start to wonder: What next? It strikes me that human intelligence still operates on a different plane. We don’t always get asked questions as directly as computers do. In our lives and our work, there is no entity querying us, to whom we can provide a satisfactory answer and thus justify our existence. Most frequently, we look at a mess of data that is life and the world, and we figure out for ourselves what queries this mess generates, what can answer these queries, how satisfactory these answers are, and even how to measure the satisfactoriness of these answers. Maybe that’s the next frontier. Human intelligence doesn’t always lie in coming up with the right answers; often, it lies in coming up with the right questions.

Atlantic offers a very interesting read on the Turing Test and Man Vs Machines through time.


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