Artificial intelligence has just got smarter

The American TV quiz show  Jeopardy! has been running for over 25 years. Contestants are given clues in categories ranging from serious subjects such as World War II, to more frivolous topics like rock musicians. They then have to come up with a question in the format: “Who is…”, or “what is…” based on the clues.

The clues are not straightforward and factual — a computer with a large database can crack such statements quickly — but oblique.

They are full of puns, obscure relationships, jokes, allusions and so on that only a human being steeped in that culture will recognise. In that sense, the clues are not ‘context-free’ as computer languages are (or for that matter, classical Paninian Sanskrit): you must know quite a bit of cultural context to decode them.

This is infernally hard for computers, and a challenge that artificial intelligence (AI) researchers have been struggling with for decades — the holy grail of ‘natural language processing’. There have been several false starts in AI, and enthusiasm has waxed and waned, but the iconic promise of computers that can converse (such as the talking computer HAL in 2001: A Space Odyssey) has remained elusive.

This is why it is exciting news that a new IBM program (dubbed ‘Watson’ after the founder of the company), built specifically to play Jeopardy, defeated two of the world’s best human players in a special edition of the show on February 16th. There was some quiet satisfaction among the techie crowd that the day may yet arrive when intelligent robots can respond to conversational queries.

Watson runs on a cluster of ninety Linux-based IBM servers, and has the horsepower to process 500 gigabytes of data (the equivalent of a million books) per second — which is necessary to arrive at an answer in no more than 3 seconds; that is the time human champions need to press the buzzer that would give them the right to answer the question. Ray Kurzweil, an AI pioneer and futurist, suggests this level of computing power will be available in a desktop PC in about a decade.

Watson’s accomplishments are qualitatively different from those of its predecessor, Deep Blue, which defeated world chess champion Garry Kasparov in 1977. In many ways, chess, with its precise rules, is much easier for computers than the loose and unstructured Jeopardy! game. Thus, Watson is much more complex than Deep Blue, which stored the standard chess openings, and did a brute-force analysis of every possible outcome a few moves into the future.

The interesting question though, is, what does all this mean for humans? The nightmare possibility is that we have reached that tipping point where humans will become redundant. That of course was the precise problem that 2001: A Space Odyssey’s HAL had - it felt the humans on board its spaceship were likely to cause the mission to fail; therefore it methodically set about eliminating them. Much the same dystopic vision haunts us in other science-fiction films: for instance the omniscient Skynet in The Terminator series or the maya-sustaining machines in The Matrix.

Berkeley philosopher John Searle, writing in the Wall Street Journal, gives us some comfort. According to him, Watson is merely a symbol-manipulating engine, and it does not have superior intelligence; nor is it ‘thinking’. It merely crunches symbols, i.e. syntax, with no concept of meaning, i.e. semantics. “Symbols are not meanings,” he concludes, “Watson did not understand the questions, or its answers… nor that it won — because it doesn’t understand anything.”

Even without becoming our overlords, Watson and its descendents may cause displacement. They will cause a number of jobs to disappear, just as voice recognition is affecting the transcription industry. Former head-fund manager Andy Kessler suggests in the WSJ that there are several types of workers, but basically ‘creators’ and ‘servers’; only the former are safe.

Technology such as Watson will, he says, not only disrupt retail workers (eg. travel agents), bureaucrats, stockbrokers and customer support staff, but also legal and medical professionals.

The latter may find applications like a doctor’s or lawyer’s assistant increasingly cutting into their job content.

Thus the arrival of Watson-like artificial intelligences may cause serious disruption in the workforce, although it is not likely that they will be ordering us around any day soon. At least not yet. Humanity may be more resilient than we thought.