However, after Jennings selected the Daily Double and wagered his entire score, he took the lead.

Watson was noticeably less confident in his answers during tonight’s game. On multiple occasions, the answers Watson generated did not meet the confidence threshold that would have caused him to buzz in, and both Jennings and Rutter tried mightily to exploit these rare opportunities to answer clues. For passing moments, Watson looked, well, human.

Still, Jennings was only able to hold onto his lead until about halfway through the Double Jeopardy round. After that, Watson took the lead and never relinquished it.

Given Watson’s commanding performance yesterday, it was very unlikely that Jennings or Rutter would catch Watson in Final Jeopardy, and indeed they did not, although all three contestants managed to answer the final clue correctly.

Those are the facts of the game, but what of the broader implications of tonight’s Jeopardy! match? Below are some points to ponder, but they are not to be taken, at least not necessarily, as the views or beliefs of The Internet Patrol.

Even if Jennings or Rutter managed to beat Watson, there wouldn’t be much to celebrate. To be altogether excited about a victory like this is rather like rejoicing in winning a war without lamenting the causalities suffered.

There has always been confidence in the economy’s ability to reinvent itself. When the Industrial Revolution was first gaining steam (haha), people worried about this transformation’s effect on agriculture. America was a nation of farmers, so what do we do when technology wipes out the need for millions of small farms?

As it turns out, farmers were able to find work elsewhere. The man who once planted and raised crops on his few acres of land could now build Model T’s in a Ford factory. Crisis averted. (That is, an unemployment crisis was averted – the fact that displaced farmers had to swarm to factories isn’t a good thing, at least not by the lights of many farmers.)

But why assume that the economy will always be able to invent new jobs? It only took a few self-checkout machines to displace ten grocery-store cashiers. True, the creation of self-checkout machines gives rise to the need for someone who can fix them, but even the most optimistic math cannot suggest that the number of jobs created offsets the number of jobs lost.

Even worse: when we invented computers people were employed to fix them – e.g., the checkout-machine fixer – but what happens when computers can start to fix themselves?

We’re not so naive as to think our crisis is necessarily worse than any other employment upheaval in history – who could claim such a thing? – but our present predicament cannot be dismissed preemptively by a simple appeal to historical cycles.

For the concern is not merely the rapidity with which technology is evolving – although this is an issue too – it is also the way it’s evolving. Technology isn’t progressing for the sake of progression; it’s progressing to help businesses run more efficiently, for hospitals to operate more effectively, and so on. In other words, we are endowing technology with the skills that we once tried to imbue into the workforce.

Again, this isn’t necessarily new, but with machines like Watson, it is becoming uncomfortably clear that we are on the verge of a brave new world. It doesn’t seem at all unlikely that machines like Watson, when designed for specific positions, could easily do the work that millions of humans presently do. We pay an enormous amount of people to analyze information – difficult information that computers are historically not good with, like natural language – and offer insights on the basis of their analysis. Sounds a bit like Watson answering questions on Jeopardy!.

Needless to say, technological innovation – even technological innovation that displaces human workers – is not without its benefits. As IBM engineers explained on Tuesday’s Jeopardy!, we are currently living in an age that is frighteningly saturated with information. Watson and similar machines could go a long way towards extracting useful information from mountains of data, distilling it for humans, and relegating the rest to the digital dust heap.

The benefits of this are obvious. Take the case of a difficult medical diagnosis, an example invoked by IBM on Tuesday’s show. A doctor is faced with an enormous amount of information – a large percentage of which is contained in natural-language documents – to synthesize. There is the newest research to be considered, often in the form of technical peer-reviewed journal articles, as well as traditional reference sources, like medical encyclopedias. A patient’s current symptoms and medical history add more information to the mix. Doctors are routinely placed in these trying situations, and it’s not hard to see how Watson – a machine that is designed precisely to make sense of huge amounts of information conveyed in natural language – could be of considerable assistance.

And yet we’re still worried.

For centuries machines have helped humans with physical labor, and we seem to have withstood this development, but now computers are moving into the arena of mental work – indeed, explicitly human mental work – and that should give us pause.

Will computers overthrow people?

Probably not, but remember: Watson was competing against humans, and it did a hell of job.

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