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IBM's Jeopardy! master robot Watson may not be a judge anytime soon, but he has gotten his first job: as a diagnostic whiz, like we expected. (Note: We will refer to Watson as a "he" and not an "it" until he stops being more charismatic than most humans we know.) According to the Wall Street Journal, IBM and health insurer WellPoint have agreed to use Watson to "help suggest treatment options and diagnoses to doctors." Congratulations, Watson! Don't blow your first paycheck on anything frivolous! [WSJ]

The Honorable Justice Watson?

The Yale Law Journal's Betsy Cooper wrote an essay examining our favorite Jeopardy! champion (and new medical diagnoser) robot Watson, but from a new angle: Could Watson help judges make legal decisions?

The essay notes that Watson could be of particular use to a certain type of judge or legal scholar: the new textualists. She writes: "New textualists believe in reducing the discretion of judges in analyzing statutes. Thus, they advocate for relatively formulaic and systematic interpretative rules. How better to limit the risk of normative judgments creeping into statutory interpretation than by allowing a computer to do the work?"

Says Cooper, "there are three important elements of new textualism: its reliance on ordinary meaning (the premise), its emphasis on context (the process), and its rejection of normative biases (the reasoning)." From that vantage point, Watson wouldn't be so much a judge (much as we'd love to see a massive black judge's robe draped over Watson's storage array) as an assistant or clerk, using its power to decide, for example, what the most "ordinary" use of a word is. Humans have to rely on instinct and experience, but Watson can systematically measure that sort of thing, narrowing down the possible meanings of words to eliminate uncertainty.

Watson also has the advantage of not being able to insert his own emotions or opinions into his decisions, by virtue of the fact that, well, he doesn't have any. Cooper does conclude that, due to his occasional errors (we'd hate to sentence criminals to serve time in Toronto) and the more basic fact that perhaps there should be a human element to judging, Watson is not an ideal candidate to actually make the bench. But that doesn't mean he couldn't be tremendously useful in legal decisions.

[Yale Law Journal]

What is...Toronto (General Hospital)?

When Watson was competing on Jeopardy!, its massive databanks were filled with encyclopedias, novels, film scripts, and history books. These days, Watson is more into medical journals and misspelled Yahoo Answers blog posts about weird rashes and vague abdominal pains. Watson is maturing, and prepping for his first non-trivia, real-world application: medical diagnoses. He's all *sniff* grown up!

We've known medicine was to be the next step for Watson for some time, but just recently, IBM gave a short demonstration of Watson's progress. Watson isn't the first attempt at an automated diagnosis program--we documented Artemis, and Isabel has been around for a few years--but Watson's incredible power, depth of knowledge, and ability to understand natural human language puts it in a totally different league. Diagnosing an ailment isn't really that much different from answering a trivia question; Watson takes in as much information as possible from the question, eliminating the potential answers as new information renders them impossible, and comes up with a list of likely answers. An example from the AP: "As more clues were unveiled - blurred vision, family history of arthritis, Connecticut residence - Watson's suggested diagnoses evolved from uveitis to Behcet's disease to Lyme disease. It gave the final diagnosis a 73 percent confidence rating."

While on Jeopardy!, Watson could only give one answer, but in medicine, it lists all possible answers, along with the percent likeliness. An 80% possibility of accuracy is enough for Watson to risk money on Jeopardy, but when working with possible diagnoses, that still leaves a one in five chance that the patient is afflicted with something else, so Watson is designed to divulge even the less likely answers.

Watson's human language recognition skills also allows it to input an entirely new sector of information: anecdotal evidence. Anecdotal evidence is not necessarily reliable, of course, but can still be extremely useful--it's worth noting that a patient's description of symptoms is anecdotal, and still very important to diagnosis. Watson is able to trawl through the internet, picking up the oodles of medical information out there and adding it to its memory banks. Being able to understand that, say, a "dry mouth" is the same as xerostomia can make legitimate use of all those confused forums.

Of course, Watson isn't designed to replace a doctor's diagnostic instincts. Instead, it's more like a futuristic reference book. There's simply too much information out there these days, in too many places and added too frequently, for any doctor to keep up. Watson could help keep track of all the new drugs, studies, journals, and anecdotal evidence.

Diagnosis systems using Watson are still likely a few years away, but IBM is working on ways to leverage Watson's abilities even to hospitals with budgets too small to afford a multimillion-dollar Watson of their own. iPad apps were mentioned as a distinct possibility--doctors could tap into an off-site Watson with an iPad, shoot off a few queries and receive an answer immediately. And as more medical data is digitized, Watson will only get stronger and more useful.

[Associated Press]

Which technology? Specifically, Drs. Jim Blascovich (of UCSB) and Jeremy Bailenson (of Stanford) cite the Microsoft Kinect, the Nintendo 3DS, and IBM’s Watson computer. They call these technologies “paradigm-shifting” for avatar conferencing and say that they make virtual meetings ready for the living room, classroom, and conference room.

This isn’t like videoconferencing--it’s far more immersive--nor is it like two avatars chatting in two-dimensional environs like Second Life. Essentially, you would use a photo to generate a true 3-D avatar to your liking--perhaps one that’s had a shower and dresses a bit more smartly than you do--and you and each of your meeting-mates would sit around looking, gesturing, and talking to each other in 3-D.

But it gets better. The Watson piece of the technology means avatars could be put on a kind of autopilot, where an AI takes over your digital presence, nodding politely at good points, laughing at jokes, and otherwise feigning attention while you hit the snooze button for the seventh straight time.

You could even tamper with your physical traits, Blascovich and Bailenson say, to make a better impression. Research shows that when a person’s face is subtly digitally morphed with that of a politician’s in an image, the person receives that politician more warmly even if they don’t share simpatico political views. The person won’t even realize the photo has been altered.

That means you could doctor your own features to exhibit some of those of a professor, a client, or a superior to gain a little extra goodwill. Of course, that might be considered unethical. Since you’re already sleeping straight through your 8:30 while some AI keeps your avatar nodding attentively, you might not want to push it.

[NYT]

The ICU is naturally an environment fraught with problems, but one of the most fundamental is an information glut--patients there are surrounded by equipment churning out streams of data about each one, yet there’s no way to distill all this data to its relevant meaning in real time (usually it’s broken down into notes by a nurse once an hour).

Meanwhile, all that meaningful data on blood oxygen levels, respiratory rates, heart rates, electrocardiogram, temperature, etc. is basically ignored because there’s no way to monitor everything for patterns or trends that might hide an underlying indicator. That’s what Artemis does. Grabbing data from both medical records and those real time sensors feeding data to the machine, Artemis’ algorithms look for signals that an infection might be taking root.

This is where Artemis begins to compute like Watson. The two are different in several ways, but Artemis was built on an analytics platform called InfoSphere that came out of IBM research just as Watson did. And both make decisions on the fly based on rapidly incoming data from multiple sources, no archiving necessary.

Conventional computers can hunt for trends or patterns in data just fine, but before they can do so the data needs to be written to hard drive and databased. Artemis, like Watson, takes its inputs on go. Information flows in, the software filters out the relevant bits (be they answers to questions or symptoms) and the rest of the data flows on downstream. In a world where data is being produced prodigiously, such a computing paradigm has great potential.

And in an ICU environment, it could be lifesaving. Artemis can handle multiple streams of data from multiple infants, monitoring for the telltale signs of an infection before it gets the chance to take root (it also helps doctors refrain from diagnosing false-positives). It could someday be deployed as a centralized, remote diagnosis system, accepting online data streams from faraway locations and serving ICUs around the world.

As such, Artemis is already going global; two Chinese neonatal ICUs will connect using the technology later this year.

[Technology Review]

Hey, it can win on Jeopardy, so let's put our lives in its hands

"Absolutely!" In Ferrucci's example, say Watson reads somewhere that "cytoplasm is a fluid that cushions the nucleus." Sharp Watson takes this information with a grain of salt, since it is uncorroborated. Later, Watson is told authoritatively that "cytoplasm is a liquid that surrounds the nucleus." At this point, Watson has burning questions to investigate, Ferrucci explains. "Is a liquid a fluid? Does surrounding mean cushioning?"

Awesome. Spoon-feeding information to a giant brain is not really a scaleable process, so I'm glad to know that the machine is using its skills to teach itself about the world, rather than being dependent on fallible meatbrains for deciding what it should learn next.

Meanwhile, having won on Jeopardy, Watson is getting a job in a hospital.

After the airing of the latest triumph (and crowning as a "new computer overlord" by trivia-master Ken Jennings [read his side of the story at Slate]), IBM announced Watson's next project: a foray into healthcare. IBM will be working with Nuance Communications, a company that works on speech recognition for medical diagnoses, as well as physicians at both Columbia University and the University of Maryland. They'll be working on using Watson's analytics in a way that'll help doctors make faster and smarter diagnoses--Watson is able to quickly scan mountains of information, from journals to prior cases and all kinds of other medical literature, finding relevant facts much faster than humans could. A one-word indicator in a patient's description of a symptom could trigger Watson to find applicable data, which he can do instantly, which a doctor could miss.

IBM and Nuance have a multi-year research project in the works, but expect to have some sort of commercial project ready within 18-24 months.

AI in prime time

Today at 7PM Eastern, the three-day mini-tournament will kick off, pitting IBM's supercomputer Watson against the two greatest modern Jeopardy! champions: Ken Jennings, who holds the record for longest winning streak, and Brad Rutter, who has taken home the most total prize money. It's an epic battle we've been looking forward to ever since we say Watson take on the champions in that preview battle last month--and it's finally here. But actual trivia knowledge may not turn out to be the deciding factor in the contest.

Over at Boing Boing, former champion Bob Harris (the 13-game Jeopardy! winner, not to be confused with the Lost in Translation character) lays out perhaps the most overlooked variable in Jeopardy!: the buzzer. We've been concentrating largely on the task of actually figuring out the answers to the questions (or questions to the answers--thanks for that weird rule, Jeopardy!), which for the layman is certainly challenging. The mix of trivia, riddles, puzzles, irony, and wordplay were assumed to be the toughest part of the game, but Harris lets us in on a secret: It's all about the buzzer. As he says, "At the top tournament level, every player can figure out nearly all of the correct responses, no matter how arcane."

When Trebek finishes reading a clue, a producer hits a button that flashes a light, telling the contestants the buzzers can now be triggered. Once you're at this top echelon of trivia mastery, the questions aren't the deciding factor--it's all about timing. Harris notes that "Since a computer can obviously react to the 'go' lights more rapidly and consistently than any human, it will probably win," providing Watson is allowed to buzz in as fast as possible. That corroborates what I saw in the practice match: None of the contestants, man or machine, actually got a clue wrong, and none went unanswered. This game may turn into a speed contest.

But that doesn't mean it won't be incredibly fun (and romantic) to watch.