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Do you remember when IBM Watson (Jeopardy winner) was going to revolutionize medicine?

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Economist Gary N. Smith and Bradley Center director Robert J. Marks continued their discussion of many things AI, including John Searle’s Chinese Room, but talk turned to why Watson couldn’t turn its famous 2011 Jeopardy win into usefulness in medicine:

Robert J. Marks: Do you know the current status of IBM Watson? I’ve heard some bad things.

Gary N. Smith: They’ve been trying to go into all sorts of things with mixed success and one of the most hopeful things was that they would be able to revolutionize medical care, health care. And it’s not worked because they could look up symptoms of various diseases and they could look up cures for various diseases and they could look up medical articles. But they don’t understand which are more meaningful than others, which medical articles are reasonable and which are bull and so a lot of doctors have become disillusioned with Watson. And a lot of hospitals have literally pulled the plug. More here.


See also: Why did Watson think Toronto was in the USA? How that happened tells us a lot about what AI can and can’t do, to this day

Why an AI pioneer thinks Watson is a “fraud.” The famous Jeopardy contest in 2011 worked around the fact that Watson could not grasp the meaning of anything.

and

IBM Watson is not our new computer overlord. AI help, not hype: It won at Jeopardy (with specially chosen “softball” questions) but is not the hoped-for aid to cancer specialists. (Robert J. Marks)

Earlier discussions between Robert J. Marks and Gary Smith:

Why an AI pioneer thinks Watson is a “fraud.” The famous Jeopardy contest in 2011 worked around the fact that Watson could not grasp the meaning of anything.

Can AI combat misleading medical research? No, because AI doesn’t address the “Texas Sharpshooter Fallacies” that produce the bad data.

AI delusions: A statistics expert sets us straight. We learn why Watson’s programmers did not want certain Jeopardy questions asked.

and

The US 2016 election: Why Big Data failed. Economics professor Gary Smith sheds light on the surprise result.

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