Slashdot Mirror
IBM Promised Its AI Platform Watson Would Be a Big Step Forward in Treating Cancer. But After Pouring Billions Into the Project, the Diagnosis is Gloomy. (wsj.com)
Can Watson cure cancer? That's what IBM asked soon after its AI system beat humans at the quiz show "Jeopardy!" in 2011. Watson could read documents quickly and find patterns in data. Could it match patient information with the latest in medical studies to deliver personalized treatment recommendations? "Watson represents a technology breakthrough that can help physicians improve patient outcomes," said Herbert Chase, a professor of biomedical informatics at Columbia University, in a 2012 IBM press release. Six years and billions of dollars later, the diagnosis for Watson is gloomy [Editor's note: the link may be paywalled; alternative source]. WSJ: More than a dozen IBM partners and clients have halted or shrunk Watson's oncology-related projects. Watson cancer applications have had limited impact on patients, according to dozens of interviews with medical centers, companies and doctors who have used it, as well as documents reviewed by The Wall Street Journal. In many cases, the tools didn't add much value. In some cases, Watson wasn't accurate. Watson can be tripped up by a lack of data in rare or recurring cancers, and treatments are evolving faster than Watson's human trainers can update the system. Dr. Chase of Columbia said he withdrew as an adviser after he grew disappointed in IBM's direction for marketing the technology. No published research shows Watson improving patient outcomes. IBM said Watson has important cancer-care benefits, like helping doctors keep up with medical knowledge.
after they replaced the HR system, no one could figure out how.
Maybe because finding patterns without actually understanding anything is not really "intelligence". The AI hype is slowly dying and even non-IT/non-science-related people finally have finally come to a realization that ... not understand how these trained networks operate and that turns them into a black box you cannot really trust and which is bound to give absolutely wrong results.
1) AI is not a magical pill that can solve all the problems in the world
2) There isn't too much "intelligence" in AI
3) Coding real intelligence is a lot harder than using throwing reinforced convolutional neural networks at everything
4) We do
It's not like we understand how the human brain operates but we have certain reasons to believe it's mostly rational, intelligent and infallible (with exceptions, of course) since it has got us here - the age of technology and an improved quality and increased length of life which no other animal has been able to achieve.
I'm not against reinventing the biological intelligence that the human beings possess but it surely looks like we haven't come close to it.