Thursday, July 06, 2017
We Need To Keep The Progress In AI And Machine Learning In Perspective. Manage The ‘Hype Cycle’!
This appeared least week
by Evan Sweeney
Healthcare needs to recalibrate its expectations of AI and find ways for the technology to work with physicians.
Artificial intelligence is hitting its stride—at least when it comes to hype.
The unbridled excitement surrounding AI and machine learning technology is higher than ever before, so much so that it’s become a distraction for the medical community, according to two Stanford researchers.
Arguing that AI has reached the “peak of inflated expectations,” Stanford researchers say the healthcare industry needs to shift its focus to how rapidly evolving technology can improve care.
Arguing that AI has reached it’s “peak of inflated expectations,” Jonathan H. Chen, M.D., and Steven M. Asch, M.D., from Stanford University’s Department of Medicine wrote in the New England Journal of Medicine that healthcare can "soften a subsequent crash into a 'trough of disillusionment' by fostering a stronger appreciation of the technology’s capabilities and limitations."
One particularly radical example emerged earlier this month when venture capitalist Vinod Khosla said AI would soon render oncologists obsolete.
“I can’t imagine why a human oncologist would add value, given the amount of data in oncology,” he said during an event in San Francisco hosted by MIT, according to VentureBeat. “They can’t possibly comprehend all of the things that are possible.”
That's the kind of debate that is viscerally satisfying, but ultimately ineffective, the authors contend. Instead, healthcare would benefit from an approach that combines the talents of both humans and algorithms. Healthcare informatics experts took to Twitter on Wednesday night in support of that approach.
AI’s true value will be in decision support, Chen and Asch added. Current AI applications often reach conclusions that are already well known to patients. For AI to make an impact on clinical care, the technology needs to provide predictions that can influence care decisions enough to improve current practice.
There has been a lot of conversation about this area in the last year of two – especially regarding IBM’s Watson.
It is an area to keep a close eye on while at the same time keeping balanced in expectations.
Posted by Dr David G More MB PhD at Thursday, July 06, 2017