Kenneth Cukier
speaker
76 appearances
1 recordings
1 series
first heard Mar 2013
last heard Mar 2013
Kenneth Cukier’s voice in public audio — every appearance, attributed to the second.
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Appearances
But this is just good for marketeers, isn't it?
Advertisers?
Absolutely not.
It's going to transform all aspects of society and our lives.
But just think of health care.
Go into a clinic and the doctor has to use his wisdom and his judgment and experience.
Many times he is completely wrong.
Instead, we should take an approach whereby we are looking into a database of correlations of all of our electronic medical records, of what treatments work with what sort of people, where are adverse side effects for drugs and depending on the machine to do things that we can't do and can do it better and depending on our judgment and our creativity to do what we do very well and blend the two.
Well, no, and one of the biggest reasons why is that the healthcare data is not either in electronic form, hadn't been because you never had the techniques to extract information from it before, or because there's actually rules protecting privacy that actively discourage the sharing of medical information.
This is heinous.
Future generations will be bewildered to wonder how medical service in the 21st century could have made decisions about human health without looking at the data of all of us and learning from correlations.
Correlations just simply mean that we find associations or links between two things.
So an example would be we might find out that everyone who takes one sort of drug and another sort of drug in combination becomes very, very drowsy.
It might be a side effect that we didn't know about before.
It might be too infrequent when it happens for an individual doctor to recognize.
But through big data correlations, the machine would groom all of the data and identify it, and then we'd know.
Well, that's right.
What you're referring to is spurious correlations.
And with big data, it's still a problem, but it was a problem prior to big data.
You're essentially saying that we're looking for needles in haystacks, and instead of finding a needle, we're finding a strand of hay.
Showing 21–40 of 76 · page 2 of 4
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