...How the smartest computer on earth could shake up health care for 70m pharmacy customers

The artificial intelligence system known as Watson is going to supercompute your health. IBM and CVS announced on Thursday that they will work together to come up with algorithms that use physiological indicators and red-flag behaviors to predict whose health is fine and whose may be on the decline. The first stage of the deal will focus on patients with chronic conditions, such as heart disease and obesity, but after that the sky's the limit. Here's why the deal is poised to shake up the way you think about health care.

CVS has 7,600 retail stores, about 1,000 walk-in medical clinics, and a pharmacy program with more than 70 million participants. That's nearly 22 percent of the U.S. population. The IBM-CVS partnership could transform the roles of a pharmacist, retail clinic practitioner and your primary-care doctors and specialists. A routine trip to the drugstore could involve consulting with Watson at a kiosk about your health...

With mobile phones everywhere and wearable fitness devices proliferating, the average person is predicted to generate more than 1 million gigabytes of health data in their lives. IBM is working with Apple, Johnson & Johnson, and Medtronic to use Watson to glean insights about people's health and the effectiveness of interventions.

The way Watson and the Deep Neural Networks (DNNs) work are very complex. It is almost a black box like Skinner proposed for behavior. I don’t think there is a way of checking how a conclusion is reached. You could delete every reference to a behavior, but because people lie cheat and steal...not everyone and not every time, of course the computer would use the absence or presence of information as part of the trained network. DNNs just got out of the toy-box, in language recognition. With reliable data from more than a few million in the customer database and a few GIGABYTES on each person, the 2% outliers will be the ones in need. The real answer
will become:

We know what is the best treatment for you. And here are your options...by what and who it costs.

Then comes the harder part of what we will do when we find out that info.

Whoever says they have to use it just for medical care? They can have a separate secret one for “enemies of the regime” or “politically incorrect”
and a (ahem) special tag which feeds those names into the rest of the process (for the “real” no moar care flags) midstream.

Who’s gonna reverse engineer, or DNN the whole encapsulating process?

(Because, like you said, “science!”)

My assumption would be simulating markets and maximizing profits...more money in that than medicine, for the moment. Your idea of targeting of political enemies, I assume that is already in the works. But the work would be incredibly sensitive, garbage in garbage out. If you have biased input, the output will be biased.

As far as have a DNN look into itself...or another DNN for reverse engineering, I believe it would be about as complicated as unraveling the hidden meaning of DNA. We have small bits, that indicate certain problems. We cannot cut and paste, yet. We cannot replicate the sequence and put a simulation of the entity it came from, yet. There are protective codes we don’t have a clue about, even though the Nobel Prize went to someone who discounted the protective coding as junk DNA...he did not have to give the prize back.

In the new movie Ex Machina, and I have a mixed review of it, the Billionaire Wunderkind turned on all the devices he wanted to, to get the information to train his android human-like entities. We process information at a chemical speed mostly and the electronics is 100 to 1000 times (or more) faster. If we were to train a DNN with 1000 nodes for a year on a “problem”... how would we evaluate or deconstruct the way it arrives at conclusions? If we complicate that with what IBM has been working on for four years...an electronic synapse low power chip...

http://www.engadget.com/2014/08/07/ibm-synapse-supercomputing-chip-mimics-human-brain/

using Moore’s Law

>>That single-core prototype has now been significantly scaled up, leading to a new, production-ready SyNAPSE chip that blows past its predecessor with 1 million neurons, 256 million synapses and 4,096 neurosynaptic cores, all the while only requiring 70mW of power.<<

In five years, it should be 16 times more powerful. It is getting $53 million from DARPA. 4 billion synapses, hundreds of times faster than a brain synapse, the software is the limiting factor. It will drive your car, better than you will. Better than NASCAR drivers, a litter after that. And opening the black box, will lead to mostly scratching of the head wondering if studying phrenology would lead to more understandable conclusions.

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