The Data Agenda

Friday, October 30, 2015

2 Sides of Watson

You may have seen the ads IBM has been airing for its Watson system recently. Here is one of them:



So cute and friendly, right?

Watson is IBM's cognitive computing system. IBM explains, “to understand the power of Watson, we must first understand cognitive computing and how it enhances, scales, and accelerates human expertise.”

Fast Company ran an article about Watson in its November 2012 issue.

By way of background, the article explains, “The way Watson solves problems—or, rather, the way it looks for answers, simultaneously sending out thousands of inquiries in all directions and then scoring the evidence it collects—is different from how other computers work. One person at IBM likens Watson's process to (1) gathering hundreds or thousands of possible solutions from a vast data bank, (2) pouring them into a giant funnel, (3) stirring with a dash of algorithms, and (4) letting only the best drip out of the bottom.”

A dash of algorithms? Who needs to explain chemistry when you can just make it sound like alchemy instead?

This human-created system must be beyond humans if “Watson can ingest more data in a day than any human could in a lifetime.”

Two quotes from that article stand out, and they stand in stark contrast to one another.

The first is, “Watson, in IBM's marketing schema, is here to help with our questions, rather than solve them. In the case of medicine, it—for Watson is not really a he—is here to support doctors, not replace them.” The industry term for this today is “decision support,” abbreviated DS, CDS (clinical decision support), DSS (decision support system), etc. Putting it another way, “Watson could provide any doctor anywhere with the world's best second opinion.”

Then there's the second quote. The article cited Mark Kris, “an oncologist at Memorial Sloan-Kettering Cancer Center in New York.” “I ask him what if Watson's request is denied. Kris seems amused by the question. Watson has already consulted the latest medical literature, and it's been trained by the best cancer doctors in the world. 'Who is the authority that is going to trump that?' he asks.”

Which is it, IBM? Is Watson only there to “accelerate human expertise” or will there be no authority “that is going to trump” the edicts of Watson?

One of these quotes represents how IBM is now selling Watson to the public.

The other represents how Watson can be used to enforce compliance with the agenda of whoever is feeding Watson information.

There is a whole host of questions that need to be asked about how this system is implemented.

How does Watson handle information in medical journals that conflicts? Does it assume the most recent recommendation is correct?

What happens when Watson is found to have been given incorrect information? (This question could apply to information from medical journals or in patient records.)

Does Watson have information on the cost of each option that is is calculating? Does it have information on who is paying? Can Watson make recommendations for making providers or insurers more profitable?

Should we really follow a system that is “seeing where the data sends it today”?

How do authorities handle things if the patient doesn't want the treatment that Watson recommends? What if the patient wants the MRI even if Watson hasn't recommended it?

IBM recently announced it is buying The Weather Company for its technology to integrate it with Watson. Some may be mistaking this for a move into the weather space. It seems doubtful that IBM built Watson just to have an entry into the already crowded weather-predicting market. While both weather and health deal in Big Data, it seems more likely that IBM wanted ownership of an already-established forecasting system to apply to health data. “A dash of algorithms.”

The Fast Company article explained, Watson renders answers “by giving not a single solution but a range of probable solutions, each backed up by Watson's evidence and ranked by its level of confidence. In the lingo of computer science, that makes the machine probabilistic rather than deterministic. One might say this trait gives Watson a humanizing glow of humility and diminishes concerns that it marks a stride toward a computer-led dystopia.”

If the U.S. federal government, a very large provider of health care in America, becomes a client of IBM's cognitive computing system, then the probability of Watson's recommendations becoming deterministic vastly increases. Given IBM's previous work with governments, this should stir us to vigilance.

If IBM isn't selling us anything directly during those sports programs we watch, then we do well to ask why is it trying to sell us something?

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