When Computers Get a Right Brain

IBM is increasing its commitment to Watson in a big way, which was evident in last week's IBM Think Forum. IBM believes that if it can find a product that thinks first, it can take full control of the technology market again, and every other company will follow it again.

It is making some impressive top routes, and I agree that the firm working on it will not only change the technology market on a large scale, but will also change the world. The very real result is that many of us will find that our skills have become redundant - and when I say "many of us," I include analysts, because we are clearly at risk.

I'll close with my product of the week: Gorilla Glass, which is likely to keep us from having more broken phone screens and possibly helping Apple to avoid taking back the iPhone 6 (though I still think that needed).

Watson's Surprise

Watson is an attractive system. I am referring to this class of systems as "decision engines", as they are intended to help people make better decisions. What makes them different from any other tool is that they learn about you, rather than you learn more about them.

Granted, with these early versions, it's more like a shared experience - but before systems like Watson, all efforts to find out how the user interface was. With Watson, the ultimate goal is to transfer almost all of this burden to the system.

This means that in the near future, when you need something from Watson, you will be able to produce immediately instead of spending weeks and months, which usually takes longer to learn a new system. Because Watson learns from you, the longer you work with it, the better it will be.

As more and more Watson computers are deployed, they learn from each other creating a digital gestalt that accelerates the learning process in a big way.

Near term expectations

There were many examples on the Thinking Forum of working systems and prototypes that show what Watson can do today.

For example, a hospital treating a cancer patient can look at the detailed information captured on the patient and then determine the highest probability path to well-being. Watson already has information about unexplained treatments and diseases, which he can apply to solutions.

The end result is a customized program developed from information gathered around the world - preventing both mistakes that have already been made and identifying lesser known successes to reach an optimal solution.

Watson can provide travelers with the same experience as travel agents once provided. For example, if your plane was delayed or grounded, it would automatically detect and suggest an alternate route for you to transit, which you could execute with one click like Amazon.

When asked to help plan a trip, Watson can find out what about you and the various airlines and hotels most likely to make the itinerary. You can travel anytime.

For help desk issues, it will take customers through custom decision trees defined by the capability of the system to remotely diagnose the problem and explore the caller's technical capability. It will be able to provide the fastest resolution for the lowest cost, while optimizing on a mix of customer satisfaction and cost control.

This will automatically identify bad trends for decision makers and, with customized recommendations, will solve both core issues in a timely manner and reduce associated costs.

The company testified at the Think Forum that they were seeing a large increase in customer satisfaction and were handling costs much better than Watson-type technology, which is still in its infancy.

Jobs at risk

Now with the next series of technology advances, there are a ton of jobs at risk - and not obvious, either. Experts are safe for a while, but people who provide general services - such as accountants, teller, bankers, stock traders and, well, analysts - are poor in the long term.

Fortunately, this will not happen overnight, and there will be some great employment training systems like Watson in the near term, but once trained, these systems will be able to train each other almost immediately.

It would be even longer before experts were at risk, as the cost of training a system like Watson to handle a specialty would outweigh the benefits for some time. If the attribute is specific, then the time may be uncertain.

Wrapping Up: The Future

The Think Forum wrapped up with a look into the future, and it was a fascinating discussion. Watson is like a left brain decision engine. It is very strong numerically, but it is like an extreme version of Sheldon on The Big Bang Theory. It is not very sympathetic, and it is not intuitive.

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