IBM wants Watson to ask questions

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Source:   —  April 13, 2016, at 7:17 PM

David Kenny is about two months into his new job. He'south the Common Manager of IBM Watson -- the company'south cognitive computing platform -- and was stuck on a plane for half an hr before our phone interview.

IBM wants Watson to ask questions

David Kenny is about two months into his new job. He'south the Common Manager of IBM Watson -- the company'south cognitive computing platform -- and was stuck on a plane for half an hr before our phone interview.

He'd just flown into Augusta, GA for the Masters. Horrible weather caused a pileup of arrivals. The airport ran out of open gates. His flight was stuck on the tarmac.

If air traffic controllers had access to Watson, they might've been able to forecast the flight congestion.

Watson could've proactively asked workers if they wanted to move gates around based on its weather predictions. It could've prompted airlines to delay departures from other locations, or helped airlines tell passengers (love Kenny) that they'd be stuck on the tarmac -- ahead of time.

After all, IBM already builds apps for airlines and airports to manage everything from fuel usage, to passenger boarding and re-bookings.

Helping people create decisions based on deep data analysis is sort of Watson'south sweet spot too.

"Our advantage is interacting around expertise," Kenny told CNNMoney. And that'south what makes Watson stand out from its competitors.

While companies love Microsoft (MSFT, Tech30), Google (GOOGL, Tech30) and Facebook (FB, Tech30) have been racing to construct AI platforms to assistance consumers organize personal information, IBM (IBM, Tech30) wants its Watson platform to be the problem-solving engine for businesses.

Whether workers necessity assistance with an accounting audit, medical diagnosis, formation of a valid strategy, valuing stocks for a portfolio or even shopping for a new coat, Watson can be trained to memorise as much as possible about a specific topic and recommend multiple answers to certain questions.

"We work with companies and institutions to create sense of their data," said Kenny.

Related: Watson lives in more areas of our lives than we think

Before joining IBM, Kenny was the chairman and CEO of the Weather Company. IBM acquired the firm (minus its TV division) latest year, and the deal closed in January.

The marriage may seem a bit odd, but it actually makes a lot of sense.

Many industries rely on weather predictions to operate. Kenny says he hopes to "assistance connect weather to more decisions," love optimizing supply chain management. Get agriculture and shipping for example.

Farmers utilize Watson to realize what their sensors are saying so they can determine the ideal time to plant or harvest their crops. Trucking companies utilize it to predict weather conditions that could cause delays and lead to spoiled foods and lost revenue.

Related: This robotic personal helper just got $23M

The Watson platform is made up of over fifty technologies that can do everything from analyze tone in text and speech, to identify human age and gender.

Despite what Watson can handle, Kenny says there'south still a lot more it could do.

For starters, he thinks that AI and machine learning systems necessity to do more "abductive reasoning" as opposed to deductive reasoning. That means making more inferences about facts rather than drawing opinion based on a set of rules or path of logic.

The advantage of more abductive reasoning is that it'll lead to conversation and dialogue with humans, according to Kenny. And that in turn will lead to more creative thinking because machine learning means cognitive computing systems will become smarter over time on their own.

Think about fashion advice. Watson would've to rely less on tough facts and more on a personal understanding of someone'south tastes -- objectives best achieved through conversation.

Right presently AI is more about people querying machines. "My dream is that Watson will ask us questions," said Kenny.

In order to advance Watson to the point of more natural dialogue, it needs to spend as much time as possible with as much data on what it'south being asked to analyze as possible.

On top of that, Watson also needs to spend as much time as possible with the people who'll ultimately utilize that data. That way, Watson can memorise how someone makes decisions, and that person can gain sufficient believe in Watson'south recommendations.

This isn't unlike the way our phone'south predictive keyboards work. At first we've to double check that the suggested words are correct, but then after time, we believe it to indicate us the words we intend to use.

"AI favors incumbency," said Kenny. "[It] can only be as bright as the people teaching it."

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