April 4, 2017 | Written by: Chad Kartchner
Categorized: AI/Watson | Mobile
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I know that, as a human, I have a limited capacity for knowledge. But, I also know that I can augment my knowledge.
I can form a support system, aided by computers that have the power to read, search and retain millions of documents. That support system has already begun on my mobile device.
Most of us have mobile devices with us all the time—so we can take pictures of our food. But we also use navigation, search and communication apps to help make faster decisions. When I can get relevant answers quickly, it suddenly unlocks an ability to get things done.
That’s fast. But, to really augment intelligence, I need more.
Creating a solution that’s both faster and smarter
At Honeywell Aerospace, I’ve been working on a mobile offering to help transform aircraft maintenance—by making it faster and more intelligent. I saw that airplane mechanics were using their mobile devices to take pictures of fault codes that they needed to remember and trace through maintenance manuals. In the manuals, each code would branch out to other codes. The mechanics had to chase and read each one.
I wanted to make that search process faster and more convenient for mechanics. But I wanted more than just a fast way to search manuals. I also wanted to help take the knowledge that one person accumulated over years of experience and get that information to another mechanic somewhere else. That’s where cognitive technology could come in, with machine learning that tracks which solutions are correct and adapts to suggest those solutions over time.
But, when we took a step back, we saw that we needed to start by starting over.
Making the solution more seamless, too
We needed to re-imagine this airplane maintenance solution as mobile first. We needed to recognize that mobile devices are a primary and ubiquitous interface—not just a way to access information that’s really designed for print or a computer.
Mobile devices can help us make faster and smarter decisions. But, to truly “augment intelligence,” we need to do one more thing: We need to make the solution as seamless as we can. We worked with IBM Business Partner SparkCognition to develop a solution that met mechanics where they were, letting them just enter symptoms, then showing them a list of suggested actions. That list of suggested actions adjusts and re-prioritizes top recommendations as our mechanics add more symptoms. Plus, the solution records feedback and adapts to suggest the solutions with the most success.
This approach moves us toward a seamless exchange of information, blurring the lines between individual knowledge and shared system knowledge. Further, as cognitive technology advances, it can make interfaces like this one more intuitive and information more accurate.
Moving forward with fuller knowledge
As we connect to the Internet of Things, we’re seeing opportunities to share knowledge with others who may not have any relationship, social or professional. Even our mobile devices now give us access to more knowledge than we could ever consume. To really augment our intelligence, we need the exchange of knowledge to be as fast, smart and seamless as possible.
We need the exchange to almost disappear. That’s where I see the need for cognitive technology. We can now make our interfaces more intuitive, our information more accurate and our knowledge more complete.
Note: This solution implements the IBM Watson Retrieve and Rank service, through the IBM Watson Developer Cloud, to help find and suggest the most relevant information to solve contextual issues.
For more, watch the IBM interview with Chad Kartchner below.