Thought Leaders in Artificial Intelligence: Allied Universal CIO Mark Mullison (Part 2)

Sramana Mitra: Can you take us through some use cases in your customer scenarios where you are seeing these kinds of impact?

Mark Mullison: Just a little more context and then I’ll get to the specifics. There are three big differentiators in Helios’s platform. The first is a proprietary attribute model that we use to store all the knowledge about the site. We organize that in a special way.

You might think, “Isn’t that just a big database? Doesn’t everybody have that?” In some sense, yes, but there’s a saying in the AI community that goes, “If you have the right knowledge representation, problem-solving is easy.” We’ve spent time to organize this information in a special way that allows us to reason over it.

The second big differentiator is the AI engine itself. That’s not the end of the story. The third component is a very sophisticated workflow engine. The reason that’s important is, if I were to tell you that a certain stock is going to double over the next six months, that information won’t be useful to you by itself. You have to act.

The workflow engine is the thing that makes sure that these recommendations coming out of the AI engine are acted upon. There’s value in all the three. When these three things come together, that’s when the magic happens.

You can start to imagine how all kinds of scenarios begin to play out that result in that reduction in security incidents. Let’s imagine that you’re starting to see that your claims data on a large site is starting to go up. You want to understand why that’s happening.

We can use the visualization tools to double-click down on accidents and start to see where and when they happen. Let’s say for instance that you slipped and fell in the cafeteria. You might set up a safety-focused tour around the lunch hour to have your security guards go to the cafeteria and look for slip hazards. If they find any, you might have workflows to put out the wet-floor sign and call maintenance staff. That’s how it works in the old way.

In the new way, because the AI engine is getting access to all information and because all our security professionals are collecting data as a by-product of doing their job, the engine is able to notice that trend for you and then create a recommendation that around lunchtime, somebody should go to the cafeteria.

It’s a good thing because it automates something that we could have done ourselves. The AI algorithms are so much more sophisticated, they look a level deeper and not only try to understand the obvious but also past that.

When we were beginning to test the AI engine, we constructed a bunch of demo data and contrived a story. But the AI engine didn’t know that. It deals with it just like it would deal with any live client.

This segment is part 2 in the series : Thought Leaders in Artificial Intelligence: Allied Universal CIO Mark Mullison
1 2 3