When visiting a new city, a GPS app is a must have. But when drivers are travelling in their own hometowns, they often disregard their GPS’s directions, believing they know the best route. It’s a matter of trust.
Drivers don’t understand how their app arrived at its conclusion, putting more faith in their own instincts and sense of direction instead of a machine’s algorithm. As artificial intelligence and machine learning becomes more prevalent in society , trust and explanability are critical for its widespread adoption, especially in high-stakes environments, such as healthcare, national security and weather prediction.
Raytheon Intelligence & Space, a Raytheon Technologies business, is developing artificial intelligence and machine learning systems for space systems, cyber protection, the intelligence community and military that are transparent, explainable and reliable. AI systems that their customers can trust.
“I trust navigation systems, because I know how they work,” said Fotis Barlos, vice president of Analytics and Machine Intelligence at BBN Technologies for Raytheon Intelligence and Space. “A few times, I tried to outsmart Google Maps and I paid for it.
He added, “It’s the high-consequence missions where AI must prove its competence and trustworthiness, which is something that we’re doing at Raytheon Technologies and BBN.”
One area Raytheon Intelligence & Space specializes in is collecting, fusing and processing petabytes of data for the intelligence community and military, providing them with actionable information so high-stakes decisions can be made quickly. Without AI/ML, the mountains of images streaming down from its space-based sensors would require an army of imagery analysts and hours of time to sift through. Time and manpower that the national security professionals can’t afford.
“With machine learning, we are teaching AI to look at imagery and flag which images that an operator may need to pay attention to,” said Jack Allen, C2 Digital Solutions chief engineer for RI&S.
This human-machine teaming will cue up items of interest for analysts instead of them having to manually cull through screen after screen of useless images.
“One hundred images may be nothing but a blank desert, but one of them might have a missile in it,” Allen said. “AI can find the one.”
AI can recognize patterns in images, as well as shifts in activity. Then it can rapidly characterize the data, classify and identify objects, inform models and present human analysts with intelligence that predicts potential future outcomes.
Raytheon Intelligence & Space can also use AI’s ability to recognize patterns to help weather forecasters at the National Oceanic and Atmospheric Administration. Despite the chaotic nonlinear characteristics of hurricanes, NOAA accurately predicted the path of Hurricane Ida with the aid of AI/ML.
“NOAA uses a technique called ensemble forecasting where they use multiple models, multiple options and slight variations as well as historical data that we’ve collected over the years to predict the path and the strength of the storm,” Barlos said.
The same sort of ensemble modeling is being used for the 2021 California wildfires.
“Our sensors combined with AI could help identify escape routes and ML can optimize looking at fire patterns, where they're going and how fast they're going to get there,” said David Appel, vice president of C2 Digital Solutions for Raytheon Intelligence & Space. “It can identify and reroute first responders to be able to rescue men and women who are at risk.”