Leidos: Building trusted, secure, and safe AI systems
“Leidos’ mission is to make the world safer, healthier and more secure. We take on some of the world's most interesting, challenging and data-centric problems,” says Ron Keesing, VP of AI and Machine Learning. Formerly known as Science Applications International Corporation (SAIC), the company was officially founded in 1969. Eventually splitting into two entities in 2013, Leidos (from ‘kaleidoscope’) has subsequently taken on a host of high-profile projects for clients, including NASA’s next-gen lunar landers, “the world’s longest supply chain” with the National Science Foundation, and the entire health record system for the US Department of Defense (DoD).
Among the company’s core tech competencies is the development of artificial intelligence (AI) and machine learning, which it hopes to gradually incorporate into all of its solutions. Referring to Leidos’ participation in the DARPA ACE (Air Combat Evolution) programme, Keesing says, “We're essentially taking a technology that came from the commercial world and we're using it to transform aerial combat.” Inverting traditional battle paradigms, wherein many people would control a single platform or aircraft, the company uses AI so that one person can administrate multiple aerial assets, both manned and unmanned, during the course of a mission.
It can be easy to forget that the purpose of AI should be to augment or improve the lives and working conditions of people. However, this concept is central to Leidos’ mission, as Keesing explains: “We combine humans and machines to be able to perform these missions better and faster. Leidos’ role as an integrator of AI technology comes from many different sources and we bring them all together into solutions that the US Government can use. Currently, we're using AI to transform the processing of veterans’ health benefits to make sure they’re receiving improved healthcare through natural language processing (NLP). This will enable faster claims and benefits processing with much higher accuracy and speed than was possible before.”
Despite having devised so many cutting-edge applications, Keesing emphasises the importance of keeping up with the latest AI-based research and promoting understanding among clients regarding the best way to use it. This is a perspective shared by the DoD, as well as the USAF, which are cultivating AI-led workforces. “Many across the community are also starting to appreciate what it means for AI systems to be ethical; we wouldn't want systems making crucial mistakes that could put human safety at risk.” As such, Leidos believes in building trust between humans and AI in order to foster comprehension and encourage its wider application. This is particularly crucial in the digital era, when large volumes of Big Data can overwhelm those not equipped to manage it. In this particular arena, Keesing states, AI is significantly transformative. “AI can be a crucial tool by helping to replace highly manual processes, therefore allowing humans to focus on the most important and challenging problems that machines can't solve.”
Questions relating to the security of AI continue to be challenging for the tech sector as a whole, and Leidos, for its part, is dedicated to addressing them, particularly as AI becomes further integrated into its product portfolio. Therefore, Keesing closes by encouraging everyone from students to senior decision-makers to invest their attention in AI’s development. “This is such an exciting time for people thinking about launching careers in AI and machine learning; how people understand AI will affect their systems and platforms. Whether we want it or not, this technology is going to transform every aspect of our world and Leidos is staying ahead to make sure the systems we're building are safe, secure and can be trusted.”
Dr Peng Wei: Designing the Future of Autonomous Aircraft
Air traffic is expected to double by 2037. According to the International Air Transport Association (IATA), the world will need 37,000+ new passenger and freight aircraft, and more than half a million new pilots—unless we come up with another solution. Right now, a George Washington University School of Engineering and Applied Science professor, Dr Peng Wei, is starting to research autonomous electric aircraft design.
NASA will fund the research, which will study how to minimise risks for electric vertical take-off and landing (eVTOL). As Airbus states: ‘Autonomous technologies also have the potential to improve air traffic management, enhance sustainability performance and further improve aircraft safety’.
Who is Dr Wei?
An assistant professor of Mechanical and Aerospace Engineering, Dr Wei has researched aircraft control, optimisation, and AI and ML applications in aviation. Over the next three years, he’ll lead the US$2.5mn NASA grant project in collaboration with researchers from Vanderbilt, the University of Texas at Austin, and MIT’s Lincoln Lab.
Why is His Research Important?
Even though the wide adoption of self-piloting cars, much less aircraft, is still far down the road, technologies that Dr Wei and his colleagues are researching will form the commercial transport of the future. But aviation manufacturers, in order to produce autonomous aircraft, will have to meet extremely high safety standards.
‘The key challenge for self-piloting capabilities is how the system reacts to unforeseen events’, said Arne Stoschek, Wayfinder Project Executive at Acubed. ‘That’s the big jump from automated to autonomous’. In the air, AI-piloted aircraft will have to manoeuvre around adverse weather conditions, such as wind and storms, and other high-altitude risks, such as GPS hacking, cyberattacks, and aircraft degradation. And the stakes are high.
‘If a machine learning algorithm makes a mistake in Facebook, TikTok, Netflix —that doesn't matter too much because I was just recommended a video or movie I don't like’, Dr Wei said. ‘But if a machine learning algorithm mistake happens in a safety-critical application, such as aviation or in autonomous driving, people may have accidents. There may be fatal results’.
What Are His Other Projects?
In addition to the new NASA research, Dr Wei has been awarded three other grants to pursue AI-piloted aircraft:
- A 2-year grant from the Federal Aviation Administration (FAA) in conjunction with West Virginia University and Honeywell Aerospace to investigate “learning-based” aviation systems
- A six-month SBIR Phase I NASA award with Intelligent Automation to mitigate airspace congestion at vertiports—the electric craft version of airports.
- A 1-year collaborative grant with the University of Virginia and George Mason University from the Virginia Commonwealth Cyber Initiative (CCI) to develop anti-cyber attack technologies and aviation video systems
Research like NASA and Dr Wei’s three-year programme will help improve how AI reacts and adapts to challenging air conditions. In coming years, autonomous aircraft will likely take off slowly, starting with small package delivery, then upgraded drones, and finally commercialised aircraft. But congestion issues will worsen until autonomous aircraft are the best alternative.
According to BBC Future, by 2030, commuters will spend nearly 100 hours a year in Los Angeles and Moscow traffic jams, and 43 cities will be home to more than 10 million people. The final verdict? Bring on the AI-operated transit.