Collecting and generating quality data sets to train artificial intelligence models needs to be a priority for the department, with some officials arguing it should be a requirement in contracts moving forward. By being proactive about collecting and generating data, the future of AI can be built on quality inputs, Michael Kanaan, director of operations at the Air Force's AI Accelerator at MIT, said Tuesday during the AFCEA DCAI and ML Technology Summit. Other technology officials endorsed the idea of being more aggressive about data collection rather than being "opportunistic" or working on old, lower quality data sets. For instance, the Air Force used quality data to train a machine learning model that turned the boards that officials use to manually track flight times into an automated, intelligent system. The ML system that replaced the "puck boards" ensured pilots got enough hours to maintain mission readiness.

Collecting and generating quality data sets to train artificial intelligence … For instance, the Air Force used quality data to train a machine learning …