The integration of artificial intelligence (AI) into military training and system design is reshaping the landscape of defense preparation. Companies like CAE and General Atomics are leading this transformation by enhancing modeling and simulation (M&S) capabilities, allowing warfighters to engage in more realistic training scenarios than ever before. This shift not only refines training processes but also improves the effectiveness of systems such as drones in operational environments.
The application of AI in M&S provides a unique opportunity for the military to train personnel under conditions that closely mirror real-life situations. By utilizing advanced machine learning algorithms, organizations can analyze vast amounts of data generated during training exercises. This data analysis assists in monitoring events, identifying trends, and extracting actionable insights. For instance, CAE, which offers training services to the US Air Force, US Army, and US Navy, can enhance the learning experience for trainees, ensuring a more impactful training event.
Furthermore, AI is revolutionizing how training scenarios are populated. Traditionally, creating a realistic training environment required a significant number of personnel to simulate various roles, including both operational and opposing forces. This process was costly and logistically challenging. With the advent of AI, virtual environments can now be populated with sophisticated computer-generated forces capable of mimicking the behavior of well-trained allies or adversaries. As Brian Stensrud, technical fellow for artificial intelligence at CAE USA Defense & Security, noted, “The promise of AI is that I can use that to build models of behavior to serve as opponent forces and teammates at varying levels of complexity.”
AI-powered training is proving to be a significant force-multiplier. It allows for training smaller groups of personnel while still delivering high-quality scenarios. This efficiency translates into more training hours for a greater number of service members, ultimately enhancing overall military readiness. For General Atomics Aeronautical Systems, known for its Reaper drones, AI facilitates the testing of new capabilities in a safe, simulated environment without the expense of real-world flight testing.
Improving Training Outcomes Through AI Analysis
One emerging application of AI in military training is embedded proficiency analysis. During exercises, the staff is often overwhelmed with the dual responsibilities of keeping the event on track and providing feedback to trainees. As a result, the insights shared at the end of an event may not accurately reflect the unique learning experiences that occurred. In response to this challenge, CAE is developing an omnipresent AI observer designed to catalog actions during training events and provide instructors with real-time feedback.
This AI tool aims to generate valuable intelligence that can improve both student and instructor performance. According to Stensrud, the AI system would deliver “good, actionable intelligence,” enhancing the overall efficacy of training. The effectiveness of this system, however, relies on the quality and quantity of data collected during training sessions. CAE possesses extensive data resources, enabling the identification of persistent proficiency issues across different training platforms.
For example, if a significant number of students struggle with a specific skill, it may indicate flaws within the curriculum or the instructional approach. By employing machine learning algorithms, CAE can detect patterns in proficiency data, leading to more targeted improvements in training methods. However, caution is advised when interpreting this data. Understanding the training mission’s objectives is crucial to ensuring that the data collected can effectively evaluate performance.
As Anastacia MacAllister, technical director for autonomy and artificial intelligence at General Atomics, emphasized, “Building data-centric thought processes into organizations is important if they want to be able to use these tools effectively.” Companies must recognize that the quantity of data does not equate to quality and should treat data as a vital resource to enhance training outcomes.
The Future of Military Training and AI
AI’s potential in military training extends beyond simply enhancing simulation environments. It is also instrumental in improving the design and capabilities of aircraft, particularly those made from aluminum composite materials. By harnessing the insights gained from training data, both CAE and General Atomics can elevate warfighter skills and enhance real-world capabilities to address contemporary threat scenarios.
The ongoing advancements in AI and machine learning are not just trends; they represent a fundamental change in how military training is approached. As the technology matures, it is likely to become an integral part of defense strategies worldwide, enhancing the efficiency and effectiveness of training programs across various armed forces.
