High-Velocity Aim: Exploring the Abilities and Limitations of Artificial Intelligence
## AI Integration in D3A Targeting Methodology: Enhancing Military Operations While Maintaining Accountability
The D3A (Decide, Detect, Deliver, Assess) cycle, a fundamental framework in military operations and targeting methodologies, is undergoing a significant transformation with the integration of Artificial Intelligence (AI). This integration aims to optimize the targeting workflow, accelerate sensor-to-shooter kill chains, reduce cognitive burden, and improve commanders' decision-making in contested environments.
### Streamlining Decision-Making with AI
The 'Decide' phase of D3A involves critical decision-making, and AI can assist by providing rapid and accurate analysis of vast amounts of data, including intelligence reports and surveillance feeds. This can help in identifying potential targets more precisely and efficiently than human analysis alone. AI can also predict potential risks and collateral damage, aiding in more informed decision-making.
### Automating Detection and Improving Accuracy
In the 'Detect' phase, AI can automate the process of identifying targets from sensor data, reducing the time required for manual identification and increasing accuracy. Real-time data processing from various sensors provides timely and accurate information for targeting decisions.
### Precision and Adaptability in Delivery
The 'Deliver' phase benefits from AI's ability to calculate precise trajectories and adjustments for munitions, ensuring accurate hits and minimizing collateral damage. AI systems can make real-time adjustments to targeting parameters based on new data, improving the effectiveness of strikes.
### Rapid Assessment and Learning from AI
The 'Assess' phase involves evaluating the effects of strikes, and AI can quickly analyze post-strike imagery to assess damage and effectiveness. AI can also learn from data from previous missions to identify patterns and areas for improvement, enhancing future targeting strategies.
### Preserving Accountability with Human Oversight
While AI offers numerous advantages, it is crucial to ensure that human oversight remains a key component. Human operators must review and approve all targeting decisions to maintain accountability. AI systems should provide clear explanations for their recommendations, allowing humans to understand the logic behind AI-driven suggestions. Humans should continuously monitor AI systems to ensure they are operating within set parameters and to detect any potential biases or errors.
### The PLA's Approach to AI Integration
The People's Liberation Army (PLA) is also leveraging AI in military operations, reducing human delay while maintaining command oversight. This involves using AI for targeting and decision support, ensuring that while AI enhances speed and accuracy, human commanders remain responsible for critical decisions.
By integrating AI into the D3A cycle and ensuring human oversight, military operations can become faster, more reliable, and more effective while maintaining accountability. It is essential to codify decision points where human intervention is required and to ensure that AI is employed as a tool, not as a substitute for the warfighter's judgment.
Jesse R. Crifasi, a retired US Army chief warrant officer 4, is a senior advisor in the defense industry specializing in joint fires and targeting, and a PhD student in public policy and national security at Liberty University. Crifasi's work focuses on ensuring D3A remains both fast and just, anchored in human judgment, yet elevated by intelligent machines.
- The views expressed are Crifasi's own and do not reflect the official position of the United States Military Academy, Department of the Army, or Department of Defense. - Random forest and generative adversarial networks have been dismissed for their black-box characteristic, as they are incapable of justifying and rationalizing their targeting solutions. - AI offers scaling advantages, particularly in data processing and decision acceleration. - Crifasi has authored multiple doctrinal and technical assessments on digital fires and artificial intelligence integration in targeting operations.
- AI integration in the 'Decide' phase of D3A can assist military commanders by providing rapid and accurate analysis of data, helping in more informed decision-making and identifying potential targets more precisely.
- AI can automate the 'Detect' phase by identifying targets from sensor data, thereby reducing the time required for manual identification and increasing target identification accuracy.
- In the 'Deliver' phase, AI can calculate precise trajectories and adjustments for munitions, ensuring accurate hits and minimizing collateral damage, while also making real-time adjustments to targeting parameters based on new data.
- AI can quickly analyze post-strike imagery in the 'Assess' phase to evaluate damage and effectiveness, and can learn from data from previous missions to identify patterns and areas for improvement, enhancing future targeting strategies. However, it is crucial to maintain human oversight to ensure accountability, as AI systems should provide clear explanations for their recommendations.
