The mere mention of the military can cause civilians in particular to conjure up images of soldiers fighting in the battlefield with fighter jets flying overhead. But several innovations such as artificial intelligence (AI) are changing all of that.
When it comes to modern warfare, using military artificial intelligence has become a necessity. The armed forces’ operations rely heavily on intelligence gathering, which is where AI systems like drones come in handy. Aside from improving combat systems, these new devices can process field data more efficiently. The question that remains is: At what cost?
Benefits and Challenges of Using Military Artificial Intelligence
For years now, military operations have been evolving to include the use of sophisticated tools and AI devices. Here are some of the benefits of using military artificial intelligence, along with its corresponding challenges:
1. Improve Battlefield Threat Prediction
Recently, the U.S. Army launched the Aided Threat Recognition from Mobile Cooperative and Autonomous Sensors (ATR-MCAS) Program. It aims to integrate artificial intelligence use into reconnaissance missions to help people on the field predict where threats can come from.
The project, a collaboration with the Ammunition Initiative Task Force (AITF) and Carnegie Mellon University’s National Robotics Engineering Center (CMU NREC), aims to help the army foresee enemy movement and intent. With the aid of target recognition, drones, and machine learning (ML), soldiers can gather relevant data about their opponents and where an attack is most imminent.
The Challenge:
It would take years before ATR-MCAS can become a fully operational, combat-ready system. Additionally, the program cannot replicate a human intelligence officer or a trained sniper. Similarly, there are concerns about how the military can use these drones to track and monitor not only “enemies” but also ordinary citizens.
2. Streamline Military Operations
In case of a war or an armed conflict, all military personnel must process data rapidly to aid in decision-making processes. Data analysis is, however, often hampered by the use of different data-processing applications. Inconsistencies often arise.
Military AI allows armed forces to collect, categorize, and analyze data faster. A recon drone can, for instance, send real-time data to both ground and air forces at the same time. Intelligent software would also rid officers of the need to switch radio frequencies manually just to transmit relevant data to the proper authorities. In short, military artificial intelligence can help officers process and analyze data in real-time to come up with informed decisions.
The Challenge:
Developing algorithms for robotics and sensors can be tricky as most of the essential data would come from complex scenarios, something that machines may not be able to understand like humans. The people who feed data to military artificial intelligence systems may also be too busy battling enemies on the field and so send misleading information.
3. Enhance Personnel Selection and Training
One of the promising applications of military artificial intelligence is using ML to educate, train, and select enlisted soldiers and officers for specific tasks. Military artificial intelligence systems can do so without bias.
Military artificial intelligence would also prove useful in training. Commanders can design virtual exercises to prepare soldiers for battle better. Using intelligent algorithms, officers can create “dynamic enemies” that would improve as soldiers get better. Furthermore, military artificial intelligence systems can help create highly complex simulations to improve the tactical skills of personnel.
The Challenge:
While military AI can remain unbiased, their developers may not be able to do the same. And formulating effective training exercises requires a lot of data that may not be readily available.
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While military artificial intelligence provides several benefits, including saving lives, it is still bereft with challenges. And while it may make data gathering and analysis faster, it would still require human inputs to work.
