Dream of Becoming a Pilot? Think Again
The U.S Military is looking to introduce robots to their flying squad in replace of modern day pilots. They are currently considering funding the huge task of automating all of its existing manned fleets into robot-piloted planes.
The U.S Military is looking to introduce robots to their flying squad in replace of modern day pilots. They are currently considering funding the huge task of automating all of its existing manned fleets into robot-piloted planes. The experts confirm that this is a relatively easy process, with no real modifications to the actual aircraft itself, eliminating custom design and integration costs.
As soon as the robot is placed in the cockpit, it immediately uses its vision-based recognition system to read gauges and operate all the other controls just as a human pilot would, operating the yoke and throttle using the same movements. There are many benefits to having a fully automated pilot system without having to develop new vehicles including the obviously reduced costs and not to mention the invaluable manpower that can now be used in areas of high need.
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Although some may feel that the thought of a robot flying a plane may be somewhat daunting. We need to remember that planes are already very much automated, and many commercial pilots actually do very little ‘flying’ during their journey, according to recent studies, and we may be safer in ‘robot hands.’ If the funding were to go ahead, the possibilities and benefits for the Air Force alone are quite significant. Just in being able to fly autonomous missions without spending time or money rebuilding aircraft is extraordinary, but this shift to robot-piloted planes could also mean a change in the likes of they way we currently see the commercial shipping or transporting humans operate in the near future.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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