Russia’s MiG Corporation has already announced that its multirole MiG-35 fighter jet will be outfitted with artificial intelligence elements to assist the pilot in decision-making.
Russia is likely to launch a project under which artificial intelligence (AI) and machine learning will be introduced in the production and operation of military aircraft, according to reports.
The move aimed at ensuring flight safety was recently announced by the Ministry of Defense’s Flight Safety Service and JSC RT-Techpriemka, a subsidiary of the state-owned Rostec Corporation.
Airline operations are by and large foolproof but the addition of artificial intelligence (AI) will overcome human errors. For this purpose, big data could play a key role. The use of AI and machine learning could not only ensure flight safety but also lead to a new phase of air warfare.
According to reports, the system will use predictive analytics — prediction of potential future outcomes based on historical data. This growing new approach has an accuracy of up to 90%. It can be used in several phases of flight safety – manufacturing, operations, and repairment, thus making it possible to carry out long-term planning of product quality.
Thus, during production, the system will be able to predict possible future failures in the equipment. In the later stage of maintenance, it could detect factors affecting the functioning, showing the root causes of malfunction in that regard.
Russia’s MiG Corporation has already announced that its multirole MiG-35 fighter jet will be equipped with artificial intelligence elements to assist the pilot in decision-making.
Robert A. Pearce of NASA’s Aeronautics Research Mission Directorate stated that “as the systems become more complex, we’re going to need to apply artificial intelligence and big data analytics to help bring all this information together, help us extract insights and help us do the mitigations that are required in real-time before issues become incidents.”
It is not only military aircraft but also civilian ones that can be benefitted from these new methods. The Airbus A350, sometimes called the most advanced airliner, uses greater variety, volumes and velocity of data. This data can be transformed into useful information for flight safety through AI and machine learning.
In the military domain, AI could significantly enhance warfare capabilities. According to Air Power Asia, “AI shall provide enhanced air warfare capabilities like target identification, target designation, target tracking, optimized attack maneuver, and autonomous engagements.”
India’s federal government think tank NITI Aayog’s discussion paper on ‘National Strategy for Artificial Intelligence’ of June 2018 seemed to corroborate the claims that India’s high-quality research publications related to AI rank third in the world. But it will probably require a lot of funding to make that research a reality.
At present, the US leads in the field of AI use in the military domain with its Advanced Targeting and Lethality Automated System (ATLAS) and unmanned aircraft systems (UAS). But China is not far behind with its Ziyan’s Blowfish A2 killer drone which can autonomously perform many complex combat missions.
The latest Russian effort could increase the competition among these nations. “Thanks to new technologies, maintenance work is optimized, downtime will be reduced, and the operator will have complete information about the condition of the equipment and, most importantly, will be able to prevent equipment failures,” said Vladlen Shorin, Director General of RT-Techpriemka JSC.
“Now we are on the verge of a large-scale study, on the basis of which the model will be trained. To achieve maximum accuracy, it needs to be trained in several stages, adding or removing some datasets,” Shorin added.
But AI like other technologies has its flip-side too. The Airbus AF 447 crash on June 1, 2009, can partly be blamed on the AI disengaging autopilot due to inconsistent airspeed data input from blocked pitot tubes. At the end of the day, AI cannot compensate for human error in its programming.