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From Ukraine to Taiwan, can software really predict the outcome of a war?

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From Ukraine to Taiwan, can software really predict the outcome of a war?

The invasion of Ukraine by the Russia, with the recent Kiev counter-offensive, and the tension around Taiwan they have dramatically raised the geopolitical guard level. In a global scenario where the risk of armed conflicts even among superpowers it no longer represents a remote eventuality, it was inevitable that increasing attention would be paid to predictive software that assess which army has the greatest chance of success in war or in a given battle.

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Not just with AI

One of the best known is Mcosm (the acronym stands for Major Combat Operations Statistical Model), developed in Monterey, California, within the Naval War College. This system leverages data from 96 major battles and military campaigns that took place from the end of the First World War to today to evaluate the chances of success of opposing forces in a conflict.

Unlike machine learning-based artificial intelligence systems, this predictive model makes great use of human evaluations: Users must enter their own estimate of over 30 parameters, including the level of training of the forces in the field, their firepower, logistics, decision making and more. In a nutshell, the algorithm is limited to giving support to the military who use it, who must still have a thorough knowledge of skills of the opponent to make the most of the system.

Come explained in the Economist, the creator of Mcosm, Jon Czarnecki, in evaluating the chances of success of Russia in the initial attempt to conquer Kiev, gave a very low judgment (one in 7) to the decision-making skills of the top of Putin’s army. Also on the basis of this vote, the Mcosm system judged Moscow’s chances of success as “very poor” (two points out of a maximum of 7) and quite high (5 out of 7) possibility of the Ukrainian army to defend the city. An assessment that turned out to be correct, given that Russia had to abandon attempts to take Kiev.

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When computers intervene

If the Mcosm is a deterministic system (inserting the same parameters you always get the same result) and which relies heavily on human evaluations, other software works according to different and more refined logics: for example, Brawler Air Combat Simulation is an aerial combat simulation system produced by ManTech, a company specializing in military software.

By analyzing the performance data of a specific aircraft, as well as of the ground radar, ground-to-air missiles supplied to the enemy, altitude you are flying, the presence of rain and other elements, the system is able to evaluate which evasive maneuver would be able to make a US F-16 escape from chasing a Russian S-400 missile. By repeating this simulation over and over again, it becomes possible to instruct pilots on what is the behavior with the greatest chance of success in the event of an air conflict.

But if some of the elements taken into consideration from Brawler are objective (the performance of the aircraft or the speed of the missile), others risk, in an attempt to be as accurate as possible, to insert variables in the system that are almost impossible to estimate, including the skills of the pilots: “Those coming from democracies are considered to be more creative than those from authoritarian regimes, where personal initiative is discouragedā€, We always read in the Economist. An evaluation which in turn risks being excessively subjective and a victim of prejudice.

Despite the potential limitations, Brawler is not only employed by the US militarybut also by the British Ministry of Defense and (in a simplified version) by those of Taiwan and South Korea.

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What is the “defense metaverse”

Lo instrument more advanced (but still in the planning stage) is perhaps Pioneer, a system on which Bohemia Interactive Simulations, a company recently acquired by the British armaments giant BAEwho called it “a defense metaverse”.

This system would be capable of simulate the behavior of soldiers (also evaluating the military doctrine followed by their army), of tanks, ships and planes, also considering the terrain on which they must move, the weather, the weapons used and many other parameters. After making a few hundred simulations under different conditionsPioneer is able to suggest how and under what conditions to carry out certain military operations.

As always in the case of probabilistic models, no prediction proves to be entirely correct when tested in the field and the unknowns that no system (or general) had been able to predict turn out to be fundamental. Nonetheless, these systems are spreading to the strategic support level and it is easy to predict that they will play an increasingly important role. With the utopian hope that one day the armies will just clash in incredibly detailed simulations.

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