Artificial Intelligence and the Future of Warfare

The ideas of automating warfare have been conceptualized by various nation states for centuries. The first usage of what we today define as Unmanned Aerial Vehicle technology can be pinpointed to the use of the unmanned air balloon called ‘Vulcano’ by the then Austrian empire on the Italian city of Venice. The technology which was then used has grown many folds, most of which can be attributed to the cold war era, which saw an arms race between the Soviets and the Americans.

Earlier, the use of UAVs was limited to general reconnaissance. All of this changed with the introduction of two prototypes in 1971 by DARPA (Defense Advanced Research Projects Agency) called “Prairie” and “Calera”. They were powered by a modified lawn-mower engine and could stay aloft for two hours while carrying a 28-pound (13 kg) load. Since then, a full-fledged arms race for creating a better UAV drone has been on between the world powers. This technology has seen military success in various campaigns globally, such as the Vietnam war, Soviet invasion of Afghanistan, the American invasion of Iraq and Libya, etc. The technology itself still requires a human controller sitting afar from the war zone. Another one of its restrictions is that all UAV drones have to be controlled individually by the operators in general, hence, which not only limits the use of these drones in a larger capacity but also affects perfect coordination. These “shackles”, as Lockheed Martin prefers to call them, can be completely removed with the use of Artificial Intelligence in warfare, the use of which isn’t restricted to the control of just drones but also other offensive military infrastructure. Hence it won’t be factually inaccurate to predict that the future of warfare is going to be in the weaponization of Artificial Intelligence.

To better understand the nuances of AI, it is important first to understand the difference between an automated and an autonomous system. An automated system is one in which a computer reasons by a clear if–then–else, rule-based structure, and does so deterministically, meaning that for each input the system output will always be the same (except if something fails).

An autonomous system is one that reasons probabilistically given a set of inputs, meaning that it makes guesses about best possible courses of action given sensor data input. Unlike automated systems, when given the same input autonomous systems will not necessarily produce the exact same behavior every time; rather, such systems will produce a range of behaviors. Today when it comes to the use of Artificial Intelligence or the usage of machine learning based algorithms in the military sector, most of it is restricted to automated systems which, again, isn’t very popular in the defense sector due to the general belief that the technology is still in its primitive state.

FUTURE OF THE TECHNOLOGY

When it comes to the predictions made by researchers and academicians about the future of Artificial Intelligence in warfare and its uses, most of them can be classified as follows:

Use of AI in launching a cyber-offensive attack on the digital infrastructure of a nation-state

This function of AI has already seen the light of day as it was stated in the recent Pentagon report regarding the cyber military infrastructure of the People's Republic of China. The use of AI in launching a cyber-offensive makes it easier for a given party to launch DDOS attacks on certain infrastructure which may be fragile and susceptible to such attacks. Further, the use of AI in this area allows for the removal of the aspect of human error (which allows the one who is attacked to track down the assailant). The only defense against this is the use of machine learning and AI driven defense apparatus.

Note: The Pentagon report clearly states that the use of AI in the cyber sphere by the Chinese isn’t as advanced as the technology was in its early dates.

Use of AI in logistics and transportation

Unlike how boring it sounds, the use of artificial intelligence in logistics and transportation will be a revolution of its own. We will see self-driven vehicles operated by AI, transporting large scale ammunitions in tough terrains (like Daulat Beg Oldi, which hosts an Indian army camp at a very high altitude, close to the Chinese (/Tibetan? borders). The use of AI for this can help in decreasing the transportation cost and will reduce the human factors involved in general. It also enables military fleets to easily detect anomalies and quickly predict component failures. Recently, the US Army collaborated with IBM to use its Watson artificial intelligence platform to help pre-identify maintenance problems in Stryker combat vehicles.

Assisted target recognition

AI techniques are being developed to enhance the accuracy of target recognition in complex combat environments. These techniques allow defense forces to gain an in-depth understanding of potential operation areas by analyzing reports, documents, news feeds, and other forms of unstructured information. Additionally, AI in target recognition systems improves the ability of these systems to identify the position of their targets.

The capabilities of AI-enabled target recognition systems include probability-based forecasts of enemy behavior, aggregation of weather and environmental conditions, anticipation and flagging of potential supply line bottlenecks or vulnerabilities, assessments of mission approaches, and suggested mitigation strategies. Machine learning is also used to learn, track, and discover targets from the data obtained.

For example, DARPA’s Target Recognition and Adaptation in Contested Environments (TRACE) program uses machine learning techniques to automatically locate and identify targets with the help of Synthetic-Aperture Radar (SAR) images.

This technology has been used extensively in the Russian S-300 , S-400 series, as well as the notoriously well know Israeli Iron Dome – which detects an incoming missile or aerial projectile , identifies its nature and then fires a targeted retaliatory missile for the incoming missile to neutralize it while its airborne in order to prevent any ground casualty or damage to public infrastructure.

Battlefield rescue and immediate health care assistance

Rescuing wounded soldiers during active battlefield situations is one of the most dangerous positions and the cause of many military deaths. According to researchers, around 86% of battlefield deaths occur during the first thirty minutes post-injury. This is the reason researchers across the world are working toward developing artificial intelligence (AI) technology that can bolster battlefield healthcare.

Artificial intelligence (AI) can reduce serious injury and death on the field of battle. Most of the development is occurring in the application of robotic systems and unmanned ground vehicles (UGVs) to implement and provide aid in on-site surgery. Remote surgical systems – while still in the developing phase – could change the whole scenario of battlefield healthcare. Many private companies, as well as the U.S. military, are already investing resources that will ensure that semiautonomous technologies will be capable of providing different health care options for locations which have none. With on-site robotic surgical systems, healthcare personnel can perform “remote” or “unmanned” surgery. Even though currently, a human doctor is required to oversee a robot-performed procedure, the systems can be helpful in places where highly skilled medical resources and doctors are not available to perform complex surgeries, such as on the battlefield and in isolated enclaves.

Military reconnaissance

Threat monitoring & situational awareness rely heavily on Intelligence, Surveillance, and Reconnaissance (ISR) operations. ISR operations are used to acquire and process information to support a range of military activities.

Unmanned systems used to carry out ISR missions can either be remotely operated or sent on a predefined route. Equipping these systems with AI assists defense personnel in threat monitoring, thereby enhancing their situational awareness.

Unmanned aerial vehicles (UAVs) – also known as drones – with integrated AI can patrol border areas, identify potential threats, and transmit information about these threats to response teams. Using UAVs can thus strengthen the security of military bases, as well as increase the safety and efficacy of military personnel in battle or at remote locations. The ones which are widely available for this purpose are the Raven series (sold by Aerospace) and the DesertHawk-3 by Lockheed Martin and have seen extensive use in military operations.

Current scenario

In the current circumstances, investments in the Artificial intelligence sector have largely been centered around public utility. But with the continuous advances in technology, especially in the AI field, we can see further militarization of this technology. On an average, the current investments for R&D is at a 20 billion ball mark. The militarization and weaponization of Artificial Intelligence is the future, and no one can deny it. But to summarize, this technology’s effect is – ‘it seeks to eliminate the human factor or variable in warzone which can be haunting or blissful, depending on how one is to see it’.