A Temptation of AI in Military Affairs

Will the European Military miss the widow of opportunity for the 4th generation industrial-based force generation?

Keywords: National Defence, Artificial Intelligence, Weaponization, Security Strategy

Introduction

The human ability to collect information, make sense of a situation, optimise action, and learn while executing has been challenged recently in games, simulators, diagnoses, and real-time analysis. How may this development reflect future tactical combat-level decision-making? Is the machine going to win the man in combat?

Based on recent AI progress, artificial cognitive abilities and skills are emergently dominant compared to human competencies. In theory, the military may access Artificial Intelligence, which could:

• Gain knowledge from a zero-knowledge starting point through gaming against itself and, within months, master a given battle scenario’s technical, tactical, and possibly operational level features for victory.
• Anticipate adversary moves ahead, create a picture of potential scenarios, and predict adversary manoeuvring in 3-D space within seconds in a fully digitalised battlefield.
• Make short-term decisions within 80 milliseconds and optimise decisions simultaneously at technical and tactical levels.
• Identify lessons from the events and gain 150 years of theoretical combat experience teaching itself overnight.

At the same time, the price has decreased, and the availability of components increased to build lethal autonomous weapons from commercial products. A “slaughterbot” that nearly killed the president of Venezuela in 2018 could be built by an experienced hobbyist for less than $1,000. States are not able to control the manufacturing of lethal weapons as it becomes easier to weaponize commercial cyber-physical products of the 4th generation of industrial manufacturing.

During the ongoing War against Ukraine, the Russian military is massing troops and firing where their operational art finds the best course of action. However, even in Russia, the live mass is consumed too fast concerning available expendable and willing human resources.

China’s People’s Liberation Army Strategic Support Force (PLASSF) aims to counter U.S. dominance asymmetrically in all five battle domains through intelligentised ”combat capabilities for joint operations based on the network information system and the ability to fight under multi-dimensional conditions.”

U.S. DoD all-volunteer force recruiting has been declining for the past 15 years, and no silver bullet has yet been found to mitigate the gradual loss of human potential and competency. Furthermore, the 2$ trillion annual budget is struggling to maintain the required fleets of armament.

With the emerging Russian threat, European militaries are struggling to build up their military capabilities while the cost of defence material is rising, recruiting cannot address the need for enlisted, and deadlines to achieve national defence goals are closing fast.

Will the temptation of AI overcome the ethical concerns and generals fill their order of battle from the cyber-physical actors and sensors of the fourth industrial revolution?

How the Use of Artificial Intelligence May Impact Military Confrontation?

Digitalization changes human endeavours from physical to social level, including military affairs:

• Information operations and cognitive warfare are ongoing and taking place mainly outside of the military attention
• The physical battlefield is more transparent due to the density of sensors deployed
• Asymmetrically used, remote-controlled weapon systems challenge 2/3 generation industrial platforms on the battlefield
• Cyber electromagnetic effects have proven effective against current generations of military system of systems
• The ability of defence industrial production becomes a key strategic asset in prolonged conflicts like in Ukraine
• 4th Industrial Revolution-based (4IR) information, data, and algorithm-driven military affairs promise major advantages for commanders.

The traditional near-peer analyses of a number of arms and men with Lancaster I and II laws of attrition between BLUE and RED Forces are not sufficient when the battlefield and opposing societies change in different ways, culture becomes either an enabler or obstacle for the military to adopt new capabilities and the national and coalition defence industry either can or not produce and maintain 4th industrial cyber-physical armament. The main components of a model assessing the impact of AI in the military system of systems are illustrated in Figure 1.

Figure 1: A Model for assessing the impact of Artificial Intelligence technologies in military confrontation

Strategic Pressure Builds Up Between the European Union and Russian Federation Confrontation

Strategic analyses between the European Union and the Russian Federation bring up differences in resources and opportunities. Table 1 compares the larger but diversified European society against the smaller but more coherent society of Russia. Both populations are growing older and smaller over time. European society is producing more and dependent on exported energy whereas Russian society is smaller and dependent on energy exports. Both sides have about the same number of active troops, but European troops are more digitized than Russian. Furthermore, Russia has a wider base to recruit reservists than Europe and, with higher resilience against casualties, can play longer confrontation games. Both societies are exporting arms. EU exports advanced 3rd industrial generation armament whereas Russia produces surplus in 2nd and lower 3rd generation armament.

Table 1: Strategic comparison between EU and Russia concerning resources

European Union	Russian Federation
Democratic decision-making between 27 nation-states	One autocratic state with 193 ethnic groups
Over 448 M people, speak 24 official languages and believe in a god 52 %	Over 147 M people, speak one official language and believe 60% of orthodox
With a median age of 44.5 and a fertility rate of 1.46 live births per woman, society is in a negative population change	With a median age of 40.3 and a fertility rate of 1.42 live births per woman, society is in a negative population change
Produces 16.6 % of the world GDP Consumes 59 billion GJ energy of which 3/5 is imported	9th largest economy with 54% coming from oil and gas exports
Military expenditure 1.6% of GDP	Military expenditure 5.9% of GDP
Active-duty troops 1.34 million	Active-duty troops of around 1 million
Not tested but probably more fragile concerning casualties	Tolerates over 1200 casualties/day and is resistant even over 500 000 casualties over 2 years
Nuclear capable (FRA) with high digitalization level of Forces	Nuclear capable but low digitalization level of Forces
Exports over 20% (FRA, GER, ITA) of arms in the world	Exports 11% of arms in the world
Produces more 3rd and 4th generation advanced armament	Produces more 2/3rd generation bulk armament

Based on the analysis, it seems that Putin’s regime has a window of opportunity in using the smaller but coherent population to support less advanced but higher volume armed forces to achieve his political goals after he failed to use information operations and the European energy dependency to manipulate democratic decision-making. 

Military Capabilities Comparison Reveals the Gap for AI Opportunities

After the strategic level analysis, the following Table 2 takes the research one step down to the military operational analysis of systems performance and capabilities. Table 2 illuminates the fact that the EU military forces are somewhat minor to the Russian operational performance as the Russians can use wider avenues of attack (physical, information, cognitive and social) for their joint operations and gain dominance in social and physical realms. Military scenarios wargame with Russian 2nd and 3rd generation troops storming over the European side borders using the “shock and awe” or the “blitzkrieg” art of manoeuvring, bypassing the few defending forces and speeding towards the capitals, seizing them, and freezing the conflict as experienced in the 2014 invasion of Ukraine. 

Table 2: Operational-level systems analysis of the EU and Russian military capabilities

European Union	Russian Federation
Reactive rather than proactive political decision-making with slower implementation	Faster decision-making and implementation top-down through the regime
Open media and social media for foreign manipulation	Ability to wage information operations and cognitive warfare while protecting society from foreign manipulation
Advanced digitalization, data, and information but lacking knowledge creation	Ability to disable or suppress advanced technology on the battlefield (by jamming GPS, radars, sensors, and targeting emitters)
Few advanced 3rd generation industrial weapon systems lacking interoperability	Ability to manufacture higher volumes of 2/3 generation armament
Incohesive and non-interoperative forces with little or no combat experience	Ability to train simple, repetitive skills for technical military performance
	More advanced operational art with 3rd generation forces
Fragile societies in hardship and casualties	Ability to tolerate more casualties and societal hardships
Defence industry is not able to sustain or reproduce 2/3rd generation armament in masses	Ability to transfer society to support 2nd and 3rd generation Armed Forces power projection for a longer time

Because of the real or perceived underminer status of the EU military decision-makers, there is a temptation to invest in:

• more automated force (decreasing the probability of human casualties) against conventional fighters, 
• precision targeting payloads (preventing collateral losses when fighting in densely populated areas) versus area bombardment 
• faster identifying and recognising adversary manoeuvring on the battlefield (to use sparse blue forces more optimally)
• countering the dominant operational art of the red force (faster analyses of the available lines of operation and selecting effective courses of action)
• sustain advanced 3rd generation armament in taxing environment to improve capability availability (digital twins to pre-emptive maintenance)
• manufacture 4th industrial dual-use cyber-physical products in sensor and effector platforms (meeting the red 2nd and 3rd manufacturing advantage with 4th generation additive manufacturing).

Is the Digital Leap Possible for the EU Military Forces?

Digital leap or transformation is always challenging, particularly for the military, because of the nature of military culture to sustain command and control structure even in chaotic situation. Figure 2 provides some simple checkpoints to improve the transformation towards more digital, data-driven and artificial intelligence-enhanced force:

1. Define your strategic posture against your potential adversary to adjust goals and resources in balance
2. Define your process development opportunities and limitations for each core function, i.e., Force utilisation, generation, deployment/projection, sustainment, and support
3. Consider your Forces' ability to take steps on the digital transformation road
4. Define why you need to change. Is it to improve cost-efficiency in times of diminishing budgets, potential threats from adversaries, or just implement a transformation dictated by politicians
5. Consider the width of your leap towards the future, particularly, how wide transformation your current culture supports
6. Divide your transformation portfolio into three folders: unfreeze, move, and refreeze. 

Figure 2: A simple tool to improve success in military digital transformations

Artificial Intelligence and Fog of War

Done Improperly, Artificial Intelligence May Enhance the “Fog of War” Rather than Improve the Situational Awareness

For centuries, technology has been used to improve situational awareness, but the realisation has sometimes fallen short. The 1990s network-centric warfare initiative in the U.S. DoD developed operative situational awareness but neglected the tactical level, which exposed the military to micro-manage battlefield. Tactical Data Links have provided superior connectivity since the 1970s but a vast array of deployed datalinks have delayed the update of tactical communications and now there is a need for a wide leap from formatted messages to Internet Protocol data transfer. Computerisation of battle management has left the commanders with screens full of up-to-date, detailed information, but exposed to challenges in recognising the essentials from the amount of information. The development of technology introduces first time a cognitive-level companion to soldiers. Are they ready to trust artificial advice in stressful situations?

Figure 1: Evolution of Military Systems of systems

Recently, Artificial Intelligence technology (AI) has promised to bring visibility through the “fog on the battlefield”. There are four mistakes that the military should avoid in implementing Artificial Intelligence in this concern: 

1. New technology makes soldiering harder for individuals, although it adds capability;

2. AI introduces a new kind of cognition on the battlefield;

3. Decision-making will be accelerated to machine speeds; 

4. AI will introduce new ways for deception on the battlefield. 

Let’s look at each of them more in detail.

1. AI Will Make Individual Soldiers’ Jobs Harder Even Though It Increases the Capability of the Force

In the beginning, just flying a fighter used to be an all-consuming task for pilots. Then digitalization introduced expert logic to make flying simpler but same time introduced more sensors and weapon systems. Then sensors, aerodynamic systems, and weapons were integrated, requiring automation to manage threat, target acquisition, and flying situations.  Furthermore, systems become more complicated, including, e.g., guided weapons and electronic attacks in 5th-generation aircraft. The next (6th generation) fighter aircraft will be surrounded by several “autonomous air systems” (UAS) flying in formation alongside and the pilot needs to operate an even more complex swarm of platforms, sensors, and weapons. The complexity is beyond human control and needs AI enablement.

Figure 2: Wingman UAS aircraft concept

 

2. New Kind of Battlefield Cognition

Human understanding or cognition has been the ultimate decision-maker in previous wars. We spend long hours in general staff college to learn to understand the battle and study different analytical methods to make the best decisions. The implementation of AI technology in command and control introduces an “alien cognition”. AI has gone through a different military education. It does not necessarily follow human morale or values. The AI considers statistical correlations, calculates a long chain of probabilities, and optimizes through large decision trees. All of these are intuitively impossible for human cognition. The future battlefield requires social cognition and AI cognition to communicate and understand each other and thereby work together in human-machine teams better than individually. Commanders need to be educated in dealing with complex issues within human-machine relationships and build intuition to recognise when a human understanding is subordinate to machine cognition. 

Figure 2: New mixture of cognition on the battlefield

 

3. Human-speed vs Machine-speed

The pace of warfighting has increased throughout the history of war. The decision cycle (OODA) is getting shorter, and situations are more ambiguous and stressful. Ethical implementation of Artificial Intelligence requires humans in the OODA loop to ensure compliance with Laws of War and Rules of Engagement. All good when the situation unfolds at the pace of human understanding. But when hypersonic weapons are guided by artificial intelligence or an approaching fighter is piloted by AI optimized in a dog fight, slowly reacting humans in the loop will end with more casualties. Left in autonomous mode, the AI may conclude the situation totally against the mission of the operation and end up slaughtering innocent by-passers. On the other hand, current military risk-avoiding cultures are already keeping their defensive systems in auto-mode. The probability of this behaviour does not decline with more semi-automated systems on the battlefield. 

Figure 4: Intelligent hypersonic weapons change the pace of combat

 

4. Deception at Machine-speed

Information operations (INFO-OPS) are a significant part of contemporary military operations. INFO-OPS requires a massive amount of data that only Artificial Intelligence may make sense. Artificial Intelligence will command the information impact on individual behaviour at higher sophistication, scale, and lower cost than anytime before. It is already challenging for humans to recognise deep fake videos (manipulated real-time videos) from real ones. On the other hand, AI-enabled sensors are doing the primary image recognition in the machine-speed battlefield. Currently, people are playing with autonomous cars and taping traffic signs to appear different from the autonomous vehicles. The cyber, electromagnetic, and physical realms open a variety of attack vectors to mislead your machine or human sensors.

Figure 5: Earlier deception of intelligence analysts does not affect the Artificial Intelligence

Conclusion

In summary, AI deployment, just like new technology, may lead to mistakes and fatalities in military affairs. Nevertheless, the promise of military effects and impacts in adversary systems drives the development and fielding of AI-enabled sensors, effectors, and integrators. Soldiers need to be trained to understand the new artificial cognition, communicate with it, train it, recognise its strengths and weaknesses, and work together with it to win more fights than the adversary. The future battlefield requires officers with science, technology, engineering, and mathematics (STEM) skills more than ever before.

Sources:

https://warontherocks.com/2020/03/fog-friction-and-thinking-machines/

https://www.popsci.com/future-air-force-fighters-leading-drone-swarms/

https://www.popsci.com/china-drone-swarms/