Military Artificial Intelligence

Military Artificial Intelligence

Military artificial Intelligence refers to the use of current technology in developing and operating machines, such as military robots and autonomous weapons systems (Allen & Chan, 2017). These machines are capable of performing progressively advanced military works, such as targeting adversaries without or with little human control. Artificial Intelligence (AI) is a fast-advancing field of technology with possibly important implications for national security (Allen & Chan, 2017).  Artificial Intelligence can also be defined as the development of computer programs or machines with the ability to think and learn mimicking human Intelligence via the use of algorithms. There are three main types of AI which are; Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Super Intelligence (ASI). Other than replacing real humans, highly advanced AI systems can handle vast volumes of field data more efficiently and improve the capabilities of smart combat systems. AI technologies hold great promise for facilitating military decisions, minimizing human causalities and enhancing the combat potential of forces, and in the process dramatically changing or revolutionizing the design of military systems (Gunning, 2017). This is especially true in a wartime environment when data availability is high, decision periods are short, and decision effectiveness is an absolute necessity. AI can offer essential help when choices must be made quickly or right away, considering a considerable measure of data, and when lives are at stake. From creating sophisticated flight plans to actualizing elaborate supply systems and devising simulation training, AI is a characteristic partner in the modern military (Cummings, 2017). The use of AI technology enables self-directed operations, leads to making progressively informed military decisions, and increases the scale and speed of military action.

AI systems have a regular life cycle. The first step in the development of an AI system is designing, data, and modeling. This encompasses planning and design, data collection and processing, and model building and interpretation.  The system’s concepts, objectives, and requirements are laid out, and a prototype is made. Data is gathered, and intended uses are outlined. Algorithms are created and calibrated. The second step involves verification and validation, which puts the model to the test. Deployment ensures compliance with set regulations and evaluates user experience. The last step is operation and monitoring, which involves continuous assessment of the AI system’s impact on society in accordance with ethics. Problems are identified in this step, and necessary adjustments are made.

Some examples or illustrations of AI systems include; autonomous driving systems, credit-scoring systems, AlphaGo Zero, and Assistant for the visually impaired. Autonomous driving systems are machine-based systems that make predictions like the presence of an obstacle and make decisions like accelerating. These systems create models of a car and its environment. It consists of several outcomes, for example, stops and goes. AlphaGo Zero is an AI system that plays a board game. It has both human-based and machine-based systems. The credit-scoring system has both human-based and machine-based inputs and has outcomes such as giving or denying loans. Assistant for the visually impaired makes recommendations on whether the person should avoid an obstacle. It perceives images of the environment by object recognition algorithms. This system provides outcomes such as sounds to describe particular objects. Military Artificial Intelligence exhibits both positive and negative effects.

To begin with, military AI has gone a milestone in ensuring cybersecurity. It is a capable defense system for cyberspace warfare. AI identifies vulnerabilities, bugs, and verifies codes. Artificial Intelligence offers protection to computers, programs, networks, and data against unauthorized access. In line with enhancing security, AI assists in the development of counter-attack tools after analyzing cyber-attack patterns. AI processes vast amounts of data from surveillance systems, which could otherwise be tedious and time-consuming when done technically by humans.

Military AI comes in handy in combat simulation and training. It provides simulations or decoys with unpredictable adversaries for training sessions. AI achieves customized and more realistic outcomes. Simulations could be made to mimic individuals, crowds, or complex environments. The Army Research Lab seeks to design simulation-based training programs with a reduced workforce. ARL desired synthetic training environment is only possible by the use of artificial intelligence in conjunction with distributed computing, machine learning, augmented reality, and data analytics, (Susan Miller, 2018). AI is also useful in creating training scenarios, delivering required instructions, conducting an automated assessment of trainees’ performance, and diagnosing outcomes from simulation-based training that involves mission command, aviation, and infantry.

Target recognition is another essential and advantageous aspect of military AI. Automatic Target Recognition (ATR) programs are much used in several military applications. The ATR programs can form a basis for the development of weapons such as missiles designed to destroy specific targets. Some ATR systems automatically detect and identifies specified goals by processing image data from a laser radar. (Richard & Seth, 1993).

Military Artificial Intelligence promotes battlefield healthcare. Robotic Surgical Systems, integrated with AI, carries out remote surgical and evacuation activities. These systems also assist in carrying out the complex diagnosis by processing the patient’s electronic medical records and ranking them according to how critical their health is. AI can also monitor threats and provide situational awareness. Reconnaissance (ISR) operations acquire and process information which is relevant to military activities. ISR missions are carried out using unmanned systems equipped with AI to increase their situational awareness. Crewless Aerial Vehicles (UAVs), which are also known as drones, are integrated with AI. Drones perform borderline patrols, identify potential threats, and communicate threat information to the response teams. ISR systems integrated with AI enhance the security of military bases as well as the efficacy and safety of soldiers during battle.

Despite the many benefits that come with the use of artificial military Intelligence, some challenges come with its application. One problem is that AI systems may result in unintended consequences due to defective data inputs. As indicated by O’Neil (2017), algorithms used in AI may deform reality and lead to wrong, unjust, and misleading choices. The problem of “garbage in, garbage out” can be intensified by AI. Usually, AI data originate from various sources, and it is not always collected carefully. Aggravating the issue of falsified results and incorrect data, AI regularly reflects human bias or makes new inclinations dependent on flawed learning from the data provided. It is difficult to distinguish similar objects, and even more difficult under deception and denial campaigns that may, for instance, use disguise and distractions. Sometimes, AI “fantasizes” things that don’t exist even when data appears accurate. Moving the deep-rooted issues of data interpretation reliability to the battlefield brings up serious questions about the security and safety that compliment attractive characteristics of lethality and speed (Turchin & Denkenberger, 2018). Accidentally hitting the wrong targets, for instance, could have consequences.

Another challenge is that countering some AI applications can be straightforward and clear. Adversarial control of data gives many chances for mischief and mistakes. The fact that AI data is easily altered welcomes efforts to undermine its desired military advantages. By corrupting data in intended ways, it may be possible to cause disastrous miscommunication, equipment failures, logistical nightmares, devastating mistakes, and confusion in AI-dependent systems (Turchin & Denkenberger, 2018). The black-box nature of AI, which makes it challenging to figure out why and how AI decides, likewise makes it hard to notice whether data is undermined and delivering incorrect results, for example, hitting the inappropriate targets or misleading allied forces.

The last challenge is that predictive analytics cannot be relied on for decisions of war and peace. There are fundamental differences in the means in which data is utilized for logistic, scientific, and economic reasons and human behavior prediction. Unlike decisions involving questions of peace and war, machine learning cannot be relied on for predicting the results of elections, international conflicts, or sports contests, within margins of acceptable error (Turchin & Denkenberger, 2018). Despite enduring concern in predictive analytics that can alert decision-makers on possible outcomes, trust in the power to predetermine results or incidents of conflict and war grounded on machine learning of big-data is filled with misplaced hopefulness. Just like the self-driving car perils, in which AI can correctly assess nearly all circumstances, a success rate of 90 percent in military applications could misinform decision-makers and put civilians and soldiers unnecessarily at risk (Turchin & Denkenberger, 2018). All the threats emerging from machine-learning bias, interpretive errors, and unreliable data are magnified when non-rational behavior, emotions, and inherent unpredictability cloud data and decision making. The outcome is an error with larger margins, which may be agreeable for purposes of research, but not for the ethical and practical demands of state security (Allen & Chan, 2017). When it comes to war, nuclear risks are involved, and therefore accuracy is demanded.

I think solutions need to be provided for the negative impacts of artificial military Intelligence. First, collaboration should be strengthened among stakeholder groups and across borders (Taddeo & Floridi, 2018). In my view, all over the world, people should be enlightened about the evolving concerns on artificial Military Intelligence and then agree on the best measures to tackle the AI’s challenges. Secondly, policies should be formulated to ensure that AI’s development will be aimed at the common good and augmenting individuals (Taddeo & Floridi, 2018). I would recommend a general transformation in the certification, regulation, and development of autonomous systems. The objective of autonomous systems should be to ensure that technology meets ethical and social obligations for the common good. Lastly, there is a need to shift the primary concern of political, education, and economic systems to encourage people to keep the technology pace just as the robots (Taddeo & Floridi, 2018). In my opinion, the formulation of regulations (ethical and operational standards) and policies should change the main concerns of the government and corporate to aim at the international advancement of humanity in line with technology, instead of nationalism or profits. It is crucial for countries to invest heavily in education systems, especially in this era of rapid technological advancements, to equip them with the necessary skills to tackle the increasingly critical cybersecurity vulnerabilities (Taddeo & Floridi, 2018).

Military Artificial Intelligence is associated with some dangers and ethics. Ethics concerning AI can be defined as the principles and guidelines for the use of AI by the Defense Department. AI systems used in the military are required to be reliable, equitable, responsible, governable, and traceable. Ethics ensure the security of AI systems, reflects on research goals and purposes. There is also a link between the development and application of AI technologies. Applied ethics are associated with the orientation of AI towards the common good.

Some dangers related to artificial military Intelligence are inclusive of the fact that even though AI enables machines to mimic human intelligence, it doesn’t exhibit emotions like love or hate, thus rendering them biased in-terms of decision-making evaluation. Another danger can arise on occasion where autonomous weapons fall in the wrong hands, such as in the hands of terrorists, which could lead to massive destruction and multiple casualties. Autonomous weapons are termed as being the third in revolutionary warfare, following gunpowder and nuclear weapons.

Artificial Intelligence affects society both positively and negatively. The application of artificial Intelligence in communities by incorporating it in buildings, vehicles, and business processes saves time, money, and even lives. It provides individuals with more customized services especially in education and healthcare systems. Computers accomplish tasks easily because they are equipped with sophisticated analytics, speech recognition, visual acuity, language translation, and pattern recognition. Due to its excellent reasoning and learning capabilities, Artificial Intelligence might even exceed human abilities. It is also applied in army missions to collect information and signaling electronic warfare.

Artificial Intelligence poses a threat to human autonomy, agency, and capabilities. AI can lead to loss of social control over their lives, data abuse, and also job loss. Data abuse in the sense that artificial intelligent systems do not have values and ethics and lack people skills especially when making decisions. Artificial Intelligence addresses issues such as global concerns while promoting growth and innovation. However, AI brings about ethical fears and anxieties. People require answers to questions such as whether it’s trustworthy. AI exhibits dangers in sectors like existing biases in decision making. AI systems do not respect personal spaces, such as privacy. AI also raises concerns regarding market concentration, climate change, inequality, and the digital divide.

Artificial Intelligence systems influence the environment by predicting, recommending, and deciding on outcomes. It affects both real and virtual environments. AI systems increase productivity and assist in problem-solving processes. As the systems are evolving from narrow artificial Intelligence to artificial general Intelligence, more reliable outcomes are expected. Artificial General Intelligence is a general-purpose technology that can be achieved via complementary investments in digitalized workflows, skills, and data. Changes to organizational processes are also crucial. Due to their general-purpose applications, AI systems have been absorbed in several areas, from transport to health.

AI has mostly been integrated into transport systems. This has been implemented via the use of autonomous vehicles, equipped with virtual driver systems, optimized traffic routes, and high-definition maps. The evolved transport systems provide outcomes such as safety to man and environment, thus increasing the quality of life. In health and scientific fields, AI systems assist in the collection of large amounts of data useful in the reproduction of experiments. The ability to obtain and analyze multiple data lowers research costs and speeds up scientific discoveries. AI systems have played a significant role in the early diagnosis of disease and infection by the use of self-monitoring devices. Obtaining relevant information also precedes disease prevention. The invention of new drugs and treatment methods is also a great achievement of artificial Intelligence.

Criminal justice systems apply AI in assessing the risks of reoffending and predictive policing. Real-time detection of threats and respond to such threats is tackled by AI systems integrated into digital security apps. Predicting environmental influences on-farm yields and monitoring the quality of soil and can be achieved by the use of artificial Intelligence. Positive effects of AI can never be overemphasized. AI systems can be used in financial departments to support legal compliance, reduce customer service costs, automate trading, and detect fraud. AI has dramatically improved marketing and advertising agencies by analyzing customer behavior, which helps in targeting and personalizing goods and services, recommendations and prices, and available information.

For the positive effects of AI to be entirely beneficial, it is essential to ensure that people have faith and trust in human-centered AI systems. This can be achieved by the implementation of national policies that encourage responsible research and development of AI systems. AI systems should be designed in such a manner as to be transparent and accountable for their expected outcomes. People should undergo continuous training and skills development to facilitate healthy transitions from analog to digital.

In conclusion, it is essential to note that AI technologies hold great promise for facilitating military decisions, minimizing human causalities and enhancing the combat potential of forces, and in the process dramatically changing or revolutionizing the design of military systems. The significant advantage of artificial military Intelligence is that it enables autonomous operations, leads to making progressively informed military decisions, and increases the scale and speed of military action. Despite numerous benefits of using AI in the military, some challenges come along with military AI. One of the problems is that AI systems may result in unintended consequences due to defective data inputs. Additionally, countering numerous AI applications can be straightforward and clear, which may lead to the corrupting of data by adversaries in intended ways.  Lastly, predictive analytics cannot be relied on for decisions of war and peace. Appropriate solutions need to be provided for the negative impacts of artificial military Intelligence; for instance, arms race ought to be addressed appropriately as well as the implementation of relevant policies.

References

Allen, G., & Chan, T. (2017). Artificial Intelligence and national security. Cambridge (MA): Belfer Center for Science and International Affairs.

Cummings, M. (2017). Artificial Intelligence and the future of warfare. Chatham House for the Royal Institute of International Affairs.

Gunning, D. (2017). Explainable Artificial Intelligence (ai). Defense Advanced Research Projects Agency (DARPA), and Web, 2.

O’Neil, C. (2017). How can we stop algorithms telling lies? The Guardian, 07-16.

Taddeo, M., & Floridi, L. (2018). Regulate Artificial Intelligence to avert cyber arms race.

Turchin, A., & Denkenberger, D. (2018). Classification of global catastrophic risks connected with artificial Intelligence. AI & SOCIETY, 1-17.

Delanoy, R. L., & Troxel, S. W. (1993, April). Automated gust front detection using knowledge-based signal processing. In The Record of the 1993 IEEE National Radar Conference (pp. 150-155). IEEE.

Wasilow, S., & Thorpe, J. B. (2019). Artificial Intelligence, Robotics, Ethics, and the Military: A Canadian Perspective. AI Magazine, 40(1).