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1. La Intersección entre Inteligencia Artificial y Armas Nucleares: Riesgos, Beneficios y Recomendaciones

Author:
Manuel Herrera
Publication Date:
01-2025
Content Type:
Journal Article
Journal:
Revista UNISCI/UNISCI Journal
Institution:
Unidad de investigación sobre seguridad y cooperación (UNISCI)
Abstract:
Las innovaciones tecnológicas han sido clave en la evolución de la defensa militar, permitiendo a los Estados obtener ventajas estratégicas, como ocurrió en 1945 con la bomba atómica. Actualmente, la inteligencia artificial (IA) impulsa una revolución similar. Aunque su uso principal es civil y empresarial, varios países la están integrando en sus capacidades militares para ganar superioridad estratégica. La IA ya se emplea con éxito en drones y análisis de macrodatos, pero también comienza a aplicarse en sistemas de armamento nuclear, lo que podría tener consecuencias imprevisibles. Este artículo examina el impacto de la IA en las armas nucleares, centrándose en los sistemas de mando y control, y sus implicaciones para el equilibrio estratégico global. Se define la IA, se analiza su uso histórico en la Guerra Fría por Estados Unidos y la Unión Soviética, y se evalúan sus aplicaciones actuales. Finalmente, se proponen recomendaciones para mitigar riesgos asociados a su integración en el ámbito nuclear.
Topic:
Nuclear Weapons, Artificial Intelligence, Automation, and Machine Learning
Political Geography:
Global Focus

2. Cybersecurity Implications of Quantum Computing and Its Combined Use with Artificial Intelligence

Author:
Andrea G. Rodriguez
Publication Date:
01-2025
Content Type:
Journal Article
Journal:
Revista UNISCI/UNISCI Journal
Institution:
Unidad de investigación sobre seguridad y cooperación (UNISCI)
Abstract:
Quantum computing presents new market opportunities, but also significant challenges, particularly in areas such as cybersecurity. Although still in its infancy, quantum computing is maturing rapidly. If quantum computers can provide countries with new offensive capabilities - often in combination with artificial intelligence - it is arguably investment in the quantum communications agenda - in particular quantum networks - that can provide measures and actions to improve cyber defence.
Topic:
Science and Technology, Cybersecurity, Machine Learning, Encryption, and Quantum Computing
Political Geography:
Global Focus

3. Machine-Learning Theory and Its Policy Implications

Author:
Naod Abraham
Publication Date:
04-2024
Content Type:
Working Paper
Institution:
Centre for International Governance Innovation (CIGI)
Abstract:
The goal of this paper is to present an intuitive summary of computational learning theory, and its application for analyzing the most popular learning algorithms in machine learning, neural networks. This paper assumes no mathematical background or knowledge of machine learning from the reader. Throughout the paper, the important sections are presented using a pyramid approach (that is, in three levels). After introducing each major idea/topic, its policy implications and connection to Canada’s law are discussed. Finally, a summary of Canada’s relevant artificial intelligence law, with a case example, is given.
Topic:
Artificial Intelligence, Digital Policy, Emerging Technology, and Machine Learning
Political Geography:
Canada and North America

4. Exploring the Impact of Behavioural Factors and Personality Traits on Private Pension System Participation: A Machine Learning Approach

Author:
Can Verberi and Muhittin Kaplan
Publication Date:
01-2024
Content Type:
Journal Article
Journal:
Istanbul Journal of Economics
Institution:
Istanbul University Faculty of Economics
Abstract:
This study aims to investigate the effects of personality traits, in addition to basic financial literacy, private pension literacy and behavioural factors on Private Pension System (PPS) participation using machine learning algorithms. The PPS participation model was trained using both random forest and LightGBM algorithms, and the contributions of model inputs in the prediction of pension participation were interpreted using the Tree SHAP algorithms with swarmplots. The data employed in the empirical analysis is survey data collected from the Şırnak province of Türkiye with a sample size of 449. The findings of the study shows that: (i) PPS participation is more likely for females and middle-aged people; (ii) High basic financial literacy has a negative impact on PPS participation; (iii) Extraversion is the key personality trait affecting PPS participation; (iv) Advanced pension literacy has more impact on participation than simple pension literacy: (v) Present-fatalistic tendency is key behavioural factor and it negatively affects PPS; (vi) Present-hedonistic, conscientiousness, future-time orientation, and locus of control tendencies increase PPS participation. Furthermore, the distribution of colours in LightGBM has a greater degree of uniformity in both directions compared with the random forest algorithm. Finally, to increase PPS participation, the results of the study suggest the implementation of the following policy measures: Tailored pension literacy programmes can help to increase pension participation rates. Incentives should be created to prevent narrow-minded behaviour and establish a sense of protection and control around PPS, targeting middle-aged individuals and women.
Topic:
Economics, Behavior, Pension, Machine Learning, and Personality
Political Geography:
Turkey and Global Focus

5. Future Warfare and Responsibility Management in the AI-based Military Decision-making Process

Author:
Alessandro Nalin and Paolo Tripodi
Publication Date:
03-2023
Content Type:
Journal Article
Journal:
Journal of Advanced Military Studies
Institution:
Marine Corps University Press, National Defense University
Abstract:
The application of artificial intelligence (AI) technology for military use is growing fast. As a result, autonomous weapon systems have been able to erode humans’ decision-making power. Once such weapons have been deployed, humans will not be able to change or abort their targets. Although autonomous weapons have a significant decision-making power, currently they are not able to make ethical choices. This article focuses on the ethical implications of AI integration in the military decision-making process and how the characteristics of AI systems with machine learning (ML) capabilities might interact with human decision-making protocols. The authors suggest that in the future, such machines might be able to make ethical decisions that resemble those made by humans. A detailed and precise classification of AI systems, based on strict technical, ethical, and cultural parameters would be critical to identify which weapon is suitable and the most ethical for a given mission.
Topic:
Ethics, Weapons, Artificial Intelligence, Machine Learning, and Decision-Making
Political Geography:
Global Focus

6. PART II: Whale Songs of Wars Not Yet Waged: The Demise of Natural-Born Killers through Human-Machine Teamings Yet to Come

Author:
Ben Zweibelson
Publication Date:
03-2023
Content Type:
Journal Article
Journal:
Journal of Advanced Military Studies
Institution:
Marine Corps University Press, National Defense University
Abstract:
Current human-machine dynamics in security affairs positions the human operator in the loop with artificial intelligence to conduct decisions and actions. As technological advancements in AI cognition, speed, and weapon sophistication increase, human operators are increasingly being shifted to an on the loop where AI takes more responsibility in warfare and defense decisions, whether tactical or even strategic. Human operators are also falling off the loop, trailing enhanced AI systems as the biological and physical limits because humans are not the same for artificial intelligence in narrow applications. Those likely will expand toward general AI in the coming decades, presenting significant strategic, organizational, and even existential concerns. Further, how natural humans respond and engage with increasingly advanced, even superintelligent AI as well as a singularity event will feature disruptive, transformative impacts on security affairs and even at a philosophical level discerning what war is.
Topic:
Science and Technology, War, Artificial Intelligence, and Machine Learning
Political Geography:
Global Focus

7. PART I: The Singleton Paradox On the Future of Human-Machine Teaming and Potential Disruption of War Itself

Author:
Ben Zweibelson
Publication Date:
03-2023
Content Type:
Journal Article
Journal:
Journal of Advanced Military Studies
Institution:
Marine Corps University Press, National Defense University
Abstract:
Technological innovation has historically been applied in war and security affairs as a new tool or means to accomplish clear political or societal goals. The rise of artificial intelligence posits a new, uncharted way forward that may be entirely unlike previous arms races and advancements in warfare, including nuclear weapons and quantum technology. This article introduces the concept of a singleton as a future artificial intelligent entity that could assume central decision making for entire organizations and even societies. In turn, this presents what is termed a “singleton paradox” for security affairs, foreign policy, and military organizations. An AI singleton could usher in a revolutionary new world free of war and conflict for all of human civilization or trigger a catastrophic new war between those with a functioning singleton entity against those attempting to develop one, along with myriad other risks, opportunities, and emergent consequences.
Topic:
Security, Science and Technology, Machine Learning, Transhumanism, and War Studies
Political Geography:
Global Focus

8. Awareness of artificial intelligence: Diffusion of information about AI versus ChatGPT in the United States

Author:
Rajeev K. Goel and Michael A. Nelson
Publication Date:
11-2023
Content Type:
Working Paper
Institution:
Kiel Institute for the World Economy (IfW)
Abstract:
This paper addresses the awareness about the artificial intelligence across states in the United States. We uniquely create indices of Google internet search results for general AI awareness and about ChatGPT, normalizing alternatively by internet users and land area. An understanding of the awareness about AI would provide useful insights into regulatory attempts to monitor and guard the AI technologies, besides suggesting alternatives for laggard states to catch up. Econometric results to explain the drivers of AI awareness show that, ceteris paribus, more prosperous states had greater awareness about AI and ChatGPT. On the other hand, states with greater economic freedom had a lower awareness. States with more men to women has lower AI awareness when hits were normalized by area, but the reverse was true when weighted by internet users. States with a higher proportion of the elderly population were no different from the other states, while those with greater urbanization had more AI/ChatGPT awareness when the internet hits were weighted by land area. Finally, states bordering Canada were no different from other states, while states bordering Mexico generally had a lower AI/ChatGPT awareness.
Topic:
Urbanization, Innovation, Artificial Intelligence, Machine Learning, Digitalization, Gender, and ChatGPT
Political Geography:
North America and United States of America

9. Artificial intelligence and policing in Australia

Author:
Teagan Westendorf
Publication Date:
04-2022
Content Type:
Special Report
Institution:
Australian Strategic Policy Institute (ASPI)
Abstract:
ASPI’s Strategic Policing and Law Enforcement Program is delighted to share its new Strategic Insights report, Artificial intelligence and policing in Australia by Dr Teagan Westendorf. Digital technologies, devices and the internet are producing huge amounts of data and greater capacity to store it, and those developments are likely to accelerate. For law enforcement, a critical capability lagging behind the pace of tech innovation is the ability and capacity to screen, analyse and render insights from the ever-increasing volume of data—and to do so in accordance with the constraints on access to and use of personal information within our democratic system. Artificial intelligence (AI) and machine learning are presenting valuable solutions to the public and private sectors for screening big and live data. AI is also commonly considered and marketed as a solution that removes human bias, although AI algorithms and dataset creation can also perpetuate human bias and so aren’t value or error free. This report analyses limitations, both technical and implementation, of AI algorithms, and the implications of those limitations on the safe, reliable and ethical use of AI in policing and law enforcement scenarios. This publication closely examines usage of AI by domestic policing agencies to model what success looks like for safe, reliable and ethical use of AI in policing and law enforcement spaces. It also explores possible strategies to mitigate the potential negative effects of AI data insights and decision-making in the justice system; and implications for regulation of AI use by police and law enforcement in Australia. AI ‘algorithms’ or ‘models’ promise to: enable high volumes of data processing at speed, while identifying patterns human judgement is not capable of; supercharge knowledge management while (supposedly) removing human bias from that process; and operate with ethical principles coded into their decision-making. This ‘promise’, however, is not a guarantee.
Topic:
Science and Technology, Police, Artificial Intelligence, and Machine Learning
Political Geography:
Australia

10. Improved detection of chemical threats by sensor data fusion

Author:
Norbert Ludwig Kopp and Helge Koch-Eschweiler
Publication Date:
03-2022
Content Type:
Journal Article
Journal:
Security and Defence Quarterly
Institution:
War Studies University
Abstract:
This paper presents some aspects of sensor data fusion that were derived from the EU-SENSE project of the European Commission (Horizon 2020, Grant Agreement No 787031). The aim of EU-SENSE was to develop a novel network of sensors for CBRNe applications through the exploitation of chemical detector technologies, advanced machine-learning and modelling algorithms. The high-level objectives of the project include improving the detection capabilities of the novel network of chemical sensors through the use of machine learning algorithms and reducing the impact of environmental noise. The focus in this paper is on the detection and data fusion aspects as well as the machine learning approaches that were used as part of the project. Detection (in the sense of detectto-warn) is a classification task and improvement of detection requires enhancing the discriminatory power of the classifier, that is reducing false alarms, false positives, and false negatives. This was achieved by a two-step procedure, that is a sensitive distance-based anomaly/change detection followed by downstream classification, identification and concentration estimation. Bayesian networks proved to be useful when fusing information from multiple sensors. For validation purposes, experimental data was gathered during the project and the developed approaches were applied successfully. Despite the development of several new, helpful tools within the project, the domain of chemical detection remains challenging, particularly regarding provisioning of the necessary prior-knowledge. It might make sense from a coverage point of view to look into integration of stand-off detection techniques into a sensor network, including data fusion too.
Topic:
Science and Technology, European Union, Machine Learning, and Chemical Threats
Political Geography:
Europe