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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