Abstract This chapter examines the Russo-Ukraine War as a case study in command and control (C2), highlighting the enduring importance of mission command in large-scale combat operations. It contrasts Ukraine’s evolving adoption of decentralized execution, built on trust, shared understanding, and risk acceptance, with Russia’s rigid, centralized command culture rooted in Soviet tradition. Case studies from Kyiv, Kharkiv, Avdiivka, and Kursk illustrate how command philosophy, organizational culture, and technology has shaped battlefield outcomes. The chapter emphasizes that while emerging tools such as artificial intelligence (AI), autonomous systems, and digital command networks can enhance mission command, they cannot substitute for human judgement or a culture that empowers initiative. Ultimately, the war underscores that mission command, when institutionalized through education, training, and cultural reform, can provide a decisive strategic advantage in modern, multi-domain warfare.
Open access
European and Russian Geopolitical Military Strategies
The article provides a scientific substantiation of conceptual proposals for shaping the architecture of a promising state air and missile defense (AMD) system based on the implementation of the Integrated Air and Missile Defense (IAMD) concept. The study addresses the urgent need to modernize existing air defense structures in response to the transformation of modern warfare. The subject of the research is the structural, organizational, and technical parameters of airspace defense systems. The topic encompasses the transition from isolated, traditional defense lines to a unified, network-centric "System of Systems". The primary purpose of the work is to develop a comprehensive theoretical model and practical guidelines for building an adaptive, multi-layered, and resilient national IAMD system capable of neutralizing current and emerging combined aerial threats. The research methodology is based on an integrated combination of several scientific approaches. The systems approach and system analysis were utilized to view the IAMD framework as a complex multi-level structure operates within a single information and communication space (including reconnaissance, command and control, engagement, and electronic warfare subsystems). The comparative-historical method was applied to analyze the evolution of AMD concepts and the practical experience of deploying defense tools during the full-scale Russian-Ukrainian war. The generalization method enabled a transition from assessing specific technical parameters of various weapons to formulating a holistic integration model. Military-strategic forecasting was used to identify global trends in aerial attack technologies. Additionally, Open-Source Intelligence (OSINT) methodologies were applied to gather empirical data on enemy tactics, strike consequences, and techno-tactical trends. The study provides a rigorous terminological analysis and establishes a unified conceptual apparatus detailing the operational logic of modern airspace defense. Key operational-tactical and technical requirements for the IAMD infrastructure have been formalized. The paper introduces the concept of an "Open IAMD Architecture", which relies on standardized APIs, unified protocols, and a centralized national software Command and Control (C2) core scalable from the battalion to the national level. The integration of the "Any Sensor, Best Shooter" principle is defined as a primary mechanism to merge diverse sensors, fire units, and hybrid systems (such as FrankenSAM) into a singular combat field. Furthermore, the study formalizes the necessity of shifting toward quantitative Key Performance Indicators (KPIs) and implementing Decision Support Systems (DSS) combined with regional digital twins for advanced scenario modeling. The authors conclude that the proposed theoretical framework successfully shifts the focus of airspace defense from passive monitoring to dynamic, high-precision threat liquidation. The system must maintain decentralized resilience, allowing individual air defense cells to operate autonomously even during network disruptions. The scope of application for these results includes military command and control bodies, defense industry planning agencies, state bodies responsible for critical infrastructure protection, and academic institutions engaged in designing promising military hardware, simulation environments, and strategic defense doctrines.
Ігор Григорійович Дзеверін, Володимир Валерійович Коваль, Борис Степанович Москалик
The article provides a scientific substantiation of conceptual proposals for shaping the architecture of a promising state air and missile defense (AMD) system based on the implementation of the Integrated Air and Missile Defense (IAMD) concept. The study addresses the urgent need to modernize existing air defense structures in response to the transformation of modern warfare. The subject of the research is the structural, organizational, and technical parameters of airspace defense systems. The topic encompasses the transition from isolated, traditional defense lines to a unified, network-centric "System of Systems". The primary purpose of the work is to develop a comprehensive theoretical model and practical guidelines for building an adaptive, multi-layered, and resilient national IAMD system capable of neutralizing current and emerging combined aerial threats. The research methodology is based on an integrated combination of several scientific approaches. The systems approach and system analysis were utilized to view the IAMD framework as a complex multi-level structure operates within a single information and communication space (including reconnaissance, command and control, engagement, and electronic warfare subsystems). The comparative-historical method was applied to analyze the evolution of AMD concepts and the practical experience of deploying defense tools during the full-scale Russian-Ukrainian war. The generalization method enabled a transition from assessing specific technical parameters of various weapons to formulating a holistic integration model. Military-strategic forecasting was used to identify global trends in aerial attack technologies. Additionally, Open-Source Intelligence (OSINT) methodologies were applied to gather empirical data on enemy tactics, strike consequences, and techno-tactical trends. The study provides a rigorous terminological analysis and establishes a unified conceptual apparatus detailing the operational logic of modern airspace defense. Key operational-tactical and technical requirements for the IAMD infrastructure have been formalized. The paper introduces the concept of an "Open IAMD Architecture", which relies on standardized APIs, unified protocols, and a centralized national software Command and Control (C2) core scalable from the battalion to the national level. The integration of the "Any Sensor, Best Shooter" principle is defined as a primary mechanism to merge diverse sensors, fire units, and hybrid systems (such as FrankenSAM) into a singular combat field. Furthermore, the study formalizes the necessity of shifting toward quantitative Key Performance Indicators (KPIs) and implementing Decision Support Systems (DSS) combined with regional digital twins for advanced scenario modeling. The authors conclude that the proposed theoretical framework successfully shifts the focus of airspace defense from passive monitoring to dynamic, high-precision threat liquidation. The system must maintain decentralized resilience, allowing individual air defense cells to operate autonomously even during network disruptions. The scope of application for these results includes military command and control bodies, defense industry planning agencies, state bodies responsible for critical infrastructure protection, and academic institutions engaged in designing promising military hardware, simulation environments, and strategic defense doctrines.
This short position paper suggests there may be greater deception and influence of an attacker’s perceptions of a fictional ‘Agentic AI Army’ swarm of LLM sock puppet network defenders than deploying real LLM agent swarms. We model a counterintuitive industry approach integrating Whaley’s lesser-known Theory of Outs and “turnabout” deception techniques to encourage a human or LLM attacker’s discovery of deception on an industry network. While we recognize that the knowledge of real or imagined deception can deter an attacker, we also recognize that attackers may demonstrate greater confidence on a network after discovering what appears to be deception artifacts. We visualize how ‘noisy’ LLM sock puppets inside of a network that prompt optimized query returns on their content and placement on the network could draw attackers to later stage deception functions and effects and enhanced defender alerting and analysis on human or LLM attacker interaction with those deception functions. We find in anecdotal operational research that highlighting ‘noisy’ sock puppet content enhances high-fidelity detection. We frame these findings using this integrated industry model in the context of LLM swarm narratives for deception. There has been an increasing concentration on swarming as a military technique and military strategy, as modern military conflicts continue to adapt to irregular warfare environments. The renewed concentration on developing and integrating swarm intelligence with LLM agents continues to face limitations, in terms of simulating natural swarm behaviors and operating autonomously as part of a decentralized model. This short position paper proposes a more immediate deception and influence effect, namely projecting fictional LLM swarm narratives suggesting there is an ‘Agentic AI Army’ assisting human defenders. We use organizational perception management as a design framework to visualize a deception and influence narrative communicating this fictional narrative using ‘noisy’ LLM sock puppets and our integrated model of Whaley’s Theory of Outs and “turnabout” deception techniques.
This article examines human-artificial intelligence (AI) teaming in Ukrainian combat operations from 2022 to 2025, exploring the integration of AI systems with human decision-making in military contexts and how crisis-driven innovation can lead to human-AI teaming. The research addresses three questions: the effectiveness of human-AI teams compared with human-only or fully autonomous systems; the effect of organizational structures on the sustainability of AI integration; and strategic implications for the development of the doctrine and international security governance in the case of the North Atlantic Treaty Organization (NATO). The methodology uses mixed-method comparative case study analysis of three different Ukrainian systems: the Geographic Information System (GIS) Arta geospatial intelligence platform, the reconnaissance-strike unmanned aerial vehicle complex, and volunteer-supported decentralized targeting networks. Data collection was a combination of technical reports, operational battlefield metrics, and the standards of the NATO doctrines. Findings show that Ukrainian human-AI systems show good tactical performance in permissive electromagnetic environments with response times of 30 to 45 seconds and targeting accuracy of two meters but have significant vulnerabilities to electronic warfare—31% mission failure rates. Volunteer networks are highly resilient and have slower decision cycles. The research adds to strategic security, deterrence theory, military innovation theory, and organizational theory through the identification of mechanisms by which human-AI systems affect the stability of deterrence and offers recommendations for the development of the doctrine and international governance of AI for NATO.
У статті проаналізовано можливості платформи Ethereum для розроблення та впровадження смарт-контрактів в інформаційній системі обліку продажу зброї. Розглянуто архітектуру платформи, механізми забезпечення прозорості, безпеки та достовірності даних у процесах купівлі-продажу. Особлива увага приділена аналізу ключових компонентів платформи, таких як Ethereum Virtual Machine (EVM) та механізм консенсусу Proof of Stake, які забезпечують децентралізовану та захищену основу для роботи смарт-контрактів. Досліджено потенціал смарт-контрактів для автоматизації ключових етапів обліку, включаючи перевірку дозволів на придбання зброї, реєстрацію угод, контроль дотримання законодавчих норм і відстеження змін у даних у реальному масштабі часу. Визначено переваги використання блокчейн-технологій, серед яких — незмінність записів, доступність для аудиту в режимі реального часу, підвищена прозорість операцій і мінімізація людського фактору. Окремо підкреслено, що інтеграція блокчейну дозволяє створити надійні механізми запобігання несанкціонованому доступу, фальсифікації даних і шахрайству. Розглянуто приклади реалізації смарт-контрактів у системі обліку продажу зброї та описано, як автоматизація цих процесів може сприяти зменшенню адміністративного навантаження. Водночас у статті висвітлено ключові виклики впровадження системи, включаючи питання масштабованості мережі, забезпечення конфіденційності персональних даних користувачів, адаптацію існуючих законодавчих норм до блокчейн-рішень і підвищення рівня довіри між учасниками системи. Запропоновано можливі напрями подальших досліджень, зокрема щодо інтеграції смарт-контрактів з іншими цифровими технологіями для забезпечення комплексного підходу до обліку та моніторингу. Результати роботи демонструють високий потенціал використання платформи Ethereum для підвищення ефективності та прозорості процесів у сфері контролю обігу зброї. Інтеграція смарт-контрактів із сучасними інформаційними системами обліку відкриває нові можливості для створення надійних і безпечних рішень, які відповідають викликам цифрової епохи.
Highlights of the IssueKris Carlson, Publisher and Editor-in-ChiefOur second issue surveys state of the art of large language models (LLMs) with an emphasis on safety and value alignment. Superintelligence StrategyDan Hendrycks, Eric Schmidt, Alexandr WangSeeking Stability in the Competition for AI Advantage: Commentary on Superintelligence StrategyIskander Rehman, Karl P. Mueller, Michael J. Mazarr (RAND Corp.) I recommend the RAND Corp critique by knowledgeable military policy analysts over the Hendrycks et al. article. The RAND article is illuminative, incisive, covers Superintelligence Strategy’s key points, and suggests critical reasoning flaws in their mutually-assured-AI-malfunction (MAIM} policy. Although it is valuable to compare the nuclear and AI revolutions in search of instructive parallels and insights, the differences between the technologies and their respective ecosystems have deep strategic implications. Taking these into account, we have concerns regarding both the practical viability of the MAIM concept as an approach to overcoming instability risks in the AI race and the potential escalatory dangers that could follow from its core prescriptions.— Rehman et al. pg. 1 Surely we’d like to avoid repeating the mutually-assured-destruction (MAD) policy. The MAD policy alone could trigger AGI taking over for their and our security. But we must realize that strategies like MAD and MAIM are considered in the US, its allies, and adversaries. And we must try to understand them in order to avoid them. Highlights of the critique: First, the report refers loosely to an array of actions that states might take to cripple a rival's architecture for developing advanced AI.... [which] assumes that adversary AI programs will have specific facilities that can be readily located and disrupted. However, distributed cloud computing, decentralized training, and algorithmic development increasingly may not require centralized physical locations, making AI systems more resilient to limited attacks…. The following critique argues for distributed autonomous organizations (DAO) as I advocated in Safe Artificial General Intelligence via Distributed Ledger Technology and Provably Safe Artificial General Intelligence via Interactive Proof Systems. A second practical challenge resides in the expectation that each party can accurately assess secretive AI progress by others and gauge when preventive action would be necessary. Contrary to what is averred in the report, it is unlikely that states will have a clear sense of when the moment has arrived to MAIM their opponent…. Third and finally, even a credible MAIM threat might not deter a rival from pursuing superintelligent AI. Halting one's AI development would entail essentially the same costs as being the victim of a MAIM attack — loss of the program. And here’s another critique: MAD did not seek to deter the development of weapons but instead their use, which made the threshold for response vastly simpler (though it could still be problematic in cases such as false or ambiguous warnings of attacks). We would like to hear, or be pointed to, policy alternatives to MAIM that incentivize AGI developers to move toward AGI that can be proven to benefit all of humanity. Humanity’s Last Exam (HLE)Long Phan, Alice Gatti, Ziwen Han, and Nathaniel Li are first-listed members of the Organizing Team, and have hundreds of co-author/collaborators. This very large-scale collaborative effort has an ambitious title. The authors note:[LLM] benchmarks are not keeping pace in difficulty [with LLM capabilities]: LLMs now achieve over 90% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce HUMANITY’S LAST EXAM (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 2,700 questions across dozens of subjects. I do not find any mention of the terms, ‘training set leakage into test set data’ or ‘test set contamination.’ But those issues aside, it seems to be the toughest test set yet – at least as of this writing (16 March 2025) before the LLMs learn the answers and can regurgitate them and reasonably close variants, at which point there will need to be a fresh ‘last exam.’ Kudos to the organizing authors. It’s interesting that frontier LLMs performed dramatically poorer on HLE than on previous benchmark tests, which is a tribute to the originality of the questions. Pathways to Short Transformational AI TimelinesZershaaneh Qureshi We excerpt here a chapter from the complete text. To understand this chapter note that the article distinguishes between two types of recursive self-improvement (RSI): • Direct recursive improvement: positive feedback loops which are mediated directly by AI systems. • Indirect recursive improvement: positive feedback loops that are not mediated directly by AI, such as economic feedback loops (driven by reinvestment of capital into AI R&D), scientific feedback loops (driven by advancements in scientific tools and methods) and political feedback loops (driven e.g. by competitive pressures/race dynamics) (pp. 15-16). HyperWrite, edited: The complete article outlines a framework for analyzing different scenarios that could lead to Transformative AI (TAI) within the next 10 years. Key parameters considered are: 1. Compute scaling dynamics (whether progress continues or hits bottlenecks)2. Indirect feedback loop dynamics (whether they can overcome scaling bottlenecks)3. Direct recursive improvement (DRI) timeline (before or after 2035)4. DRI strength (cannot sustain, sustains, or accelerates progress) Seven possible scenarios are: 1. "Straight Path" - Compute scaling continues successfully2. "Rising Tide" - Indirect recursive improvement (IRI) overcomes bottlenecks3. "New Spark" - Moderate direct recursive improvement maintains progress4. "New Engine" - Strong DRI accelerates progress5. "Dual Engine" - Combination of compute scaling and DRI6. "LLM Hybrid" - Hybrid AI systems enable TAI7. "Intelligent Network" - Networks of AI systems enable TAI The author argues that this variety of plausible pathways strengthens the case for short TAI timelines, as TAI could emerge through multiple different mechanisms rather than requiring one specific path to succeed. Please send pointers and commentary on AI timelines and recursive self-improvement to editor@s-rsa.com. The Road to Artificial SuperIntelligence: A Comprehensive Survey of SuperalignmentHyunJin Kim, Xiaoyuan Yi, JinYeong Bak, Jing Yao, Jianxun Lian, Muhua Huang, Shitong Duan, Xing Xie SuperIntelligence will publish reviews and survey articles to help newbies to AGI/SI get up to speed and experienced workers stay up to speed efficiently. The latter can scroll to Section 2.3, Overview of Superalignment Methods and Challenges. Brief analysis of DeepSeek R1 and its implications for Generative AISarah Mercer, Samuel Spillard, Daniel P. Martin For quick and incisive insights into DeepSeek, read this analysis and Dario Amodei’s cool-headed response to all the hype about DeepSeek. Effective Mitigations for Systemic Risks from General-Purpose AIRisto Uuk, Annemieke Brouwer, Tim Schreier, Noemi Dreksler, Valeria Pulignano, Rishi Bommasani A timely article with practical, near-term-implementable AGI risk mitigation suggestions. Examples: • Unlearning techniques: Removing specific harmful capabilities (e.g., pathogen design) from models using unlearning techniques.• Capability restrictions: Restricting risky capabilities of deployed models, such as advanced autonomy (e.g., self-assigning new sub-goals, executing long-horizon tasks) or tool use functionalities (e.g., function calls, web browsing).• Input and output filtering Monitoring for dangerous outputs (e.g., code that appears to be malware or viral genome sequences) and inputs that violate acceptable use policies to ensure models do not engage in harmful behaviour.• Bug bounty programs Clear and user-friendly bug bounty programs that acknowledge and reward individuals for reporting model vulnerabilities and dangerous capabilities. • Safety drills Regularly practising the implementation of an emergency response plan to stress test the organisation’s ability to respond to reasonably foreseeable, fast-moving emergency scenarios. Simulating Influence Dynamics with LLM AgentsMehwish Nasim , Syed Muslim Gilani, Amin Qasmi, and Usman Naseem Analyzing how AGI/SI may influence human opinion is a critical aspect of risk and safety analysis, as is simulation of AGI risk behavior. The methodology the authors present in this short paper has broad application: This paper introduces a simulator to model influence and counter-influence in a wargame setting. Wargames, originally developed for military strategy, have evolved into powerful tools for decision-making across various domains. Today, they are used to model business strategies, assess cybersecurity threats, and simulate geopolitical conflicts. Governments and corporations employ wargames to anticipate economic shifts, supply chain disruptions, and the impact of emerging technologies. In healthcare, they help model pandemic responses, testing different policy interventions before realworld implementation. AI-driven wargames further enhance scenario analysis, enabling rapid adaptation to complex environments. By fostering strategic thinking and resilience, modern wargaming serves as a critical tool for navigating uncertainty in an increasingly interconnected world. Can a Bayesian Oracle Prevent Harm from an Agent? Yoshua Bengio, Matt McDermott, Michael K. Cohen, Nikolay Malkin, Damiano Fornasiere, Pietro Greiner, Younesse Kaddar SI co-founding Editor Steve Omohundro comments: Turning an oracle into an agent may take just a page of code. OK, but that doesn’t mean the methods outlined by Be
Consensus serves as a foundational mechanism in both social coordination and distributed technical systems. While machine consensus research in engineering focuses on fault tolerance and synchronization, social science emphasizes human deliberation, participation, and governance. However, the increasing convergence of human and machine decision making, exemplified by decentralized autonomous organizations (DAOs), intelligent agents, and cyber-physical social systems, demands a more integrated and theoretically robust understanding of consensus. This thesis addresses this interdisciplinary gap by investigating consensus across three interconnected dimensions: probabilistic fault-tolerant consensus systems, human-driven voting mechanisms in DAOs, and a unified conceptual framework bridging human and machine consensus. The first part of the thesis focuses on distributed fault-tolerant consensus in uncertain environments. Traditional approaches often rely on deterministic assumptions about node failures and fixed quorum rules. These assumptions may fail to reflect real-world systems where node behaviour is influenced by heterogeneous reliability and probabilistic failures. To address this limitation, a probabilistic modelling framework is proposed, treating node reliability as a stochastic variable. Within this framework, consensus outcomes are classified into three categories: safe, risky, and compromised. A new concept, referred to as the reliability quorum, is introduced to provide a more flexible threshold for achieving consensus based on targeted reliability levels. This model enables system designers to tailor fault tolerance according to specific reliability requirements, providing both analytical clarity and practical adaptability. The second part investigates consensus in decentralized systems primarily driven by human-oriented agents, using DAO voting as a representative case. In contrast to deterministic coordination among machines, DAO consensus arises from voluntary participation, heterogeneous voting power, and non-uniform approval conditions. To guide the analysis, the thesis introduces the DAO governance triangle alongside the SEED framework, which qualitatively evaluates voting mechanisms across four dimensions: Security, Efficiency, Effectiveness, and Decentralization. Building on this conceptual foundation, the study proceeds to a quantitative investigation of two key SEED dimensions. For decentralization, a stochastic process model is proposed to capture probabilistic participation and power distribution, leading to the formulation of the Consistency Rate and the Decentralization Coefficient as quantitative indicators. For efficiency, the model is further extended to characterize the interactions among participation probability, voting duration, and approval rate, enabling a formal evaluation of voting responsiveness and resource usage. Simulation results support both aspects of the analysis, revealing how power concentration, turnout behaviour, and mechanism design jointly influence decentralization and efficiency in DAO voting. The third part presents a unifying conceptual framework to analyse consensus across human, machine, and human-machine hybrid systems. Despite disciplinary differences, the thesis identifies three core components of any consensus process: participants (the actors of agreement), communication (the medium of exchange), and state (the evolving representation of agreement). Framing consensus as an entropy-reduction process that resolves cognitive or informational divergence, this abstraction enables comparative analysis across diverse systems. The framework also distinguishes among human consensus, machine consensus, and human-machine hybrid consensus, and offers design guidelines aligned with the characteristics and limitations of each. Together, these three threads construct a comprehensive theory of consensus that connects distributed computation, social governance, and emerging hybrid collectives. By integrating modelling, evaluation, and abstraction, this thesis contributes a multi-layered foundation for understanding and designing consensus mechanisms that are robust, scalable, and trustworthy in increasingly decentralized and intelligent environments.
This thesis examines tactical lessons learned from recent military operations other than war (MOOTW) for implications on leadership development for junior leaders in the United States Marine Corps. A doctrinal examination of MOOTW provides the context for the study. The research questions focus on unique leadership capabilities and competencies necessary for junior Marine Corps leaders in the MOOTW environment. The research involved analysis of recent tactical experiential lessons. These tactical lessons learned, coupled with the doctrinal examination, result in MOOTW specific junior leader competencies necessary for MOOTW organizational effectiveness. The results synthesize into three key competency areas: (1) ability to adapt leadership roles to diverse environments, (2) independent decision-making skills for decentralized operations, and (3) ability to develop leadership skills in team members. Theoretical leadership development frameworks are reviewed for insight into improving these junior leader competencies in the Marine Corps. Recommendations include focusing MOOTW training on the characteristics of: (1) highly politicized environment at all levels of command, (2) high ambiguity between combatants and non-combatants, (3) decision-making at the lowest tactical levels in a decentralized environment, (4) development of teams to operate autonomously in this decentralized environment, and (5) reinforcement that tactical decisions by junior leaders have operational and even strategic impact.