As the world gears up for the 2026 Nuclear Non-Proliferation Treaty (NPT) Review Conference, a new and multifaceted factor is complicating the global strategic calculus: Artificial Intelligence (AI). The “nuclear-AI nexus” has evolved from a niche technical interest to a prominent feature in global security discussions, with implications for every aspect of the NPT’s three pillars: non-proliferation, disarmament, and peaceful uses of nuclear energy. However, as experts recently cautioned at the “Atoms for Algorithms” webinar, we need to cut through the speculative “AI hype” to ensure this technology remains a means for peace, not an avenue for unintentional escalation.

To regulate the nuclear-AI connection, we first need to understand the technology. As a United Nations Institute for Disarmament Research researcher, Dr. Yasmina Fina suggests, AI is not a monolithic entity, but a “construct” and a “system of systems,” made up of code, software, data, hardware, and sensors. It is a system used to fulfill certain functions, not a threat capable of usurping human decision-making. The risk is the “speed and scale” of AI, which can have myriad implications for performance and strategy. Moreover, Fina warns that comparing nuclear governance to AI governance is unhelpful because the technologies are not the same; nuclear materials are limited and tangible, whereas AI is ubiquitous and digital.

In the context of non-proliferation, AI is touted as a game-changing verification tool. The International Atomic Energy Agency (IAEA) could potentially use “AI agents,” semi-autonomous machines capable of processing large data streams and satellite images to verify the accuracy of declarations by states at a pace humans cannot match. However, Dr. Ian Stewart, Executive Director of the CNS Washington, states that AI will not help states develop nuclear weapons they could not otherwise build, for two physical reasons: AI cannot “magic up” fissile material, and there is no evidence that large language models can transfer the “tacit knowledge” necessary for weaponization.

When it comes to AI and nuclear weapons, political concerns are high. States have been reluctant to allow the IAEA to use open-source data or “black box” algorithms. Should an AI detect an event, the absence of “explainability” or how the machine arrived at its decision could lead to a crisis of political legitimacy for the safeguards system.

The most fraught part of the nexus is disarmament. We are now seeing a “race to adopt” AI in military strategies due to the perceived speed advantage it offers. AI can speed up threat identification and data integration, potentially freeing up more time for decision-making (or, on the other hand, reducing decision-making cycles to the point that humans are simply rubber-stamping decisions).

Aliche Sultini, senior research lead at the Rhode Island School of Design, explains that AI systems create new levels of uncertainty. If a state cannot grasp how an adversary’s AI operates in its decision-making, it might fall into worst-case scenarios, reinforcing alert postures that prevent disarmament. To support disarmament, AI must be used to enhance technical verification and confidence, not to shorten the path to war. Possibly the most disruptive aspect of this interaction is the NPT’s third pillar: peaceful nuclear energy applications. According to Mr. Shota Kamishima of the IAEA, an “affinity” is emerging between nuclear power and AI. We are now moving into a world where energy-hungry AI data centers need the clean, scalable, and reliable power offered by nuclear power, and where nuclear generation and maintenance are improved through AI.

This alliance is especially important for the rollout of Small Modular Reactors (SMRs), for which AI-optimized construction schedules and supply chains are critical. By enhancing predictability and avoiding cost overruns, a major issue for nuclear construction, AI could make nuclear projects more “bankable” and thus more attractive for the global shift towards clean energy. Despite technological progress, the experts agree: human responsibility is essential. Whether it is a safeguards inspector at the International Atomic Energy Agency (IAEA) or a human commander in a nuclear-armed nation, humans are the “last line of defence”.

“Black box” systems are incompatible with a strong safety culture. Governance policies must ensure that AI is implemented with transparency, traceability, and “explainability”. We must also be alert to the potential for AI to be employed by “agents” to monitor sites, which could result in disinformation and the distortion of threat perception through “anomaly detections.” As the 2026 Review Conference draws near, policymakers’ mission should be to “denoise.” Nuclear policy decisions must not be based on science fiction or fear of competition. Rather, we should prioritize “lower stakes” opportunities where AI can help us now, such as employing AI agents to navigate the overwhelming output of the NPT process — making it searchable and highlighting inconsistencies in delegation positions.

The relationship between nuclear and AI is not a bug to be fixed with more software, but a circumstance to be managed by the international community. By prioritizing evidence-based policy and law, human-in-the-loop systems, and the common ground of the peaceful “Atoms for Algorithms” alliance, we can ensure that the digital revolution supports, rather than undermines, the global nuclear order. In the end, the fate of the NPT will not be determined by algorithms, but by human intelligence.

Muhammad Shahzad Akram is a Research Officer at the Centre for International Strategic Studies, AJK. He holds an MPhil in International Relations from Quaid-i-Azam University, Islamabad. He is an alumnus of the Near East South Asia (NESA) Centre for Strategic Studies, National Defence University (NDU), and Washington, DC. His expertise includes cyber warfare and strategy, arms control, and disarmament. Views expressed in this article are the author’s own. 

Navigating the AI and Nuclear Nexus was originally published on Global Security Review.

The amalgamation of emerging technologies and nuclear weapons systems is significantly impacting the landscape of strategic stability. The primary problem associated with such technologies is their dual-use nature, such as Artificial Intelligence (AI), hyper sonics, quantum computing, and cyber warfare. These technologies are evolving more rapidly than the treaties meant to regulate them.

The most significant emerging technology is Artificial Intelligence (AI), a prominent dual-use disruptor. In the civilian domain, it can help process large amounts of data based on its training. Meanwhile, in the nuclear domain, it affects among other things, the nuclear decision making process.

The U.S. is currently considering incorporating AI into its NC3 modernization process while maintaining a human-in-the-loop policy for launches, using AI to monitor abnormal patterns in adversary movements. Russia, on the other hand, is developing AI-driven upgrades to its automated retaliatory strike system to ensure that if the country’s leadership is decapitated, the system can autonomously verify a nuclear strike via seismic and radiation sensors before launching a retaliatory strike. These change decision timing and the deterrence dynamic.

The incorporation of hypersonic technology into delivery vehicles has revolutionized the exchange of weapons in warfare. The speed at which hypersonic systems travel can exceed Mach 5 (five times the speed of sound), potentially inducing miscalculation for an adversary, since it compresses the time window to clearly assess whether a missile is conventional or nuclear. In late 2024 and early 2025, India tested its Hypersonic Glide Vehicle (HGV) technology. Since these vehicles travel at such high speeds and at low altitudes with the ability to maneuver, it impacts the deterrence strategy between two nuclear countries. In response, Pakistan accelerated the Fatah series missiles, which are designed as flat-trajectory rockets. The geographical proximity of India and Pakistan compresses the decision-making window during a crisis.

The world’s largest naval force, the U.S. navy, is currently integrating the Conventional Prompt Strike (CPS) hypersonic system onto Zumwalt-class destroyers. A Zumwalt-class ship may appear as a nuclear threat on radar but carries conventional weapons, risking warhead ambiguity for an adversary who might launch a nuclear strike if provoked. The recent exchange of delivery vehicles during the Iran and Israel conflict of 2024-2025 has shown the effect of hypersonic missiles in military operations. Iran used the Fattah-2 hypersonic missile, capable of Mach 5+ speeds with mid-flight maneuverability. Such weapon-delivery systems create strategic ambiguity for the adversary because they provide only a few seconds’ window to decide whether to retaliate with conventional or nuclear missiles.

Advancements in quantum computing change warfare by providing more powerful algorithms producing vulnerabilities in secure systems. Nuclear launch codes, for example, are considered among the most secure encryption systems, which cannot be broken by classical computer methods. However, with advanced quantum computing methods, they become more vulnerable to hacking.

Additionally, Quantum sensing, which is facilitated with quantum electronic systems, allow for detection of minute changes in gravity or magnetic fields, which could produce systems that detect submarines, reducing their element of surprise. For example, China has made a huge leap by developing Quantum SQUID (Superconducting Quantum Interference Device) sensors. These devices may be able to detect the magnetic signature of US Ohio-class stealth submarines from miles away, threatening the ultimate nuclear deterrent.

Cyber warfare has recently moved to the forefront of modern warfare tactics with potential impacts on nuclear deterrence. Cyber warfare may produce uncertainties due to disruption of detection mechanisms and nuclear command and control that could produce unstable strategic situations. The classic Cold War model of Mutually Assured Destruction (MAD) was based on the visible, slow-moving, threat of nuclear weapons exchange. Cyber warfare introduces complexity and confusion. Thus, the deliberate nature of threats; instead, may instigate miscalculations driven by algorithms or false cyber signals.

A good example of how cyber operations can offset traditional military operations was the venture to physically damage Iranian nuclear centrifuges using malicious software (malware). The operation was carried out using Stuxnet malware installed from a USB drive that destroyed centrifuges without a single kinetic device. Similarly, Russian hackers have been carrying out cyber-attacks against Ukrainian energy infrastructure and government agencies since 2015. Vis-à-vis in 2025, during the ongoing Russia-Ukraine war, Ukrainian intelligence conducted a cyber-operation shutting down the Russian railway and affecting digital infrastructure.

A major problem lies with warhead ambiguity (conventional vs. nuclear), which poses a huge risk for accidental nuclear escalation. During the height of the May 2025 crisis between the two South Asian rivals, cyber operations were at their peak. Consequently, in the post-crisis scenario, India is enhancing its cyber deterrence. In future conflicts, any state’s cyber space will be one of the primary targets; in a scenario where lines are already blurred, a single attempt to disrupt the cyber space of NC3 could be the initiating point of nuclear escalation.

The evolution of dual-use emerging technologies is fundamentally changing the traditional pillars of nuclear deterrence by compressing the action/reaction time required for rational decision-making. A major problem lies with warhead ambiguity (conventional vs. nuclear), which poses a huge risk for accidental nuclear escalation. In the volatile context of South Asia, dual-use technologies appear to destabilize a fragile strategic stability.

Ultimately, as machines outpace human thought in the decision loop, there is a danger that the resulting disruption is not just a technological arms race but the erosion of human-centric control, creating the risk of an accidental, algorithmically driven nuclear escalation as the defining strategic challenge of the future.

Muhammad Usama Khalid is a Research Officer at the Balochistan Think Tank Network (BTTN), BUITEMS, Quetta. He can be reached at: usama.khalid.uk456@gmail.com. The views of the author are his own.

Nuclear Deterrence in the Age of Emerging Technologies was originally published on Global Security Review.

Technological advances and rising military expenditures in recent years have accelerated the development of Lethal Autonomous Weapon Systems (LAWS). Though this technology is still in its infancy, it has already transformed modern warfare. LAWS, when fully evolved, will provide means for precise and independent selection and engagement of targets without exposing soldiers to battlefield dangers. A 2025 Congressional Research Service report titled Defense Primer: U.S. Policy on LAWS classifies it as “a special class of weapon systems that use sensor suites and computer algorithms to independently identify, target and employ an onboard weapon system to engage and destroy it without manual human control.” The US Department of Defense Directive 3000.09, Autonomy in Weapon Systems (2023), defined LAWS as systems that, once activated, “can select and engage targets without further intervention by a human operator.” This concept, known as “human out of the loop” or “full autonomy,” involves target selection and engagement based on inputs from artificial intelligence (AI), big data analytics, and sensor-based identification. 

According to Data M Intelligence, the global autonomous weapons market reached USD 14.2 billion in 2024 and is expected to grow to USD 33.47 billion by 2032, with a compound annual growth rate of 11.39 percent during 2025-2032. Simultaneously, global civil society initiatives are advocating a ban on fully autonomous systems. In October 2012, Amnesty International launched the Stop Killer Robots campaign, an alliance of over 180 organizations across 65 countries, calling for an international law on autonomy in weapon systems to ensure machines are not allowed to make decisions that affect life and death. 

Concerns have arisen over unsupervised use and the potential for system errors that can cause unintended civilian casualties, escalate conflicts, and threaten global peace and security. The increasing integration of autonomous weapon systems in combat has already been highlighted by their reported use in Ukraine conflict and in Gaza. A February 2025 report by the Foundation for Political, Economic and Social Research titled Deadly Algorithms: Destructive Role of Artificial Intelligence in Gaza War revealed that Israel employed AI-based systems, Lavender and Habsora, to identify and attack human targets. The report states that Lavender can approve targets within 20 seconds, often without substantive human review. Since October 2023, the system has compiled a list of 37,000 potential individuals labelled as Hamas members without verifying their military profile.  

Since 2014, the United Nations Convention on Certain Conventional Weapons (UN CCW) has debated the regulation of LAWS. In May 2024, Arms Campaign Director Steve Goose of Human Rights Watch warned that “the world is approaching a tipping point for acting on concerns over autonomous weapons systems,” underscoring the urgency of an international legal instrument. On 2 December 2024, the UN General Assembly adopted Resolution A/RES/79/62 on LAWS by 166 votes in favor, 3 against, and 15 abstentions. The resolution marked a decisive step in acknowledging global concerns over autonomous weapon systems, affirmed the applicability of international humanitarian law (IHL) and called for further consultations in 2025. The first UNGA meeting on autonomous weapons, held on 12-13 May 2025 and attended by 96 countries, including representatives from the International Committee of the Red Cross (ICRC) and civil society, reinforced momentum to prohibit and regulate LAWS. On that occasion, UN Secretary-General António Guterres advocated for a legally binding instrument to ban LAWS by 2026, describing them as “politically unacceptable and morally repugnant.”  

Despite global concerns, progress on a legally binding treaty on LAWS remains elusive due to divergent strategic interests of major powers. The US continues to resist codification of a new binding framework, emphasizing the adequacy of national weapons review mechanisms to preserve strategic and technological flexibility. While the US maintains that it does not currently possess LAWS, senior military leaders have acknowledged that Washington may be compelled to develop them if adversaries do so. Russia has opposed any binding treaty, while China supports negotiations on the CCW and the development of norms “when conditions are ripe.” The European Union, in contrast, advocates for a legally binding international instrument, emphasizing Meaningful Human Control (MHC) and compliance with IHL. The EU’s approach seeks to differentiate between systems that incorporate human oversight and those that operate without it. 

The integration of artificial intelligence into weapon systems also presents an increasing challenge to nuclear deterrence and strategic stability. For instance, during the sidelines of the Asia-Pacific Economic Cooperation (APEC) Summit in Peru in November 2024, the then US President Joe Biden and China’s President Xi Jinping jointly pledged not to integrate AI in nuclear command-and-control systems, recognizing the catastrophic risks of automation in nuclear decision-making. However, as AI rapidly improves surveillance, missile guidance and targeting systems, it is unclear whether this restraint will hold.  

The integration of AI in nuclear forces may introduce instability into deterrence dynamics by reducing decision-making time and increasing challenges caused by algorithmic bias in early warning systems, posing the threat of false nuclear alarms. Cold War history reminds us of human judgment, central to nuclear stability, and averted catastrophes. During the Cuban Missile Crisis, the B-59 submarine incident on 27 October 1962 brought the two superpowers close to nuclear exchange when a Soviet submarine commander considered launching a nuclear-tipped torpedo under the mistaken belief that hostilities had commenced. The refusal by Vasily Arkhipov to authorize the attack prevented a potential nuclear war. Similarly, Stanislav Yevgrafovich Petrov, a lieutenant colonel in the Soviet Air Defense Forces, chose to disregard a false early-warning alert indicating an incoming US nuclear strike in 1983, preventing a global nuclear disaster. Such decision-making underscores the indispensable role of human rationality in nuclear command-and-control systems.  

As LAWS presents multifaceted threats to international peace and security, states need to consider negotiating a legally binding instrument that ensures MHC over autonomy in weapon systems. Enhancing transparency, accountability, and rigorous weapons reviews are essential to prevent destabilization and ensure that technological progress does not outpace the human element in the use of force. Confidence-building measures, such as transparency in military AI, the establishment of international verification mechanisms and a moratorium on the development and deployment of LAWS, could help mitigate future dangers. 

Jawad Ali Shah is a Research Officer at the Center for International Strategic Studies Sindh (CISSS), Pakistan. He holds a BS in International Relations from the University of Sindh, Jamshoro, Pakistan. His research areas are emerging military technologies, and South Asian nuclear deterrence and strategic stability dynamics. The views are the author’s own. 

Lethal Autonomous Weapon Systems: A New Battlefield Reality was originally published on Global Security Review.

AI has improved intelligence operations in developing nations, but it has also created a new intelligence gap due to disjointed technological implementation, political exploitation of surveillance, reliance on foreign suppliers, and insufficient integration between HUMINT and AI-driven systems. Pakistan and India have large human resources and developing technological ecosystems, but institutional fragmentation and political agendas prevent the development of integrated, modern intelligence frameworks.

The problems that South Asian intelligence services are having are part of a larger global transformation. AI is now a segment of intelligence operation in the US, China, Israel, and some European countries. This includes automated translation, pattern-of-life analysis, algorithmic triage of intercepted data, commercial satellite imagery analytics, and cyber-enabled anomaly detection. China’s surveillance state uses AI-powered facial recognition, behavior prediction, and nationwide data fusion to show what a fully integrated intelligence model looks like. The U.S. is pushing for automated signals intelligence (SIGINT) processing and predictive analysis in all its intelligence agencies in the Office of the Director of National Intelligence (ODNI). As shown in studies of its military AI systems, Israel uses AI in real-time targeting and ISR fusion.

Developing countries are just as vulnerable to cyber-attacks, terrorism, and false information, but they do not have the institutional frameworks that let AI grow. This global gap is what makes the changes in intelligence in Pakistan and India so important for strategy. Pakistan and India have both spent resources on AI-enabled surveillance systems like ID databases, CCTV networks, predictive policing tools, interception systems, and cyber technologies that come from other countries. The NADRA database and Safe City projects in Pakistan give a lot of biometric and real-time data. India has made the Central Monitoring System (CMS) and the National Intelligence Grid (NATGRID) to connect databases between state agencies. The ministry, military, police, and intelligence systems are separate. Legacy bureaucracies promote compartmentalization over integration. AI needs centralized databases, clean data, agency cooperation, and agreed analysis criteria. These requirements are missing; hence, AI systems exhibit limited and inconsistent intelligence. Agencies are collecting more data than ever but lack the framework to analyze it.

Pakistan and India still value HUMINT for intelligence. It is crucial for counterterrorism, political spying, and regional operations. HUMINT alone can’t compete with hybrid enemies who use AI-driven processing. Strategically, China’s integrated military and civilian AI ecosystem is advantageous. Developing states are stuck between two sources of intelligence: First is a legacy HUMINT system with deep networks and second is an AI ecosystem that is fragmented and not fully developed, so it cannot support strategic analysis. In cross-border threat assessments, cyber invasions, and emerging non-traditional security issues like information warfare, this mismatch causes delays, blind spots, and analytical distortions.

In both Pakistan and India, AI-enabled surveillance has been used more for political purposes than for improving strategic intelligence. Amnesty International reported that India’s use of Pegasus spyware targeted journalists, activists, and political opponents. Pakistan has been criticized for using automated social media monitoring and political profiling, which often focuses on threats from within the country rather than threats from other countries. When surveillance tools are used to control political competition within a party, two things happen. First, institutional resources prioritize domestic control over strategic analysis. Second, technology investments strengthen policing instead of updating intelligence. This challenges national security by making it harder for the intelligence system to predict cyberattacks, regional crises, and threats from outside the country.

South Asia has a lot of foreign AI and cyber infrastructure. Pakistan employs Chinese surveillance equipment (Hikvision, Huawei), while India uses Israeli, US, and European and American forensics platforms. This increases structural risks, including data exfiltration and espionage due to entrenched vulnerabilities, strategic reliance on foreign updates, and weakened sovereignty over vital intelligence activities.

Two traditional rivals, nuclear-weapon states, are weakened by this reliance. AI-powered surveillance systems increase digital access points for assault. Big national data repositories attract attackers. Pakistan has had multiple government system hacks, and India has had large breaches that compromised critical infrastructure and government information.  Failures in the past were largely caused by human error, but in the AI era, bias in algorithms, data manipulation, hostile and automated cyberattacks, and misclassification can lead to erroneous operational decisions. These dangers make the strategy unstable.

Increasing intelligence gaps between Pakistan and India jeopardize national and regional security. More likely to misjudge opponents: In fast-moving crises, agencies may miss signals, misjudge threats, or misread trends without AI–HUMINT fusion. Cross-border escalation risks rise; poor intelligence integration in nuclearized environments may aggravate misperceptions during crises like the 2019 Pulwama–Balakot incident or the May 2025 standoff. Cyber attacks expose national secrets. Easy-to-get digital network intelligence can have fatal repercussions. China-asymmetric strategic competition: China is decades ahead in intelligence upgrading, and Pakistan and India may fall further. Domestic AI reduces institutional capacity: political survival trumps strategic intelligence.

In summary, countries that do not update their intelligence risk being caught off guard, making mistakes, and becoming more vulnerable. The myths of shadows, secrecy, and huge people networks that fueled emerging country intelligence organizations are gone. AI has highlighted bureaucratic opacity’s long-hidden structural flaws: dysfunctional systems, politicized surveillance, reliance on foreign technology, and a lack of HUMINT-AI integration. Thus, Pakistan and India’s new intelligence divide is not about data or resources. It is about institutions’ failure to transition from analogue intelligence to AI-connected ecosystems. State and non-state adversaries that accelerate this transformation will benefit.

In nuclearized, crisis-prone South Asia, small misunderstandings could lead to massive wars. Pakistan and India need more than AI tools to stay competitive strategically. They need data architectures that work together, technical specialists, protocols to prevent politicians from abusing their authority, and strategic AI–HUMINT fusion.

Dr. Tahir Mahmood Azad is currently a research scholar at the Department of Politics & International Relations, the University of Reading, UK.  Views expressed in this article are the author’s own. 

The Intelligence Illusion: How AI is Exposing Strategic Vulnerabilities in the Developing World was originally published on Global Security Review.

Meanwhile, the US Department of Defense (DoD) appears to be doing the opposite. The Chief Digital and Artificial Intelligence Office (CDAO) recently axed its Chief Technology Officer (CTO) directorate, a move many analysts view as strategic self-sabotage.

This directorate, responsible for overseeing more than $340 million in AI and digital integrations in fiscal year 2024, represented a critical nexus linking battlefield innovations with institutional infrastructure. Its elimination, justified under “efficiency” mandates, alarmed defense observers who fear it fractures continuity, erases institutional memory, and sends a dangerous signal to adversaries willing to exploit perceived American weakness.

The Strategic Misstep

The CDAO was formed in 2022 by fusing key functions from the Joint Artificial Intelligence Center, Defense Digital Service, Chief Data Office, and Advana analytics, aiming to unify policy, technology, and digital services. Embedded within CDAO, the CTO led cross-functional teams in AI, cyber, logistics, and command-and-control systems, ensuring that new technologies remained interoperable and aligned with warfighter requirements.

Abruptly dismantling this directorate not only removes a pivotal vision and coordination role but also creates a void with no clear replacement. The result is fragmented efforts, lost synergy across mission areas, and a battlefield advantage handed to adversaries.

Expertise Lost, Momentum Undermined

Leadership and expertise take years, even decades, to develop. Figures like Bill Streilein, former CTO of CDAO and veteran of MIT Lincoln Laboratory, carried institutional memory and high standards into Pentagon AI programs. But when top-tier professionals are sidelined under the label of “streamlining,” they often leave and seldom return.

This pattern has already occurred. The Defense Digital Service (DDS), once lauded as the Pentagon’s “SWAT team of nerds,” lost almost all of its members by May 2025, prompting its demise. Nearly every DDS member, citing bureaucratic pressure from the Department of Government Efficiency (DOGE), chose to depart rather than conform.

These departures are not benign transfers. They represent the scattering of core innovators and connectors whose insight and trust networks are irreplaceable. Without them, emerging AI systems risk becoming siloed projects rather than battlefield-enabling capabilities.

DOGE: Efficiency or Engineered Evisceration?

DOGE, instituted by a presidential executive order in January 2025, is authorized to slash perceived inefficiencies across federal agencies—often through AI-enhanced, automated assessments. Under the leadership of figures tied to Elon Musk and Vivek Ramaswamy, DOGE has repurposed its mandate to aggressively target leadership and innovation roles across the board—including in national defense.

DOGE has justified cuts using its proprietary AI systems to flag and eliminate “inefficient” programs, often without human oversight or contextual nuance. The CTO’s directorate was among its most high-profile targets, methodically identified and removed, despite its mission-critical nature.

To make matters worse, DOGE is reportedly comfortable with these decisions. One Pentagon official described it as a “theater of dominance,” not just cost-cutting, but deliberate erasure of institutional anchors to obfuscate the depth and breadth of the sacrifice.

The High-Stakes Fallout

Adversaries feast on the narrative that the US champions AI yet purges its own tech leadership overnight. “America cannibalizes its talent while claiming leadership in AI warfare,” such narratives go. These optics weaken American deterrence, erode allied confidence, and provide cover for Moscow, Beijing, and Pyongyang to reframe the battlefield narrative.

Domestic consequences are equally grim. The consistent removal of flagship tech roles projects a clear message to science, technology, engineering, and math (STEM) professionals; serve, and risk being discarded. That weakness is a recruitment boon for adversaries, national lab contractors, and tech-armed autocracies solving tomorrow’s warfare puzzles.

Real efficiencies lie not in gutting leadership but in fortifying it. Per the National Security Commission on AI, prioritizing disciplined recruitment and retention of technical talent, including a Digital Corps and AI fellowships, is key to American competitiveness. Instead, we witness the dismantling of precisely those anchor roles meant to shepherd AI innovation into combat-relevant systems.

The DOGE-Driven Dismantling of Tech Leadership

The concepts herein are alarming and reflect an institutional unraveling that directly undermines America’s global security posture and strategic deterrence in five critical ways. First, the elimination of the Chief Technology Officer (CTO) directorate from the Chief Digital and Artificial Intelligence Office (CDAO) strips away a core pillar of the Pentagon’s ability to adapt emerging technologies for battlefield advantage. This directorate was not redundant bureaucracy; it was the crucible in which ideas from national labs, industry, and warfighters were harmonized into operational capability.

By abruptly dismantling this team, the Department of Defense has extinguished a pipeline of institutional memory and strategic insight at the precise moment when rapid, informed, and integrated decision-making is needed. This brain drain parallels a historical pattern of self-sabotage and leaves adversaries uncontested in the tech talent race.

Second, the removal of high-level AI leadership is a propaganda gift to revisionist powers like China and Russia. These states are watching America voluntarily decapitate its own strategic leadership, an act they can now frame as proof of American decline. This strengthens their strategic messaging in influence campaigns aimed at allies, neutral states, and even American citizens.

“America cannibalizes its talent while claiming leadership in AI warfare” is not just a phrase, it is a weaponized narrative that demoralizes partners and emboldens adversaries to challenge American dominance in contested domains like cyberspace, space, and AI warfare.

Third, strategic deterrence hinges on credible capability and the perception of cohesion. DOGE’s algorithmic-driven targeting of leadership roles without contextual assessment introduces chaos into the acquisition and integration life cycle of military AI systems. Instead of creating synergistic effects across logistics, cyber, and command and control, the US risks building a fractured, siloed ecosystem that fails in joint operations.

By removing the very leaders who prevent stove piping, the US sabotages its ability to develop and field interoperable, scalable, and warfighter-ready AI tools. This systemic breakdown makes deterrence brittle, vulnerable to being cracked in future high-end conflicts.

Fourth, the US has struggled to compete with the private sector for AI and cybersecurity talent. By signaling that even elite government technologists are disposable under the guise of “efficiency,” this policy drives future talent away from public service. Those who might have joined a modern “Digital Corps” will instead seek stability and respect elsewhere, perhaps even abroad.

Strategic deterrence depends not only on weapons but on technologists who know how to deploy them. Gutting these roles ensures that tomorrow’s innovations will not make it past the lab, let alone onto the battlefield.

Fifth, DOGE’s use of automated assessments to eliminate “inefficiencies” without human oversight is a grotesque parody of reform. Its reliance on cold, context-blind algorithms to purge critical roles mimics adversary models of techno-authoritarianism, not democratic accountability. If allowed to continue, this will hollow out innovation across government agencies and military branches.

Efficiency is not the enemy, misapplied efficiency is. Strategic deterrence requires smart investments, not cost-cutting theater that sacrifices our warfighting edge on the altar of political optics.

Strategic Self-Sabotage Must Be Reversed

This is not merely streamlining, it is full-blown surrender. The dismantling of the CDAO’s CTO directorate and the broader DOGE initiative represents an engineered unraveling of the very leadership needed to project U.S. strategic deterrence in the AI era. Leadership is the vector through which technology becomes capability. Remove it, and you hand your adversaries not only the advantage, but the narrative.

Unless reversed, these concepts and actions will echo through wargames, deterrence failures, and battlefield losses. The US must stop cannibalizing its competitive edge and re-center its national security strategy on strengthening, not sidelining, its AI leadership.

Conclusion

Leadership is not just overhead on the funding spreadsheet; these leaders are our ammunition in the fight for global AI dominance. Removing them during a strategic inflection point is not reform, it is a self-made vulnerability, and as the US disables its own leadership of advanced technologies, it is dismantling future readiness.

The nation must insist on accountability. Cost-cutting means nothing if it costs the technological coherence to compete in tomorrow’s battles. In the strategic competition unfolding now, leadership is the weapon, and ceding it is surrender. This page out of the DOGE handbook should be shredded and burned. Remember, Iranian nuclear scientists were not dismantled by their own regime, they were destroyed by US and Israeli bombs.

Greg Sharpe is Marketing Director at the National Institute for Deterrence Studies. He is retired from the US Air Force. The views expressed are his own.

The Quiet Dismantling of America’s AI Warfighting Edge was originally published on Global Security Review.

5GW includes information dominance and manipulation, social engineering, economic coercion, cyber sabotage, and hybrid influence operations. It thrives on ambiguity, exploiting vulnerabilities without traditional combat. In 5GW, the lines between war and peace are blurred. No declarations, no clear enemies, just a relentless assault on stability. The goal is not to conquer land or destroy armies, but to cripple a nation’s spirit, economy, and infrastructure from within.

One of the most potent asymmetric tools of 5GW is economic manipulation. Palau, a serene archipelago of over 500 islands, were untouched by war until 2017. Palau dared to reject Beijing’s “One China Policy.” This move sent shockwaves through its fragile economy in the form of economic strangulation. In a masterstroke of economic coercion, China’s state-backed tour operators erased Palau from the Web.

Travel agencies stopped selling trips. Online searches yielded no results. Palau’s tourism industry, which accounted for 45 percent of gross domestic product (GDP), collapsed. Hotels emptied, airlines shut down, and the once-thriving economy suffocated.

This was not an anomaly, but a pattern. In 2016, South Korea agreed to facilitate the American THAAD missile defense system. China retaliated not with weapons but with economic muscle. Mysterious “fire and safety” violations suddenly appeared in South Korean businesses across China. A nine-month ban on Chinese tourism cost Seoul $6.5 billion. Retail giants like Lotte crumbled, thousands lost jobs, and yet, no war was declared.

The more interconnected the world economy becomes, the more vulnerable nations are to economic blackmail. Even Venezuela, despite its fiery anti-American rhetoric, was bound to the US economy. In 2018, despite Washington branding Nicolás Maduro a dictator and Caracas calling the US a “white supremacist regime,” the two nations still had $24 billion in trade, a quarter of Venezuela’s GDP.

Yet, when Washington imposed sweeping financial sanctions, Venezuela’s economy shrunk by 35 percent in a single year. After all, the United States does not just impose sanctions; it controls the very financial system that runs the world. The US dollar is the bloodline of global trade, and those who defy it find themselves cut off from international markets, unable to access capital or even conduct basic transactions. However, economic warfare breeds resistance.

Russia and China saw the writing on the wall. Between 2017 and 2020, Moscow slashed its holdings of US Treasury securities from $105 billion to just $3.8 billion and shifted towards China’s Cross-Border Interbank Payment System (CIPS), sidestepping American financial hegemony.

The true commanding heights of global dominance lie at the intersection of technology, finance, and unchecked ambition. China is not just selling 5G networks, it is embedding itself into the nervous system of global communication. On the other hand, the US does not just dominate finance, it controls the SWIFT banking system, ensuring economic warfare is just a sanction away. Similarly, corporations do not just innovate, they monopolize, influence, and quietly dictate policy behind closed doors.

“Surge forward, killing as you go, to blaze us a trail of blood.” A battle cry? Indeed. Not from a general on the battlefield, but from Ren Zhengfei, the founder of Huawei, a company waging a war not just against competitors but against entire nations. Britain’s telecom networks are suspected to have Chinese backdoors.

Information is now what oil was in the 1970s, a critical commodity to be controlled. Today, data is the new crude, and the battle to monopolize its flow has already begun. Quantum computing, AI, and machine learning are the new oil rigs, and the nations that dominate these technologies will dictate the future. Unlike oil, information is easily stolen, manipulated, or even weaponized in ways no physical resource ever could.

The first lethal autonomous drone strike in Libya, recorded in March 2020, was a grim reminder of what is to come. A suicide drone, powered by AI, needed no human command—just a target. Fire and forget was the name of the game. Imagine the next phase: terrorist organizations deploying AI-powered swarms, able to strike with precision, invulnerability, and zero risk to human operatives. They would not negotiate, would not retreat, and would prove hard to stop.  

In a world where biological warfare is outlawed, the selective control of food, aid, and healthcare has replaced mass destruction with slow, calculated suffocation. Nations can now deny access to the very essentials of life to break their adversaries in a siege without walls and a war without battlefields. Over 40 percent of the world’s population faces water scarcity, and by 2030, drought could displace 700 million people. The Turkish-backed militias that had control over the Alouk water station in Syria in 2020 was a stark reminder—when resources are weaponized, suffering becomes policy.

Interestingly, the battle of perception is gaining momentum more than ever. In an era of clickbait headlines and disinformation campaigns, lies travel faster than truth. The Massachusetts Institute of Technology found that false news spreads 70 percent faster than real news. From the Soviet KGB planting the rumor in the 1980s that the US government created AIDS to modern deepfake propaganda, deception is the new artillery.

Even culture is not immune. Hollywood exported American ideals, Bollywood spread Indian influence, and K-pop turned South Korea into a global powerhouse. For instance, the Cold War was not just won by missiles, it was won when a West German band sang “Wind of Change,” which then became the anthem of the Berlin Wall’s collapse.

If hunger, water, and financial systems hare already weaponized, the next battlefield is clear—space and the seabed. Subsea communication cables are responsible for carrying 97 percent of global data traffic and are the arteries of the modern economy. They enable over $10 trillion in financial transactions every single day. Yet, these vital lifelines remain shockingly unprotected and are vulnerable to sabotage, espionage, and strategic disruption. A targeted attack on just a handful of these cables could cripple stock markets, paralyze banking systems, and sever military command structures—all without a single warship being deployed.

Meanwhile, the race for space dominance is accelerating. From $63.66 billion in 2024 to an estimated $74.4 billion by 2028, the global military satellite market is growing, fueled by the realization that power no longer lies in boots on the ground, but in eyes in the sky. Satellites provide precision-strike capabilities, secure communication, and real-time battlefield intelligence. The Pentagon warns that the US is already vulnerable, with China and Russia developing anti-satellite (ASAT) weapons.

In this realm, one can say that modern states wage wars without battlefields, where the goal is not to destroy but to subdue—crippling economies, infiltrating cyber networks, and manipulating narratives without a single shot fired. What is never openly begun is rarely officially ended. In 5th-generation warfare, silence is a weapon, perception is the battlefield, and survival means accepting that war never truly ends.

Syeda Fizzah Shuja is a Research Associate at Pakistan Navy War College and an Mphil scholar in Peace and Counter Terrorism. Her work focuses on hybrid warfare and maritime terrorism. She can be contacted at fizzasyed2k@gmail.com.

The 5GW Playbook: Silent Wars and Invisible Battlefields was originally published on Global Security Review.

Focusing on information operations is critical. Drones, for example, use artificial intelligence capabilities, as do defensive systems. However, conflict between near-peer adversaries and competitors is still unlikely as gray zone and hybrid conflict are the dominant avenues for competition. With the information environment transcending all domains of warfare, artificial intelligence capabilities become the go-to capability to ensure and maintain information advantage.

China’s AI-enhanced information operations are becoming increasingly sophisticated. For example, the Chinese advanced persistent threat actor Spamouflage Dragon uses generative AI to create online personas to influence public opinion. China and its proxy companies seek to develop or compete for AI supremacy within the information environment.

Of course, China will use anything within its arsenal to shape strategic, operational, and tactical levels of war to its advantage, expand its influence, and create an ecosystem that is dependent on its technologies. For example, Baidu, known as the “Google of China,” invested billions into AI capabilities, creating the proprietary ERNIE model, which has been trained on billions of parameters, increasing the output’s quality and complexity.

However, China is also leveraging open-source AI models to shape the information environment. With the recent release of open-source large language models such as DeepSeek and Qwen, Chinese-linked subsidiaries, High-Flyer and Alibaba Group created a way to expand their influence, revise history, and likely create a dependent ecosystem for target countries. Unlike the much more expensive ChatGPT, for which the more basic model is free, China’s investment in generative AI models is free for the public and even surpasses ChatGPT’s in some respects.

There is a debate about how China’s proxy state companies were able to create these advanced models without US-based critical components. China allegedly did not have access to the advanced critical Nvidia chips for which most AI models are dependent. China seems to have created generative models just as suitable or even better than that of ChatGPT, but allegedly at a fraction of the cost and free of charge to the public. The US limited Nvidia chip exports to China, a market predicted to top $1 trillion in revenue within a decade. Still, the accusation is that the Chinese subsidiary leased or bought the more advanced Nvidia chips from Singapore, circumventing restrictions, and used ChatGPT to train its model.

Regardless of how China secured these critical technologies, the cat is indeed out of the bag. China has shown that it has the capability to develop new and emerging AI technologies. From the capabilities already built, it now has a baseline to create even more capabilities to develop its own AI chip ecosystem. With such capabilities, China will become more active within the information environment with the help of AI capabilities, and its motives are far from benevolent.

Why is the Chinese model free? China has several motives, but it is likely in hopes that data and information across the globe are the price tag for using the model while lessening a dependency on Western technologies and becoming a global leader in AI by 2030. Whatever data is obtained by the United States is icing on the cake. The West is not the primary target audience. Both models have servers in Singapore and China, where information is likely subject to Chinese laws, and terms and conditions are meaningless.

The Chinese will use AI technologies to gain an advantage in the information environment and seek to expand influence by creating an ecosystem for which other countries are dependent on their models. The incentive is to give countries this technology to foster dependency. The idea is similar to China’s debt-trap diplomacy—the Belt and Road Initiative. While ChatGPT’s basic model is free, China seeks to develop better models at a cheaper price to serve as leverage over countries that cannot afford the higher-end US-based models.

The United States is taking the right approach to maintaining its information advantage through AI development and investment. The billions pouring into creating AI data centers will play an important role in ensuring the United States has the edge in AI.

These data centers remain critical for identifying and countering any malign information operations against the United States, its partners, and its allies. When Iran attempted to influence the 2024 presidential election using the generative model GPT, OpenAI detected and shut it down. Without this expansive investment in AI data centers that keep information within the letter of US law and oversight, these interventions would be out of reach, and information operations may be even more challenging to detect.

However, this approach is insufficient without incorporating artificial Intelligence into all aspects of military operations. The DoD uses artificial intelligence within some branches, but given the expansive nature of AI, this is not enough. AI is expected to touch nearly all aspects of military operations, especially information operations, and may not have time to wait for its major AI initiative, Project Maven, to fully develop.

Some military scholars have called something like this a revolution in military affairs, but perhaps, given the impact of war, it could be classified as such. The concept is somewhat antiquated and outdated without some context, but it remains the best way to describe what should take place within the DoD. The foundation is already in place through the conceptual framework of multidomain operations.

Artificial capabilities are widely available through graphical user interfaces in deployable, ready-to-use form, such as ChatGPT or even internal large language models. The joint force should use these capabilities to the broadest extent possible. If anything, artificial intelligence, including large language models, will make joint and combined forces more lethal and accurate as they counter Chinese efforts within the information environment.

The DoD must adopt incentives for service members to understand the capabilities of AI and incorporate them in all training environments. These incentives can include bonuses for taking AI-driven courses. The DoD can also increase awareness and accessibility of AI courses on its education platforms which now have a paucity of artificial intelligence courses.

The DoD must also improve the training environment. With proprietary or off-the-shelf software, the DoD can incorporate AI offensive and defensive platforms within all training and mission-critical tasks. Even simply assisting with identifying generative outputs, e.g., deepfakes, will counter Chinese influence within the information environment, especially during hybrid conflict. Furthermore, military doctrine should recognize the importance of AI, especially information operations, with an emphasis on psychological operations.

While AI investment is critical to countering Chinese influence within the information environment, the only way to truly embrace multidomain operations is to ensure service members have the AI technical competency necessary to maneuver within the information environment deterring Chinese aggression.

US Army Lieutenant Colonel Matthew J. Fecteau is a PhD researcher at King’s College London studying how artificial Intelligence will impact conflict. He can be reached at matthew.fecteau.alumni@armywarcollege.edu.

China’s AI-Driven Information Operations Are Here: The US Needs an AI RMA was originally published on Global Security Review.

This digital divide is not just about access to technology but also about the ability to harness AI’s potential for economic, social, and global political empowerment. The implications of the AI divide are leading to a tech race that impact geopolitical power dynamics, exacerbating competition major powers like the US, China, France, and India. Depending on how the race ends, it could swing the balance of power in a negative direction.

AI Paris Summit

The recent AI Action Summit held in Paris emerged as a pivotal event that highlights both the opportunities and challenges associated with this evolving AI tech race. This summit serves as a beacon of innovation, encouraging France and India to collaborate more closely, while also exposing the complex interplay of international reactions, particularly from major powers like the United States, United Kingdom (UK), and China.

The summit focused on expanding AI’s boundaries while respecting environmental and ethical obligations. France’s President Emmanuel Macron reaffirmed his nation’s commitment to AI innovation, while maintaining high regulatory standards that draw parallels to Notre Dame Cathedral’s restoration. Such a strategy will likely accelerate AI ventures and foster innovation.

However, the regulation proposed was also a noose around the neck of the summit’s emphasis—deregulation. It is worth considering whether drastic deregulation will lead to genuine advances or the weakening of certain crucial safety nets as the world grapples with how to handle ever expanding data and the fragmentation that result from the intersection of geopolitical interests and the private ownership of data and capability. The US and China approach the issue differently than Europe, whose adoption of the AI Act (2023) will see the first comprehensive AI regulation in the world.

Many wondered how agentic AI will impact the balance of power. Whether AI will have a net positive or negative effect is uncertain. The rate at which agentic AI is developed and adopted in the three main economic blocs of China, Europe, and the United States will determine much.

India-France AI Alliance

India and France are forming a partnership to leverage AI’s full potential globally, sharing knowledge, resources, and best practices to create a robust framework for AI initiatives and global dialogue. During the summit, leaders from both countries addressed how their alliance could facilitate joint ventures, research collaborations, and talent exchange programs. Prime Minister Narendra Modi and President Macron foresaw great potential for future cooperation in 2019 when they endorsed the Indo-French Roadmap on Cybersecurity and Digital Technology. India and France, founding members of the Global Partnership on Artificial Intelligence, aim to develop a safe, open, secure, and ethical AI for human development and global commons.

Global Reactions

As the world watches the developments in Paris, reactions from other global powers, notably China and the United States, added another layer of complexity to the conversation around AI regulation and collaboration. In recent years, both states have invested heavily in AI research and development, seeing it as critical to their national security and economic competitiveness.

China’s approach to AI governance contrasts significantly with that of France and India. While the Chinese government prioritizes rapid innovation with minimal regulatory oversight, this led to concerns about privacy, surveillance, and ethical implications. The US, on the other hand, grapples with debates around data privacy, corporate responsibility, and the potential for AI misuse. As a result, the responses from these two states illustrate differing philosophies about how best to harness AI’s potential while safeguarding public interests.

The US and UK declined to sign a declaration on “inclusive and sustainable” artificial intelligence at the Paris summit, in a blow to hopes for a concerted approach to developing and regulating the technology. The document was backed by 60 other signatories on February 11, 2025, including France, China, India, Japan, Australia, and Canada.

The reactions from the relevant stakeholders highlight the urgent need for international cooperation and dialogue. As AI transcends borders, creating harmonized standards and frameworks could mitigate risks associated with its deployment.

Opportunities and Challenges Ahead

The summit concluded by emphasizing the need for proactive state engagement in AI regulation, prioritizing innovation while protecting individual rights and societal values. This, participants believed, would allow the world to fully capitalize on AI’s benefits.

As the world grapples with the realities of increasingly AI-driven technology, the voices of diverse stakeholders, including technologists, ethicists, policymakers, and civil society must be heard in shaping the future of AI. Under the flag of the AI Paris Summit, the India-France AI alliance is entering into a new and more unpredictable phase. By defying red tape and cultivating a spirit of cooperation, states are setting the pace for unlocking unprecedented opportunities while highlighting the inherent challenges of this transformative technology.

Huma Rehman is a project consultant, consultant, and defense and foreign affairs analyst. She can be reached at X @HumaRehman1.

AI Paris Summit and Emerging Paradox of AI Haves and Have-Nots was originally published on Global Security Review.

Semiconductors: The Backbone of Cyber Power

Semiconductors enable the computing power that drives everything from commercial applications to military operations. Advanced chips are critical for AI, autonomous systems, and national security infrastructure. As nations race to secure technological dominance, control over semiconductor production becomes a central element of cyber deterrence.

The production of semiconductors is extraordinarily complex and relies on a global supply chain. No single country is self-sufficient in this domain. Manufacturing processes demand rare metals, precision tools, and expertise spanning Japan, the Netherlands, South Korea, Taiwan, and the United States. Companies like TSMC (Taiwan), Intel (United States), and Samsung (South Korea) dominate the field, with TSMC leading in advanced chip production. Advanced Semiconductor Materials Lithography (ASML), a Dutch company, monopolizes the production of extreme ultraviolet (EUV) lithography machines, critical for fabricating cutting-edge chips.

The Strategic Importance of Semiconductors

Semiconductors are more than just a commercial product—they are a strategic resource that nations leverage to project power in cyberspace. The United States has long recognized the importance of staying ahead in chip technology, aiming to maintain at least a two-generation lead over adversaries like China. This lead is not just about technological superiority but is also about cyber deterrence.

Cyber deterrence relies on the ability to defend, retaliate, or disrupt an adversary’s cyber capabilities. Advanced semiconductors provide the computational power necessary for AI-driven cybersecurity systems, intelligence gathering, and offensive cyber operations. For example, autonomous systems in modern warfare require sophisticated chips to function effectively. If a nation lacks access to such technology, its cyber capabilities are significantly weakened.

China’s Vulnerability and Response

China, despite being the second-largest economy and a global manufacturing powerhouse, has a surprising weakness in the semiconductor supply chain. It spends more on importing chips than oil and relies heavily on foreign suppliers, including its geopolitical rivals. This dependency creates a critical vulnerability in its cyber and AI ambitions.

Recognizing this weakness, China launched massive initiatives to achieve self-sufficiency in semiconductor production. However, the barriers to entry are steep. Manufacturing cutting-edge chips requires material purity at a level of 99.99999 percent, and even a minor defect can render a chip unusable. The complexity of the global supply chain further complicates China’s efforts. For instance, ASML’s EUV lithography machines, essential for advanced chip production, are legally restricted from being sold to China under export control agreements led by the United States.

China’s strategy focuses on targeting chokepoints in the supply chain while ramping up domestic production of less advanced chips. Success in this endeavor would significantly alter the balance of power in cyberspace, enabling China to compete more effectively in AI and cyber operations. However, for now, its reliance on foreign technology remains a significant deterrent.

US Strategy: Strengthening Deterrence Through Dominance

The United States took proactive steps to secure its dominance in semiconductor technology as part of its cyber deterrence strategy. Legislation like the 2022 CHIPS and Science Act provides billions in subsidies to bolster domestic chip production. The US also works to integrate government, industry, and academia to address challenges in manpower, education, and research and development.

The American approach to cyber deterrence is twofold. First, it seeks to maintain its technological edge by investing in leading-edge chips while ensuring a robust supply of legacy nodes for essential systems. Second, it actively restricts access to critical technologies for adversaries. For instance, since 2018, the export of EUV lithography machines to China has been prohibited, a move aimed at stalling China’s progress in advanced semiconductor manufacturing.

This strategy aligns with the broader geopolitical framework, where supply chain control becomes a tool for exerting influence. By leveraging its dominance in semiconductors, the US can deny adversaries the tools they need to compete in AI-driven cyber capabilities, thereby strengthening its cyber deterrence posture.

The Role of AI and Advanced Chips in Cyber Deterrence

AI is a cornerstone of cyber operations, from defensive systems that identify and mitigate threats to offensive tools that exploit vulnerabilities in adversarial networks. The power of AI is directly tied to the availability of advanced chips, which enable greater computational efficiency and data processing.

In the AI arms race, semiconductors are the critical enabler. Nations with access to advanced chips can train larger models, process more data, and deploy more sophisticated algorithms. Conversely, those lacking access are at a significant disadvantage. This dynamic emphasizes the importance of securing semiconductor supply chains as part of national cyber deterrence strategies.

Geopolitics and the Future of Cyber Deterrence

The geopolitical implications of semiconductor dominance extend beyond cyber operations. Control over the chip supply chain influences alliances, trade policies, and even the balance of power in global governance. Governments increasingly push nations and companies to choose sides, creating a polarized landscape.

The US and its allies currently hold a strong position, but the race is far from over. As China invests heavily in self-sufficiency, the stakes in the semiconductor arms race continue to rise. The future of cyber deterrence will depend on the ability of nations to secure their supply chains, innovate in chip technology, and adapt to the rapidly evolving landscape of AI and cybersecurity.

Conclusion

Semiconductors are not just a technological marvel—they are a strategic weapon in the cyber domain. As nations compete for supremacy, control over chip production and supply chains will play a pivotal role in shaping cyber deterrence strategies. The US, with its technological edge and integrated approach, aims to maintain its dominance, while China’s efforts to overcome its vulnerabilities will redefine the global order. In this high-stakes competition, the invisible hand of the market is guided by the visible hand of governments, ensuring that semiconductors remain at the heart of cyber power.

Adam Harris, PhD, is a career cyber professional who both practices the profession and teaches at the university level. The views expressed are his own.    

Cyber Deterrence in the Age of Semiconductors was originally published on Global Security Review.

The EAR Report is a must read for National security professionals to stay informed about rapidly evolving global threats and the strategic implications for U.S. defense policy.

This report addresses critical developments in nuclear deterrence, missile defense, and geopolitical trends, and equips professionals with actionable insights to navigate the complexities of modern security challenges effectively.

Commentary and Quotes of the Week

• Defense Secretary Lloyd Austin: Reaffirmed the U.S.-ROK alliance and the strengthening of extended deterrence through the Nuclear Consultative Group.
  Peter Huessy: Detailed the financial and strategic implications of eliminating the ICBM leg of the U.S. nuclear triad, emphasizing the costs of alternative measures for maintaining current deterrence levels.
  Jon Finer, Deputy National Security Adviser: Highlighted Pakistan’s emerging threat with the development of long-range ballistic missile capabilities.
  Bill Gertz: Revealed China’s rapid nuclear buildup and the expansion of its missile capabilities.
  Russian Leaders: Asserted advancements in missile systems and dismissed arms control as a relic of the past.
  Rep. Chuck Fleischmann: Stressed the urgency of modernizing the U.S. nuclear deterrent, citing contributions from Tennessee’s Oak Ridge Lab.

Strategic Developments of the Week

• China’s Military Build-Up: The Pentagon report highlighted Beijing’s dramatic advancements in hypersonic missile technology, nuclear warheads, and ‘intelligentized warfare.’
  Russia’s Strategic Actions: Russia’s legislative shift regarding the Taliban and progress in missile systems underlined its geopolitical maneuvers.
  U.S. Missile Defense Challenges: Reports emphasized the lag in U.S. hypersonic missile capabilities compared to China, pressing the need for enhanced missile defense systems.
  Space and Drone Developments: New legislation and technological advances highlight the increasing role of space and drones in modern warfare.

Important Reports of the Week

1. “President Trump Must Put the Nuclear Enterprise on a Wartime Footing” by Robert Peters:
   • Advocates for accelerating nuclear arsenal modernization to restore deterrence credibility.
     Calls for a stronger commitment to stockpile stewardship and missile defense.
2. “Importance of Building Homeland Missile Defense” by Robert Joseph:
   • Reiterates the vision of a comprehensive missile defense system to counter emerging threats.
     Proposes leveraging space-based systems for more robust and efficient protection.
3. “What Happens if the United States Eliminates the ICBM Leg of the Triad?”:
   • Examines the repercussions of removing the ICBM leg, including massive financial costs for alternative deterrence methods and strategic vulnerabilities.

Download the Full Report

ICBM EAR Report for December 20th was originally published on Global Security Review.

Contacts with foreign sources were not very informative. The Chinese Ministry of Defense denied any use of drones over American or other territory, and their spokesperson added, “We get all the information we need from hacking into US government and industry sources.” They referred Americans to the Russians.

The Russian Security Council denied any involvement in flying drones over the East Coast. “Iran provides most of our drones, go talk to them,” was the only response we could get from officials. They added that President Putin has his own personal drone for use when he is hunting while riding bare chested in the Far East.

Iran’s Foreign Ministry was no more helpful on the issue saying, “Any drones we have will be used for surveillance of Israel or sent to the Russians for the Ukrainians to shoot down.”

Having exhausted foreign sources, Americans turned to domestic agencies. The Department of Homeland Security had no information about drones. “We are fully challenged to cope with unprecedented illegal border crossings, a meltdown of the Secret Service, and a FEMA fiasco in North Carolina to worry about drones,” said one agency official, on background.

The Department of Defense was not any more helpful. They denied having any information about drones, other than to say that there was no evidence of aliens being connected to drone activity in the United States. On the other hand, there was no evidence that the drones were not connected to aliens. They referred Americans to past episodes of The X Files.

The State Department reported that they had no contact with drones other than some foreign ambassadors who were posted to the United States and predictably uninformed about their activities.

The intelligence community said they did not necessarily know anything about drones, but even if they did, it would be classified and could not be shared with the media. This was an understandable reply.

A Republican member of Congress from New Jersey claimed that Iran had launched drones from a “mother ship” somewhere off the coast of the United States and that this information came from highly classified sources. This was corroborated by some boardwalk vendors of pizza in Ocean City and Wildwood, New Jersey. Their credibility was not challenged.

Some residents of New Jersey thought that tourists from Pennsylvania who visit New Jersey beaches during the summer are retaliating for exorbitant rental charges paid in previous years. Given prices, this is certainly an option worth exploring.

Others claimed that the drones were the work of environmentalists angered by shore communities’ wars against sea gulls, including the importation of hawks to chase gulls away from their natural habitats. Recent destruction of irreplicable works of art by environmentalists makes the illicit flying of drones over New Jersey easily conceivable.

Residents of New York suggested that New Jersey was seeking publicity to compensate for its comparative insignificance in national and regional affairs. “New Jersey is simply a suburb of New York and otherwise has no reason to attract news coverage,” was the explanation provided by one New Yorker.

But a New Jersey native came to her state’s defense. New Jersey residents, she said, were mentally exhausted from driving around in their infamous traffic circles until their brains boiled over; aliens or foreign enemies would be a welcome distraction.

An expert in artificial intelligence (AI) suggested that the drone swarms might be the result of an AI experiment gone awry, given the widespread use of “deepfakes” pervasive in social media and other sources. “The Jersey drone swarm could be the opening scene in the next Hollywood spectacular mixing fictitious events (alien invasions) with real events (military drone attacks) in order to smash box office records,” he noted.

Whatever the case may be is still undetermined. Needless to say, the longer it takes to find an answer, the more numerous the conspiracy theories will become. They will also grow increasingly more interesting for sure.

Professor Steve Cimbala, PhD, is a Senior Fellow at the National Institute for Deterrence Studies and Professor of Political Science at Penn State-Brandywine.

Drones on the Loose was originally published on Global Security Review.

See his recently published article here.

Podcast Episode: Keeping AI Honest in Nuclear Command and Control was originally published on Global Security Review.

The recent passage of the Framework Convention on Artificial Intelligence by the Council of Europe marks a significant turning point in the quest for effective and long-lasting control of AI. The document is a statement about how European states will harness AI, a relatively new and powerful technology, to empower humanity while limiting its abuses.

The March 2024 adoption of a US-led United Nations General Assembly resolution on seizing the opportunities of safe, secure, and trustworthy artificial intelligence systems for sustainable development also highlights the common ground the United States shares with Europe and democracies around the world. While the US differs in some important areas with Europe, the significant agreement is valuable. This convention provides a foundation for others to build on.

Although new technologies often appear benign at first glance, there are many ways AI, in particular, can negatively impact the values held dear by so many around the world. From facial recognition systems interfering with privacy to machine learning that amplifies injustice, the potential cost of AI’s misuse is high.

Until now, there was not an effort at global governance of AI. This fostered a string of national laws that lack the capacity to address the transnational nature of AI adequately. A system of fractured development silos creates a wide gap wherein technological advancement is prioritized over ethics.

There are a few AI regulatory developments  around the world for AI management worthy of note. First, the US House of Representatives debated the Digital Services Oversight and Safety Act of 2022 (H.R.6796) and the Algorithmic Accountability Act of 2023 (H.R. 5628). The AI Disclosure Act of 2023 (H.R. 3831) was also introduced before the House of Representatives.

Canada saw the introduction of the Artificial Intelligence Data Act (AIDA). The European Parliament began discussing the EU Artificial Intelligence Act in 2023, which represents a shift toward “hard law.” China is also addressing the issue and undertook the Interim Administrative Measures for the Management of Generative AI Services, which was enacted in 2023.

Recently, the United States passed the 2024 National Defense Authorization Act, which included a five-year implementation plan to adopt AI applications to accelerate decision advantage for both business efficacy as well as warfighting capability.

China also released the Global AI Governance Initiative, “calling for all countries under the principles of extensive consultation, joint contribution, and shared benefits to enhance exchanges and cooperation, work together to prevent risks, and develop an AI governance framework based on broad consensus, to make AI technologies more secure, reliable, controllable, and equitable.”

The Council of Europe’s Framework Convention, discussed above, provides a comprehensive legal structure to protect human rights, democracy, and the rule of law, besides promoting innovation. This strikes a balance where the use of technology should not be limited but society must ensure that development is in the right direction—with most of the technologies promoting ethical usage.

The Convention offers a set of guidelines for the advancement of AI that include respecting human dignity and upholding the idea that one should not infringe upon the rights and liberties of others. There is a significant urge to pursue explainability, which requires an explanation for each decision an AI makes and highlights how these systems have the power to significantly impact people’s lives in fields like criminal justice and healthcare. Additionally, the Convention calls for fairness in the creation of AI by considering prejudice in learning systems.

The Convention clearly aspires to international cooperation, which is important because it is a central element of the liberal international order. Numerous states agreed to the treaty, realizing that artificial intelligence is not a local problem. Such collaboration is required since artificial intelligence affects all states, and its advantages and disadvantages can only be addressed jointly. The agreement’s openness to other parties is crucial because it enables people from different backgrounds and cultures to voice their thoughts, enhancing and leveling the playing field.

As AI advances, concerns will grow about the agreement’s direction, applicability, and resource allocation. It implies that ethically right deeds now might turn unethical as technology develops, highlighting the necessity of a progressive framework for a code of ethics.

Since the development of AI must be accompanied by its ethical application, the Convention on Artificial Intelligence represents an important accomplishment in European regulation of the technology. Therefore, this treaty serves as a guide for how human rights, accountability, and openness should be upheld when integrating AI into society. The journey has only just begun. However, the political will and spirit to act, observe, and adopt the proper approach to governance can serve to achieve the benefits of AI.

Nevertheless, it will probably be difficult to put these rules and policies into foolproof practice. It will certainly be a work in progress. The European Council is certainly providing a road map for managing global mutual technology advancement concerns.

Huma Rehman is Director of Research at the Islamabad Policy Institute (IPI) and a Defense & Foreign Affairs Analyst. The views expressed are her own.   

Paving the Ethical Route for AI was originally published on Global Security Review.

The recent surge in OSINT intake is driven by the exponential growth of digital information, the proliferation of social media, and the increasing availability of online data. These factors have expanded the volume and variety of accessible information, enabling intelligence agencies to glean valuable insights from a vast array of sources, ranging from news articles and social media posts to academic publications and government reports. However, this influx of data necessitates advanced tools and techniques to manage, analyze, and extract actionable intelligence efficiently.

Artificial Intelligence (AI) and Machine Learning (ML) applications are being implemented across the American intelligence community to enhance capabilities, resulting in a significant increase in OSINT intake. Managing this surge requires leveraging advanced technology, enhancing analytical capabilities, and ensuring efficient collaboration. AI and ML algorithms automate data collection, filtering, and initial analysis. The development of natural language processing (NLP) tools to process large volumes of text data in multiple languages will mature over time with appropriate investment. Additional investment in scalable big data platforms that can handle OSINT data will be critical, utilizing cloud-based solutions for storage and processing to ensure scalability and flexibility.

Human capital enhancement is crucial for any strategic intelligence strategy. There must be an increased focus on recruiting and developing specialized training for intelligence analysts in OSINT techniques, tools, and methodologies. Continuous education programs will keep analysts updated on the latest technologies and trends. Expanding hiring efforts to identify experts in data science, cybersecurity, linguistics, and regional studies will increase the talent pool capable of enhancing the analytical capabilities of the intelligence community. By fostering an environment that promotes continuous learning and expertise in emerging technologies, the intelligence community can stay ahead of adversaries and ensure that their analysts have the necessary skills to leverage advanced tools effectively.

Interagency collaboration within the American intelligence community and with trusted allies is vital. Creating joint OSINT task forces involving multiple agencies fosters collaboration and information sharing, leveraging unique capabilities and expertise. Developing standardized protocols and best practices for OSINT collection and analysis enhances situational awareness and reduces duplication of efforts.

By establishing clear lines of communication and cooperation, intelligence agencies can ensure a more unified approach to addressing emerging threats and challenges. This collaboration also extends to international partners, creating a robust intelligence-sharing network that provides a broader perspective and pools resources to counteract the strategic moves of adversaries.

From a strategic perspective, developing secure and user-friendly platforms for sharing OSINT findings across different agencies is essential. Implementing interoperable systems for seamless data exchange, supported by comprehensive policies and guidelines aligned with legal mandates, builds trust between agencies and the public. Ensuring the security and integrity of data and communication channels is paramount, as it protects classified information from cyber intrusions and ensures the resilience of supply chains and critical infrastructure against cyber threats. Enhanced cybersecurity measures are essential for maintaining the trust and operational effectiveness of intelligence operations.

Reversing concerns about the expanding influence of the technology industry is necessary for the defense industry and intelligence community to embrace a collaborative environment that encourages growth, innovation, and trust. The technology industry already has expertise in these domains, which can be leveraged for public-private partnerships to access cutting-edge innovations. By fostering partnerships, the intelligence community can benefit from rapid advancements in technology and stay ahead of emerging threats. Collaboration with the technology industry also provides access to a pool of highly skilled professionals who can contribute to enhancing the capabilities of intelligence agencies.

The intelligence community must embrace public-private partnerships to foster a collaborative environment that encourages innovation. Establishing feedback mechanisms, conducting regular reviews, and setting up innovation labs within intelligence agencies ensures they stay ahead of emerging threats. Feedback mechanisms can include regular debriefings, user surveys, and performance metrics to assess the effectiveness of OSINT strategies. Review processes might involve periodic audits, peer reviews, and after-action reports to identify gaps and areas for improvement. Innovation labs can foster a culture of experimentation and rapid prototyping of new technologies and methodologies. By creating a space for testing and developing new ideas, innovation labs can drive significant advancements in intelligence operations and ensure that agencies are equipped to handle evolving threats.

Continuous improvement and adaptation will be key to maintaining a competitive edge in a dynamic and ever-changing global threat landscape. Establishing feedback mechanisms to continually assess the effectiveness of OSINT strategies and make necessary adjustments is essential. Conducting regular reviews and audits to identify gaps and areas for improvement will ensure that the intelligence community remains agile and responsive to emerging threats and challenges. Enhancing all-source analytical techniques for integrating OSINT with other intelligence sources (HUMINT, SIGINT, etc.) will provide a comprehensive view of the intelligence landscape, bridging the knowledge and awareness gaps that often plague the intelligence community.

To further support these advancements, the intelligence community must also embrace public-private partnerships to leverage the technology industry’s expertise and foster a collaborative environment that encourages innovation. Establishing feedback mechanisms, conducting regular reviews, and setting up innovation labs within intelligence agencies will ensure they stay ahead of emerging threats and challenges. By fostering a culture of experimentation and rapid prototyping, innovation labs can drive significant advancements in intelligence operations and ensure that agencies are equipped to handle evolving threats.

Managing the surge in OSINT requires a holistic approach that combines technological innovation, enhanced human capital, effective interagency collaboration, and robust policy frameworks. By adopting these strategies, the intelligence community can maintain its edge in an increasingly complex and dynamic world.

Joshua Thibert is a Senior Analyst at the National Institute for Deterrence Studies (NIDS). With nearly 30 years of comprehensive expertise, his background encompasses roles as a former counterintelligence special agent within the Department of Defense and as a practitioner in compliance, security, and risk management in the private sector. Views expressed are his own. 

AI Overload: Navigating the US Intelligence Community’s Data Deluge was originally published on Global Security Review.

This means the cost is going to be exorbitant over using the cloud’s “in-place” structure of GPUs, distributed power etc.  The DOD procured and set up their own system, but where is the data coming from?

Air Force Launches Its Own Generative AI Chatbot. Experts See Promise and Challenges

The Air Force has entered into the ChatGPT game.  was originally published on Global Security Review.

Integrating AI/ML into low-observable technology presents a promising avenue for enhancing stealth capabilities, but it also comes with its own set of challenges. ML algorithms rely on large volumes of high-quality data for training and validation. Acquiring such data for low-observable technology is challenging due to the classified nature of military operations and the limited availability of real-world stealth measurements.

ML algorithms analyze vast amounts of radar data to identify patterns and anomalies that were previously undetectable. This includes the ability to track stealth aircraft and missiles with greater accuracy and speed. These advancements have significant implications for deterrence strategies as traditional stealth technology may diminish in its effectiveness as AI/ML-powered radar becomes more sophisticated, potentially undermining the deterrent value of stealth aircraft and missiles.

Stealth technology remains a cornerstone of deterrence, allowing military assets to operate relatively undetected. Radar, on the other hand, is the primary tool for detecting and tracking these assets. However, AI/ML are propelling both technologies into new frontiers. AI algorithms can now design and optimize stealth configurations that were previously impossible. This includes the development of adaptive camouflage that dynamically responds to changing environments, making detection even more challenging.

Furthermore, stealth technology encompasses a multitude of intricately designed principles and trade-offs, including radar cross-section (RCS) reduction, infrared signature management, and reduction of acoustic variables. Developing ML algorithms capable of comprehensively modeling and optimizing these complex interactions poses a significant challenge. Moreover, translating theoretical stealth concepts into practical design solutions that can be effectively learned by ML models requires specialized domain knowledge and expertise.

As ML-based stealth design techniques become more prevalent, adversaries may employ adversarial ML strategies to exploit vulnerabilities and circumvent the defenses afforded to stealth aircraft. Adversarial attacks involve deliberately perturbing input data to deceive ML models and undermine their performance. Mitigating these threats requires the development of robust countermeasures and adversarial training techniques to enhance the resilience of ML-based stealth systems.

Additional complexities are inherent in the fact that ML algorithms often operate as “black boxes,” making it challenging to interpret their decision-making processes and understand the underlying rationale behind their predictions. In the context of stealth technology, where design decisions have significant operational implications, the lack of interpretability and explainability poses a barrier to trust and acceptance. Ensuring transparency and interpretability in ML-based stealth design methodologies is essential for fostering confidence among stakeholders and facilitating informed decision-making.

Implementing ML algorithms for stealth optimization involves computationally intensive tasks, including data preprocessing, model training, and simulation-based optimization. As low-observable technology evolves to encompass increasingly sophisticated designs and multi-domain considerations, the computational demands of ML-based approaches may escalate exponentially. Balancing computational efficiency with modeling accuracy and scalability is essential for practical deployment in real-world military applications.

Integrating AI and ML into military systems raises complex regulatory and ethical considerations, particularly regarding autonomy, accountability, and compliance with international laws and conventions. Ensuring that ML-based stealth technologies adhere to ethical principles, respect human rights, and comply with legal frameworks governing armed conflict is paramount. Moreover, establishing transparent governance mechanisms and robust oversight frameworks is essential to addressing concerns related to the responsible use of AI in military applications.

Addressing these challenges requires a concerted interdisciplinary effort, bringing together expertise from diverse fields such as aerospace engineering, computer science, data science, and ethics. By overcoming these obstacles, AI/ML has the potential to revolutionize low-observable technology, enhancing the stealth capabilities of military aircraft and ensuring their effectiveness in an increasingly contested operational environment. On the other hand, AI/ML has the potential to significantly impact radar technology, posing challenges to conventional low-observable and stealth aircraft designs in the future.

AI/ML algorithms can enhance radar signal processing capabilities by improving target detection, tracking, and classification in cluttered environments. Analyzing complex radar returns and discerning subtle patterns indicative of stealth aircraft, these algorithms can mitigate the challenges posed by low-observable technology, making it more difficult for stealth aircraft to evade detection.

ML algorithms can optimize radar waveforms in real time based on environmental conditions, target characteristics, and mission objectives. Dynamically adjusting waveform parameters such as frequency, amplitude, and modulation, radar systems can exploit vulnerabilities in stealth designs—increasing the probability of detection. This adaptive approach enhances radar performance against evolving threats, including stealth aircraft with sophisticated countermeasures.

Cognitive radar systems leverage AI/ML techniques to autonomously adapt their operation and behavior in response to changing operational environments. These systems learn from past experiences, anticipate future scenarios, and optimize radar performance adaptively. Continuously evolving their tactics and strategies, cognitive radar systems can outmaneuver stealth aircraft and exploit weaknesses in their low-observable characteristics.

AI/ML facilitates the coordination and synchronization of multi-static and distributed radar networks, comprising diverse sensors deployed across different platforms and locations. By fusing information from multiple radar sources and exploiting the principles of spatial diversity, these networks can enhance target detection and localization capabilities. This collaborative approach enables radar systems to overcome the limitations of individual sensors and effectively detect stealth aircraft operating in contested environments.

ML techniques can be employed to develop countermeasures against stealth technology by identifying vulnerabilities and crafting effective detection strategies. By generating adversarial examples and training radar systems to recognize subtle cues indicative of stealth aircraft, researchers can develop robust detection algorithms capable of outperforming traditional radar techniques. ML provides a proactive defense mechanism against stealth threats, potentially rendering conventional low-observable technology obsolete.

AI and ML enable the construction of data-driven models and simulations that accurately capture the electromagnetic signatures and propagation phenomena associated with stealth aircraft. By leveraging large datasets comprising radar measurements, electromagnetic simulations, and physical modeling, researchers can develop comprehensive models of stealth characteristics and devise innovative counter-detection strategies. These data-driven approaches provide valuable insights into the vulnerabilities of stealth technology and inform the design of more effective radar systems.

In the quest for technological superiority in modern warfare, the integration of AI and ML into radar technology holds significant promise with the potential to challenge conventional low-observable and stealth aircraft designs by enhancing radar-detection capabilities. AI and ML algorithms improve radar signal processing, optimize radar waveforms in real time, and enable radar systems to autonomously adapt their operation. By leveraging multi-static and distributed radar networks and employing adversarial ML techniques, researchers can develop robust detection algorithms capable of outperforming traditional radar systems. Moreover, data-driven modeling and simulation provide insights into the vulnerabilities of stealth technology, informing the design of more effective radar systems.

The rapid advancement of AI/ML is revolutionizing both stealth and radar technologies, with profound implications for deterrence strategies. Traditionally, deterrence has relied on the balance of power and the credible threat of retaliation. However, the integration of AI/ML into these technologies is fundamentally altering the dynamics of detection, evasion, and response, thereby challenging the established tenets of deterrence. Of further concern is the consideration that non-stealth assets become increasingly vulnerable to detection and targeting as ML-powered radar systems become more prevalent. This could lead to a greater reliance on stealth technology, further accelerating the arms race.

This rapid development of AI/ML-powered technologies could destabilize the existing balance of power, leading to heightened tensions and miscalculations. The changing technological landscape may necessitate the development of new deterrence strategies that incorporate AI and ML. This could include a greater emphasis on cyber warfare and the development of counter-AI and counter-ML capabilities.

The integration of AI/ML into stealth and radar technologies will be a game-changer for deterrence. To maintain stability and prevent conflict, policymakers and military strategists must adapt to this new reality of a continuous arms race, wherein both offensive and defensive capabilities are constantly evolving in pursuit of technological superiority. Continued investment in AI/ML research is essential to stay ahead of the curve and maintain a credible deterrent posture. International cooperation on the development and use of AI/ML technologies in military applications is crucial to limit the scope of a potential arms race that regularly shifts the balance of power and destabilizes global security.

Joshua Thibert is a Contributing Senior Analyst at the National Institute for Deterrence Studies (NIDS) and doctoral candidate at Missouri State University. His extensive academic and practitioner experience spans strategic intelligence, multiple domains within defense and strategic studies, and critical infrastructure protection. The views expressed in this article are the author’s own

The Double-edged Sword of Artificial Intelligence was originally published on Global Security Review.

Against a backdrop of conflict and global security concerns, 2023 may prove to have also been a pivotal year for automated nuclear weapons systems.

A year that began with chatbots and Artificial Intelligence (AI) as the subjects of major news stories – some with particularly concerning headlines – ended with members of the United States Congress introducing legislation to ban AI systems from nuclear weapons and US President Biden signing an Executive Order on the subject. The issue was even raised in discussions between the United States and China at the Asia-Pacific Economic Cooperation forum, which met in San Francisco in November.

One can imagine a hypothetical scenario in which a nuclear weapon targets a naval base, but an approach pattern recognition determines that the target submarines have already put to sea, and so the missile opts for a redirected underwater strike instead of an atmospheric detonation. This is but one of many possible scenarios to consider involving AI.

AI systems offer an opportunity to strengthen nuclear deterrence by providing a more accurate and capable defensive nuclear response. The purpose of making nuclear weapons more accurate and capable is not to promote their usage. Such capabilities, instead, provide a more credible deterrence to nuclear war and are consistent with classic nuclear doctrine. AI is simply a strategic tool, like nuclear weapons themselves.

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Should artificial intelligence be banned from nuclear weapons systems? was originally published on Global Security Review.

AI and the Future of Deterrence: Promises and Pitfalls was originally published on Global Security Review.

1. Foreword and Executive Summary:
   • The ASC program has utilized high-performance computing for nearly three decades to support U.S. nuclear deterrence following the 1992 ban on underground nuclear testing.
   • The integration of AI technologies aims to accelerate problem-solving for national security challenges.
   • The strategy emphasizes combining AI with existing modeling and simulation capabilities to enhance the U.S. Stockpile Stewardship Program.
2. AI4ND Strategy Objectives:
   • Apply AI methods to nuclear security missions, focusing on design, production, and analysis.
   • Develop ML tools to function with limited data and stringent accuracy requirements.
   • Create scalable and secure data infrastructures to support ML applications.
   • Foster a data-driven workforce by investing in training and developing expertise in AI and ML.
3. Motivations for AI in Nuclear Deterrence:
   • AI can reduce time for material discovery, model development, manufacturing, and maintenance.
   • AI/ML technologies promise to enhance the efficiency and responsiveness of the nuclear weapons lifecycle, including discovery, design optimization, manufacturing, certification, and maintenance.
4. Enabling Capabilities and Investment Areas:
   • Physics-Informed Machine Learning (PIML): Embedding physical constraints in ML models to ensure accuracy and speed in simulations.
   • Limited and Sparse Data Sets: Developing methods to work with limited experimental data and augmenting it with simulations.
   • Verification, Validation, Uncertainty Qualification, and AI Trustworthiness: Ensuring AI models are reliable and explainable, integrating existing verification practices.
   • Data Infrastructure: Investing in performant data storage, federated data environments, and flexible data access interfaces.
   • Machine Learning Architectures and Systems: Developing high-performance ML systems integrated with existing HPC platforms.
5. Workforce, Collaborations, and Partnerships:
   • Establishing partnerships with industry, academia, and other U.S. government agencies to leverage external advancements in AI/ML.
   • Developing international collaborations with similar programs in France, the UK, and Japan.
   • Building a capable workforce through training programs and collaboration with universities.
6. Conclusion:
   • The successful execution of this AI4ND strategy will enhance the ASC program’s ability to meet national security needs, increase efficiency, and attract specialized talent.
   • Collaboration with academia, industry, and other government agencies is crucial to achieving these goals.

The document emphasizes the transformative potential of AI in ensuring a secure and reliable nuclear deterrent through strategic investments in technology, data infrastructure, and workforce development. Get the report.

Artificial Intelligence for Nuclear Deterrence Strategy was originally published on Global Security Review.

From counterterrorism efforts to geopolitical forecasting, the applications of AI in strategic intelligence operations span a diverse array of domains, shaping national security strategies and global geopolitics alike. However, alongside these transformative capabilities come complex ethical, legal, and policy considerations that necessitate careful navigation.

            Foremost, AI has the ability to continuously monitor news sources, social media feeds, and other open-source intelligence channels in real time, alerting analysts to relevant developments as they happen. Sifting through massive datasets from diverse sources that include both open-source and classified reporting will allow analysts to quickly dismiss the “noise” and more easily discover relevant information that might otherwise be missed by human-driven analysis. Tedious and repetitive tasks, like report generation or data cleaning, can be automated, increasing efficiency and allowing analysts to focus their time and efforts on critical strategic analysis.

Furthermore, algorithms will unearth subtle trends, correlations, and anomalies that traditional analytical methods often overlook. This enhanced capability will empower proactive decision-making based on insights that would have otherwise remained hidden. Algorithms can help identify and mitigate potential biases in human analysis, promoting more objective decision-making processes. AI tools can act as a “smart assistant,” highlighting relevant information, providing summaries, and offering different perspectives to enhance human analysis. This frees up analysts from mundane information-gathering tasks and allows them to focus on higher-order strategic thinking.

Expanding further, the advanced collection and analytical features of AI will greatly assist with gauging potential instability in regions of interest, analyzing competitor activities, patent filings, and market trends, which can be streamlined with AI to quickly identify threats and opportunities. AI can analyze network traffic to detect anomalies indicative of potential cyberattacks, allowing for a faster response to cybersecurity threat detection.

The capabilities of generating and analyzing various potential scenarios based on historical data and current trends, in a fraction of the time needed for humans, provides analysts with a more comprehensive analysis for decision-makers to assess the likelihood of different outcomes and a higher confidence in predicting and understanding the consequences of their decisions. The AI-powered predictive analytical forecasting potential of geopolitical events, economic shifts, or emerging technologies that might create future strategic risks or opportunities for governments is attractive to all states as they leverage advantages to expand influence and power.

Incorporating AI capabilities into the strategic intelligence realm is not without its challenges or concerns. It will be imperative to ensure meaningful human control over any AI systems associated with strategic intelligence. Other national security assets should be considered a high priority at this critical onset of AI applications focused on the establishment of safeguards against autonomous decisions.

Considering AI relies on the accuracy and completeness of data, ensuring effective measures are in place to maintain data integrity and avoid garbage-in, garbage-out scenarios is critical. It is vital that AI models are interpretable so that analysts can understand the reasoning behind recommendations. This builds trust and facilitates better decision-making. Addressing biases in AI models and ensuring algorithms are used in a transparent and responsible manner that aligns with organizational values is also important.

Advancing AI may process vast amounts of data in times of crisis, and do it far faster than humans, though there is understandable concern about the appropriate level of AI involvement in high-stakes decisions where time is of the essence. For example, should AI have any control over nuclear launch decisions, and if so, how much? Errors in AI analysis or reliance on faulty data could lead to miscalculations and unintended escalation.

As intelligence agencies increasingly rely on advanced technologies like AI, there is a need for robust regulation and oversight to prevent abuse of power, misuse of data, and violations of civil liberties. Policies should establish clear guidelines for the collection, storage, and use of intelligence data, as well as mechanisms for accountability and transparency.

The proliferation of intelligence data and the use of advanced analytics pose challenges related to data security and protection. Policies must address issues such as data encryption, secure storage, access controls, and measures to safeguard against cyber threats and breaches.

Given the global nature of many intelligence threats, there is a need for international cooperation and the development of norms and standards governing the use of AI technologies. Policies should promote collaboration among intelligence agencies from different countries while respecting sovereignty and legal frameworks.

AI algorithms used in intelligence operations may exhibit bias or produce unfair outcomes, particularly if trained on biased data or programmed with flawed assumptions. Policies should address these concerns through measures such as algorithmic transparency, fairness assessments, and diversity in data sources and large language model (LLM) development.

The development and deployment of AI technologies can confer strategic advantages to nations or organizations. Policies may need to balance the pursuit of such advantages with efforts to prevent destabilizing arms races or conflicts arising from the use of intelligence capabilities.

The use of AI capabilities, particularly in areas such as cyber warfare or information operations, can raise the risk of deterrence failures or unintended escalation. Policies should seek to establish clear deterrence strategies, rules of engagement, and mechanisms for de-escalation to mitigate these risks. As AI technologies become more sophisticated, intelligence operations will increasingly involve human-machine collaboration. Policies should address issues such as human oversight, accountability for algorithmic decisions, and the ethical implications of human-AI interaction in intelligence activities.

The future of AI and strategic intelligence operations is poised to be characterized by continued innovation, integration, and adaptation to evolving geopolitical, technological, and societal landscapes. Further breakthroughs in AI technologies, including deep learning, natural language processing, and reinforcement learning, will enable intelligence agencies to extract deeper insights from vast and diverse datasets. This will enhance capabilities for predictive analysis, anomaly detection, and decision support across a wide range of intelligence operations.

The integration of AI into autonomous systems, such as unmanned aerial vehicles (UAVs) and unmanned underwater vehicles (UUVs), will certainly revolutionize intelligence, surveillance, and reconnaissance (ISR) capabilities. These systems will be capable of operating in contested or denied environments with reduced risk to human operators and logistical support assets.

The proliferation of cyber threats and the increasing reliance on information warfare tactics will drive the expansion of cyberintelligence capabilities. Intelligence agencies will focus on detecting, attributing, and mitigating cyberattacks, as well as leveraging information operations to shape narratives and influence adversaries.

The rise of social media platforms and digital communication channels will continue to reshape intelligence gathering and analysis. Open-source intelligence (OSINT) and social media analysis techniques will play an increasingly prominent role in monitoring global events, assessing public sentiment, and identifying emerging threats. Intelligence agencies will increasingly collaborate with other government agencies, international partners, and private-sector entities to leverage complementary expertise and resources. Fusion centers will facilitate the integration of intelligence from multiple sources to produce more comprehensive and timely assessments.

Intelligence agencies will need to enhance their resilience and adaptability to rapidly evolving threats, including emerging technologies, geopolitical shifts, and unconventional adversaries. This will require agile organizational structures, flexible operational frameworks, and continuous investment in training and capabilities development.

Overall, the future of AI and strategic intelligence operations will be characterized by a dynamic interplay between technological innovation, geopolitical dynamics, and societal trends. By embracing these trends and addressing associated challenges, intelligence agencies can enhance their effectiveness in safeguarding national security and advancing strategic objectives in an increasingly complex and interconnected world.

As the United States intelligence community navigates the complexities of an increasingly interconnected and unpredictable world, the future of strategic intelligence operations will be defined by our ability to harness the power of AI technologies while mitigating their risks and ensuring their responsible and ethical use. By embracing innovation, fostering collaboration, and upholding democratic values, intelligence agencies can effectively confront the challenges of the 21st century and advance the interests of peace, security, and prosperity for all.

Joshua Thibert is a Contributing Senior Analyst at the National Institute for Deterrence Studies (NIDS). With over 30 years of comprehensive expertise, his background encompasses roles as a former counterintelligence special agent within the Department of Defense and as a practitioner in compliance, security, and risk management in the private sector. The views expressed in this article are his own.  

Unveiling the Future: The Convergence of AI and Strategic Intelligence Operations was originally published on Global Security Review.

The newspaper cited U.S. officials, who described the incidents as potential forms of espionage.

Last year, the U.S. Department of Defense, FBI, and other agencies held a review to try to curb the frequency of these breaches, which involved unauthorized entries into US military bases and other federal sites, the newspaper reported.

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Chinese Nationals Posing as Tourists Have Accessed US Military Bases and Other Sensitive Sites: Report was originally published on Global Security Review.

What about potential nuclear weapon employment via the use of the Air Forces’ Collaborative Combat Aircraft (CCA)? An unmanned, autonomous, AI-piloted aircraft, the CCA will fly alongside crewed fighters, presumably to fly combat sorties resulting in casualties and battle damage. CCAs are intended to cost-effectively augment and enhance USAF combat capabilities and capacities without aggravating the fighter pilot shortage. These CCAs must be able to operate as loyal robotic wingmen tethered to manned fighter jets, as well as fly untethered with a high level of autonomy and trust when required. The real value of the untethered CCAs is the potential to deliver the most consequential weapons, through the most contested environments, against the most significant of targets without risking aircrew. The Secretary of the Air Force (SECAF) plans to build about 1,000 CCAs by the end of the next decade.

As conveyed by SECAF Frank Kendall in his Sept 5^th, 2023 memo to Airmen and Guardians, the Department is “not optimized for great power conflict” and the Department must devise and “implement the changes needed to meet our pacing challenge.” The SECAF’s clarion call to reorganize and reorient the Air Force must also encourage innovative and bold forms of integrated deterrence that include deploying AI-empowered CCAs with appropriate “strategic” capabilities like the new B61-13 intended to hold hard-to-reach targets at risk. Now is the time to begin crafting the prerequisite planning and acquiring to ensure this capability is possible in the future to avoid the much more costly retrofitting after delivery. Hermann Kahn once said, “Usually the most convincing way to look willing is to be willing.” This is essential for maintaining America’s nuclear deterrence and assurance credibility beyond 2030.

AI-Empowered Collaborative Combat Aircraft Can Enhance US Nuclear Deterrence Beyond 2030 was originally published on Global Security Review.