by Hassan Fattahi and Zahra Mohebi-Pourkani
Abstract
- Introduction and Problem Statement
Humanity stands at a paradoxical crossroads: unprecedented scientific and technological advancement has augmented our power over nature and ourselves, yet this very power has multiplied our vulnerability to existential self-annihilation. Nowhere is this paradox more acute than in three domains—artificial intelligence (AI), climate change, and nuclear weapons—each of which transcends national borders and generational timescales. The term “existential threat” is reserved for dangers that could irreversibly curtail humanity’s future potential, whether by causing extinction or by permanently foreclosing the possibility of meaningful human flourishing.
AI represents a new class of transformative, dual-use technology whose trajectory is marked by accelerating capabilities, growing autonomy, and deepening integration in critical infrastructure and decision-making. Climate change, the cumulative legacy of industrial activity, has initiated biospheric feedback loops with the power to destabilize the planet’s life-support systems. Nuclear weapons, meanwhile, linger as a dangerous inheritance from 20th-century geopolitical rivalries, maintaining the capacity for instant, civilization-ending destruction.
These three threats are not independent; rather, they constitute a “triangle of danger” whose interactions may mutually exacerbate risks. This essay aims to provide an integrated analytical framework for understanding the existential nature of these threats, their interconnections, and the imperative for collective global responses. The central research objective is to synthesize contemporary scientific and policy literature to inform rational engagement with this dangerous triad.
- Detailed Examination of Threats
2.1 Advanced Artificial Intelligence: Threat from Within Technology
Artificial intelligence has transitioned from the realm of science fiction to a rapidly maturing technology with profound implications for security, economics, and society. Unlike prior technologies, AI possesses the potential for recursive self-improvement and generalization, raising concerns about alignment, control, and systemic risk.
The Alignment Problem
The alignment problem denotes the difficulty of ensuring that highly capable AI systems pursue goals that are compatible with complex, often-ambiguous human values such as freedom, dignity, and diversity. As noted by Bharati et al. (2023), opaque “black box” models in critical domains like healthcare already pose challenges in interpretability and trustworthiness, highlighting the broader risk that AI systems may adopt strategies or behaviors misaligned with intended outcomes (Bharati, Mondal & Podder, 2023). In the general case, misaligned superintelligent AI could, even without malice, optimize for objectives in ways that are catastrophic for humans.
Lethal Autonomous Weapons Systems (LAWS)
The development of lethal autonomous weapons—machines capable of independently identifying and attacking targets—raises unprecedented legal, ethical, and strategic dilemmas. As AI advances, the delegation of kill decisions to algorithms threatens to undermine humanitarian law and destabilize deterrence regimes, particularly if deployed in swarms or integrated into nuclear command structures (Bharati, Mondal & Podder, 2023).
Deepening Inequality and Concentration of Power
AI’s economic impact is deeply bifurcated. The concentration of data, computational resources, and algorithmic expertise in a handful of global corporations and states threatens to create insurmountable class divides. As with other disruptive technologies, the risk is that economic and informational power will accrue disproportionately, undermining social cohesion and democratic governance (Bharati, Mondal & Podder, 2023).
Information Warfare and Erosion of Truth
AI-powered tools such as deepfakes and synthetic media facilitate unprecedented manipulation of information ecosystems. The capacity for automated, scalable misinformation erodes public trust, electoral integrity, and national security, compounding the epistemic crisis already afflicting many societies (Bharati, Mondal & Podder, 2023).
Mass Structural Unemployment
Automation, increasingly driven by machine learning and robotics, threatens structural unemployment on a global scale. While AI can augment productivity and create new job categories, the pace and scope of displacement—especially in cognitive and service sectors—may exceed the capacity of economies to adapt, engendering political instability (Bharati, Mondal & Podder, 2023).
Pervasive Surveillance
AI-powered surveillance architectures enable the real-time monitoring and prediction of individual and collective behavior. These capabilities, when combined with big data analytics, empower both state and corporate actors, strengthening authoritarian governance models and raising profound questions about privacy and autonomy (Bharati, Mondal & Podder, 2023).
Acceleration of Arms Races
Military competition in AI, especially between major powers, fosters an arms race dynamic. Rapid deployment of untested or poorly understood systems in critical military functions increases the likelihood of accidents, misperceptions, and escalation, particularly in crisis scenarios involving nuclear weapons (Bharati, Mondal & Podder, 2023).
Critical Infrastructure Vulnerability
AI systems can be weaponized to identify and target vulnerabilities in essential infrastructure—electricity, water, transport, financial systems—either directly or as part of cyber-physical attacks. The potential for cascading failures and systemic collapse is heightened by the interconnectedness of modern infrastructure (Bharati, Mondal & Podder, 2023).
Erosion of Human Agency and Judgment
The increasing delegation of decision-making to AI systems risks the atrophy of critical human skills—judgment, accountability, and creative problem solving (Gizzi et al., 2022). As AI becomes more central in high-stakes domains, the danger grows that humans will become passive overseers, unable or unwilling to challenge machine recommendations.
Facilitation of Other Threats
AI is a force multiplier for other existential risks. It can accelerate research in chemical and biological weapons, guide cyberattacks on nuclear command and control, and optimize the destructive exploitation of natural resources (Bennett & Hauser, 2013). The dual-use character of AI underscores the urgency of robust governance frameworks (Bharati, Mondal & Podder, 2023).
2.2 Climate Change: Threat from Interaction with the Biosphere
Climate change, driven by anthropogenic greenhouse gas emissions, is destabilizing the Earth system in ways that directly threaten the foundations of human civilization. The latest climate science points to both gradual and abrupt risks, some of which may be irreversible on human timescales (O’Gorman, 2015; Sanjay et al., 2020).
Frequent Extreme Weather Events
Climate change is intensifying the frequency and severity of extreme weather events—floods, storms, droughts, heatwaves—causing direct loss of life and vast economic damage (O’Gorman, 2015). Observational and modeling studies indicate that precipitation extremes in particular are increasing in response to warming, with the sensitivity of such extremes higher in the tropics than the extratropics (O’Gorman, 2015; Sanjay et al., 2020).
Sea-Level Rise and Climate Refugees
Accelerated melting of polar ice and thermal expansion of oceans are driving sea-level rise, threatening coastal settlements worldwide. Projected increases, especially under high-emission scenarios, could displace tens to hundreds of millions of people this century, creating waves of climate refugees and intensifying geopolitical instability (Sanjay et al., 2020).
Food and Water Security Crisis
Climate-induced shifts in temperature and precipitation patterns are already disrupting agricultural productivity and freshwater availability. Projections for the Indian region, for instance, show increased uncertainty and intensity of both dry and wet seasons, placing tremendous strain on biophysical systems and dependent economic sectors (Sanjay et al., 2020). The risk is acute for populations already vulnerable to hunger and water scarcity.
Mass Extinction and Ecosystem Collapse
Biodiversity loss, driven by habitat alteration, ocean acidification, and other climate-related stressors, undermines the ecosystem services upon which civilization depends—pollination, water purification, disease regulation. The current extinction rate already far exceeds the background rate, and crossing ecological tipping points could precipitate wholesale ecosystem collapse (O’Gorman, 2015).
Global Health Crisis
Climate change is expanding the geographic range of vector-borne diseases, increasing heat stress mortality, and exacerbating respiratory conditions through air pollution and wildfire smoke. The interplay between climate and health systems is complex and poorly understood, but the trend points toward mounting global health emergencies (O’Gorman, 2015).
Conflict and Instability Multiplier
Resource scarcity and extreme weather act as “threat multipliers,” fueling social unrest, interstate conflict, and mass migration. The links between climate and conflict are mediated by economic shocks, governance capacity, and preexisting tensions, but the overall effect is to heighten instability (Sanjay et al., 2020).
Crippling Economic Losses
Direct disaster costs and indirect disruptions to supply chains, infrastructure, and productivity are mounting. High-resolution downscaled climate projections for South Asia, for example, highlight the potential for regional economic shocks as precipitation and temperature extremes intensify (Sanjay et al., 2020).
Crossing Irreversible Tipping Points
Certain Earth system processes—permafrost thaw, ice sheet collapse, Amazon dieback—have the potential to trigger runaway feedbacks, locking in catastrophic warming and sea-level rise. The uncertainty and irreversibility of such tipping points are a central concern in contemporary climate science (O’Gorman, 2015).
Unequal Distribution of Suffering
Climate change is fundamentally unjust: those least responsible for emissions are most vulnerable to its impacts. Models project that the semi-arid and northern regions of India, for example, will experience more rapid warming, while adaptation capacity is lowest in the poorest communities (Sanjay et al., 2020).
Threat to Statehood and International Order
Small island developing states face existential risk from submersion, threatening their sovereignty and the stability of international order. The possibility of entire nations disappearing from the map is no longer theoretical (Sanjay et al., 2020).
2.3 Nuclear Weapons: Threat Surviving from the Cold War Era
Despite the end of the Cold War, nuclear weapons remain at peak destructive capacity, with over 13,000 warheads held by nine states. The risk of nuclear conflict, whether through deliberate use, miscalculation, or accident, remains unacceptably high.
Immediate Mass Destruction
Even a “limited” nuclear exchange could kill millions within hours, destroy urban infrastructure, and overwhelm health and emergency systems. The effects would not be confined to the belligerents; radioactive fallout and climatic impacts would be global (Bennett & Hauser, 2013).
Nuclear Winter
Detonations of nuclear weapons can inject vast quantities of soot into the stratosphere, blocking sunlight and triggering a “nuclear winter.” Models predict that the resulting global cooling and precipitation decline could cause widespread crop failures and famine, threatening billions (Bennett & Hauser, 2013).
Proliferation Risks
The spread of nuclear weapons to new states—and potentially to non-state actors—raises the likelihood of use. As technical barriers to acquisition decline and arms control regimes erode, the world faces a new era of proliferation instability (Bennett & Hauser, 2013).
Human, Technical, or Judgment Errors
Numerous near-catastrophic incidents during the Cold War and since have revealed the systemic fragility of nuclear command and control, particularly under crisis conditions. False alarms, miscommunication, and technical failures remain a persistent risk (Bennett & Hauser, 2013).
Cyber Vulnerability
The integration of digital technology into nuclear command, control, and communications (C3) introduces new vulnerabilities. Cyberattacks could spoof warnings, degrade decision-making, or even trigger accidental launches (Bennett & Hauser, 2013).
Nuclear Terrorism
The possibility that terrorist groups could acquire nuclear materials or weapons, whether through theft, state collapse, or black markets, adds a new dimension to the nuclear threat landscape (Bennett & Hauser, 2013).
Long-Term Radioactive Contamination
The environmental and health effects of nuclear detonations persist for generations, with radioactive fallout poisoning land, water, and air (Bennett & Hauser, 2013).
Infrastructure Destruction via EMP
High-altitude nuclear detonations can generate electromagnetic pulses (EMP) capable of destroying electronic infrastructure over vast regions, effectively “resetting” technological civilization in targeted areas (Bennett & Hauser, 2013).
Erosion of Non-Proliferation Norms
The weakening of arms control agreements and non-proliferation norms increases the risk that nuclear weapons will spread and be used (Bennett & Hauser, 2013).
Massive Opportunity Costs
The resources devoted to maintaining and modernizing nuclear arsenals represent vast opportunity costs, diverting funds from addressing other existential risks, including climate adaptation and AI safety (Bennett & Hauser, 2013).
- Dangerous Interactions and Mutual Escalation
The existential risks posed by AI, climate change, and nuclear weapons are not independent. Rather, their interactions may create new “compound risks” that are greater than the sum of their parts.
AI × Nuclear Weapons
The integration of AI into nuclear command and control—whether in early warning, targeting, or decision-support—shortens decision times and increases the risk of accidental or unauthorized launches. AI-driven cyberattacks could compromise nuclear systems, increasing the danger of miscalculation or escalation. As Bennett and Hauser (2013) argue, automation in clinical and other high-stakes decision contexts must be accompanied by robust safeguards, yet in military settings the incentives for rapid deployment may override caution.
Climate Change × Conflict and Nuclear Risk
Resource scarcity and state fragility driven by climate change can heighten geopolitical tensions, increasing the risk of conflict between nuclear-armed states. The interplay of food and water crises, mass migration, and weakened governance creates fertile ground for escalation, whether intentional or accidental (Sanjay et al., 2020).
AI × Climate Change
AI offers tools for climate modeling, mitigation, and adaptation—improving forecasts, optimizing energy systems, and designing resilient infrastructure (O’Gorman, 2015). However, AI can also worsen crises by optimizing fossil fuel extraction, enabling intrusive surveillance of populations, or facilitating the rapid exploitation of natural resources. The dual-use dilemma is ever-present (Bharati, Mondal & Podder, 2023).
The Triangle of Danger
These interactions underscore the need for a holistic perspective. Addressing each threat in isolation is insufficient; instead, integrated approaches are needed to understand and manage the complex, nonlinear dynamics of compound existential risk.
- Proposed Research Objectives and Questions
Given the magnitude and interdependence of these threats, future research must address both their individual and collective dimensions. Key research objectives include:
Designing New Governance Frameworks
There is an urgent need to explore international governance models capable of addressing transboundary, compound existential risks. Existing institutions—such as the International Atomic Energy Agency (IAEA) and Intergovernmental Panel on Climate Change (IPCC)—must be strengthened and new bodies for AI governance created (Bharati, Mondal & Podder, 2023; Sanjay et al., 2020).
Compound Risk Modeling
Quantitative models that capture the probabilities and outcomes of interactive scenarios are essential. For instance, what is the likelihood of a major climate disaster coinciding with political instability in a nuclear state, and how might AI-driven cyberattacks complicate crisis management? Insights from dynamic decision networks and Markov decision processes, as applied in healthcare (Bennett & Hauser, 2013), can be adapted to model these compound risks.
Analysis of Destabilizing Pathways
Research must focus on the specific ways in which AI could be misused against climate or nuclear security. This includes scenario analysis, red-teaming, and the development of early warning systems (Bharati, Mondal & Podder, 2023).
Convergent Solutions
Identifying technologies and policies that reduce all three threats simultaneously is a priority. For example, scientific diplomacy, transparency mechanisms, and the use of AI for verification and monitoring can build trust across domains (Bharati, Mondal & Podder, 2023).
Crisis Preparedness Planning
International emergency protocols must be designed for “black swan” events—such as a major climate disaster coinciding with a crisis in a nuclear-armed state. Lessons from healthcare AI, where real-time data-driven decision support systems have improved outcomes (Bennett & Hauser, 2013), can inform the development of analogous systems for existential threat management.
- Strategic Recommendations
Addressing the existential triad of AI, climate change, and nuclear weapons requires fundamentally rethinking global governance, research priorities, and public education.
Strengthening International Institutions
Empowering and resourcing organizations such as the IAEA and IPCC is essential. Equally, new institutions must be created to govern the development and deployment of advanced AI, drawing on lessons from arms control and climate diplomacy (Sanjay et al., 2020; Bharati, Mondal & Podder, 2023).
Science-Based Diplomacy
Permanent scientific and technical dialogue channels among major powers should be established, insulated from political fluctuations. The interdisciplinary nature of these threats demands sustained cooperation among AI experts, climate scientists, disarmament specialists, and social scientists (Bharati, Mondal & Podder, 2023).
Investment in “Safe Science”
Dedicated research budgets for existential risk studies and mitigation strategies are needed. As Bennett and Hauser (2013) demonstrate in healthcare, investment in AI safety and dynamic decision support can yield both improved outcomes and cost savings.
Global Education and Awareness
The study of existential threats and their solutions must be integrated into curricula at all levels, from primary education to doctoral research. Public awareness campaigns are vital to build support for necessary policy changes (Bharati, Mondal & Podder, 2023).
Transparency and Trust Frameworks
Mandatory reporting and transparency in military AI, nuclear programs, and climate actions should be instituted. Verification regimes, perhaps leveraging AI itself for monitoring and compliance, can build the trust necessary for effective arms control and climate agreements (Bharati, Mondal & Podder, 2023).
- The Role of Creative Problem Solving and Explainability
A recurring theme in the analysis of all three existential threats is the centrality of human creativity, adaptability, and explainability in both problem identification and solution generation.
Creative Problem Solving in AI and Governance
As explored by Gizzi et al. (2022), creative problem solving (CPS) is essential in circumstances where established knowledge and routines are insufficient. The ability of both human and artificial agents to formulate novel solutions in ill-defined, high-stakes scenarios is crucial for crisis management. In the context of existential risk, CPS frameworks should guide the design of both AI systems and policy institutions, ensuring flexibility, adaptability, and robustness in the face of unprecedented challenges (Gizzi et al., 2022).
Explainable Artificial Intelligence
The lack of transparency and explainability in AI systems is a major barrier to trust and effective governance, particularly in safety-critical domains like healthcare, military, and infrastructure (Bharati, Mondal & Podder, 2023). Explainable AI (XAI) methodologies are needed to ensure that decisions can be understood, audited, and contested. The distinction between explainability and interpretability is particularly important: the former addresses why a decision was made, the latter how (Bharati, Mondal & Podder, 2023). In existential risk contexts, XAI can help prevent catastrophic errors by enabling human oversight and intervention.
Adaptive Decision Support Systems
Bennett and Hauser (2013) demonstrate the power of Markov decision processes and dynamic decision networks for simulating complex, uncertain environments in healthcare. Similar approaches can be adapted for existential risk management, providing real-time, data-driven guidance for policymakers, emergency responders, and international institutions.
- Case Studies and Empirical Evidence
To ground the analysis, it is instructive to examine empirical evidence from the domains of climate science and AI as they relate to existential risk.
Climate Change Projections and Regional Vulnerabilities
O’Gorman (2015) provides a comprehensive synthesis of theoretical, modeling, and observational results on the intensification of precipitation extremes under climate change. Observations show that precipitation extremes have intensified as the global mean temperature has risen, with sensitivities higher in the tropics (8–9% per degree K) than in the extratropics (4–6% per degree K). The physical mechanisms—thermodynamic (Clausius-Clapeyron scaling), microphysical, and dynamical—are increasingly well understood, though uncertainties remain, especially regarding tropical convection and mesoscale organization (O’Gorman, 2015).
Sanjay et al. (2020) extend this analysis with high-resolution, downscaled projections for the Indian region, showing that warming will be particularly pronounced in the semi-arid northwest and north, with annual mean temperatures rising by up to 4°C under high-emission scenarios by the end of the century. Precipitation patterns are projected to become more extreme and uncertain, particularly under RCP8.5, with the west coast and peninsular India facing intensified wet and dry seasons. The dominance of internal variability at sub-regional scales complicates adaptation planning, but the overall trajectory is clear: climate change will amplify existing vulnerabilities and create new ones (Sanjay et al., 2020).
AI in Healthcare: Promise and Peril
Bharati et al. (2023) document the rapid proliferation of AI models in healthcare, noting both their promise and their limitations. The opacity of many models, the risk of bias and error, and the difficulty of evaluating explanations pose significant obstacles to trust and adoption. Nonetheless, AI has demonstrated the capacity to improve diagnostic accuracy, personalize treatment, and optimize resource allocation. The challenge is to ensure that these benefits are realized without introducing new, systemic risks (Bharati, Mondal & Podder, 2023).
Bennett and Hauser (2013) show that AI-based decision-support systems, when carefully designed, can outperform conventional healthcare models, delivering better outcomes at lower cost. However, the complexity and uncertainty of real-world environments demand robust frameworks for simulation, adaptation, and oversight. The lessons learned in healthcare AI are directly relevant to managing existential threats in other domains.
Creative Problem Solving in AI Agents
Gizzi et al. (2022) argue that creative problem solving in AI is essential for dealing with environmental uncertainty and novel challenges. Their framework, which categorizes CPS problems in terms of problem formulation, knowledge representation, knowledge manipulation, and evaluation, provides a valuable blueprint for designing AI systems capable of responding to unprecedented existential risks. The capacity for CPS in both humans and machines will be critical for crisis adaptation and recovery.
- The Imperative of Integrated Global Governance
The analysis presented here converges on a central conclusion: humanity’s existing governance structures are ill-equipped to manage the scale, complexity, and interdependence of existential risks posed by AI, climate change, and nuclear weapons. The fragmentation of institutional responsibility, the short-termism of political cycles, and the erosion of public trust all conspire to undermine effective action.
Toward a Revolution in Global Governance
What is needed is a revolution in global governance thinking—one that is rooted in scientific understanding, foresight, and the prioritization of collective survival over parochial interests. Such a revolution must embrace:
Interdisciplinarity: Bridging the divides between technical, social, and policy expertise.
Transparency: Mandating openness in research, deployment, and decision-making.
Flexibility: Designing institutions and systems that can adapt to new information and changing circumstances.
Inclusivity: Ensuring that the voices of the most vulnerable and least powerful are heard and respected.
Solidarity: Cultivating a sense of shared fate and responsibility across nations and generations.
The Role of International Law and Norms
Legal instruments—treaties, conventions, and customary norms—will remain central to managing existential risks. However, the pace of technological change, especially in AI, outstrips the capacity of traditional legal processes. New models of anticipatory governance, including “soft law” mechanisms, multi-stakeholder forums, and adaptive regulation, are essential (Bharati, Mondal & Podder, 2023).
Public Engagement and Democratic Legitimacy
Ultimately, the legitimacy and effectiveness of existential risk governance depend on public understanding and support. Education, transparent communication, and genuine participatory mechanisms are vital for building the social mandate required for transformative action (Bharati, Mondal & Podder, 2023).
- Conclusion
Artificial intelligence, climate change, and nuclear weapons are not merely technical challenges; they are manifestations of humanity’s current incapacity to govern the immense, transboundary powers we have unleashed. Each, taken alone, presents a risk of irreversible catastrophe; together, their interactions multiply the dangers in ways that defy piecemeal solutions.
The scientific literature is unequivocal: addressing these threats in isolation is insufficient. The only viable path to securing a safe and sustainable future is through simultaneous, integrated action that recognizes their interdependence. This requires a revolution in global governance, grounded in cooperation, transparency, and a commitment to collective survival.
The next step must be the establishment of an interdisciplinary working group—comprising AI experts, climate scientists, disarmament specialists, social scientists, and policymakers—to expand and operationalize the strategies outlined here. Only by combining our knowledge, creativity, and determination can we hope to manage the existential threats of the 21st century and safeguard the potential of generations yet unborn.
Bibliography
Bennett, C.C. & Hauser, K. (2013) Artificial Intelligence Framework for Simulating Clinical Decision-Making: A Markov Decision Process Approach. Artificial Intelligence in Medicine. In Press. Available at: https://arxiv.org/pdf/1301.2158v1
Bharati, S., Mondal, M.R.H. & Podder, P. (2023) A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When? Available at: https://arxiv.org/pdf/2304.04780v1
Gizzi, E., Nair, L., Chernova, S. & Sinapov, J. (2022) Creative Problem Solving in Artificially Intelligent Agents: A Survey and Framework. Available at: https://arxiv.org/pdf/2204.10358v1
O’Gorman, P.A. (2015) Precipitation extremes under climate change. Current Climate Change Reports. Available at: https://arxiv.org/pdf/1503.07557v1
Sanjay, J., Krishnan, R., Ramarao, M.V.S., Mahesh, R., Singh, B.B., Patel, J., Ingle, S., Bhaskar, P., Revadekar, J.V., Sabin, T.P. & Mujumdar, M. (2020) Future Climate Change Projections over the Indian Region. Available at: https://arxiv.org/pdf/2012.10386v1
Dr. Zahra Mohebi-Pourkani is a distinguished General Practitioner and Family Physician with a distinguished career in medical service and public health leadership. Since 2008, she has accrued extensive clinical experience across diverse regions, currently serving as the Head of a government clinic in Kerman province, Iran. Beyond her clinical and administrative responsibilities, Dr. Mohebi is deeply engaged in scholarly and humanitarian pursuits. She maintains a strong academic interest in amateur astronomy, development studies, and the dynamic relationship between science and society. This interest extends to her work as a contributor to reputable Iranian and international newspapers and magazines. Dr. Mohebi is passionately committed to education and capacity building. She dedicates significant effort to pedagogical activities, particularly in fostering scientific curiosity among children through laboratory instruction. Furthermore, she has designed and led professional development courses for her colleagues, focusing on critical topics at the intersection of science and societal progress. Her professional ethos is characterized by a profound commitment to social welfare, evidenced by her non-profit collaborations dedicated to the betterment of Iranian children. A dedicated advocate for global peace, Dr. Mohebi is a vocal proponent of disarmament and stands firmly against the proliferation and use of weapons of mass destruction.
Hassan Fattahi is a lecturer and writer who specializes in physics, astronomy, and science policy. His work encompasses original research, translation, and consulting, and has been featured in prominent Iranian and international publications. He is actively committed to promoting science education in Iran.
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