Artificial Intelligence for Nuclear Deterrence Strategies — Global Security Review

The document, “Artificial Intelligence for Nuclear Deterrence Strategy 2023,” outlines a strategy for the Advanced Simulation and Computing (ASC) program to integrate artificial intelligence (AI) and machine learning (ML) into the U.S. nuclear deterrence mission. Key points include:

1. Introduction and Overview:
   • The ASC program has been leveraging high-performance computing for nearly three decades to support the U.S. nuclear deterrent since the 1992 underground nuclear testing ban.
   • The integration of AI technologies aims to accelerate the resolution of national security challenges.
   • The strategy focuses on combining AI with existing modeling and simulation capabilities to enhance the U.S. stockpile management program.
2. AI4ND Strategic Objectives:
   • It applies AI techniques to nuclear security missions, with a focus on design, manufacturing, and analysis.
   • Develop ML tools that work with limited data and strict accuracy requirements.
   • Create a scalable, secure data infrastructure to support ML applications.
   • Cultivate a data-driven workforce by investing in training and expertise development in AI and ML.
3. Motivations for AI in Nuclear Deterrence:
   • AI can reduce the time it takes to discover materials, develop models, manufacture, and maintain them.
   • AI/ML technologies are expected to improve the efficiency and responsiveness of nuclear weapons lifecycle, including discovery, design optimization, manufacturing, certification, and maintenance.
4. Realization capabilities and investment areas:
   • Physics-Based Machine Learning (PIML): Incorporate physical constraints into ML models to ensure simulation accuracy and speed.
   • Limited and sparse data setsWe develop methods to work with limited experimental data and augment them with simulations.
   • Verification, validation, uncertainty qualification, and AI reliabilityIntegrate existing validation techniques to ensure trust and explainability of AI models.
   • Data Infrastructure: Invest in high-performance data storage, federated data environments, and flexible data access interfaces.
   • Machine Learning Architecture and SystemsDeveloping high-performance ML systems integrated with existing HPC platforms.
5. People, collaboration and partnerships:
   • Establish partnerships with industry, academia, and other U.S. government agencies to leverage external advances in AI/ML.
   • It has international collaborations with similar programs in France, the UK and Japan.
   • We develop talented people through training programs and collaboration with universities.
6. Conclusion:
   • Successful implementation of this AI4ND strategy will strengthen 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 essential to achieving these goals.

The paper highlights the transformative potential of AI in ensuring a safe and credible nuclear deterrent through strategic investments in technology, data infrastructure, and workforce development. Get the report.