Militaries seek to harness artificial intelligence for decision advantage. Yet AI systems introduce a new source of uncertainty in the likelihood of technical failures. Such failures could interact with strategic and human factors in ways that lead to miscalculation and escalation in a crisis or conflict. Harnessing AI effectively requires managing these risk trade-offs by reducing the likelihood, and containing the consequences of, AI failures.

Despite being a small city-state, Singapore’s star continues to rise as an artificial intelligence hub presenting significant opportunities for international collaboration. Initiatives such as fast-tracking patent approval, incentivizing private investment, and addressing talent shortfalls are making the country a rapidly growing global AI hub. Such initiatives offer potential models for those seeking to leverage the technology and opportunities for collaboration in AI education and talent exchanges, research and development, and governance. The United States and Singapore share similar goals regarding the development and use of trusted and responsible AI and should continue to foster greater collaboration among public and private sector entities.

CSET Director of Biotechnology Programs Anna Puglisi testified before the U.S.-China Economic and Security Review Commission at a hearing on "China’s Challenges and Capabilities in Educating and Training the Next Generation Workforce."

China’s government has pushed the country’s technology and financial firms to expand abroad, and Southeast Asia’s growing economies — and AI companies — offer promising opportunities. This report examines the scope and nature of Chinese investment in the region. It finds that China currently plays a limited role in Southeast Asia’s emerging AI markets outside of Singapore and that Chinese investment activity still trails behind that of the United States. Nevertheless, Chinese tech companies, with support from the Chinese government, have established a broad range of other AI-related linkages with public and commercial actors across Southeast Asia.

Machine learning advances have powered the development of new and more powerful generative language models. These systems are increasingly able to write text at near human levels. In a new report, authors at CSET, OpenAI, and the Stanford Internet Observatory explore how language models could be misused for influence operations in the future, and provide a framework for assessing potential mitigation strategies.

CSET's Ali Crawford and Jessica Ji submitted this comment to the Office of the National Cyber Director in response to a request for information on a national strategy for a cyber workforce, training, and education.

China is rapidly building cyber ranges that allow cybersecurity teams to test new tools, practice attack and defense, and evaluate the cybersecurity of a particular product or service. The presence of these facilities suggests a concerted effort on the part of the Chinese government, in partnership with industry and academia, to advance technological research and upskill its cybersecurity workforce—more evidence that China has entered near-peer status with the United States in the cyber domain.

Funding and priorities for technology development today determine the terrain for digital battles tomorrow, and they provide the arsenals for both attackers and defenders. Unfortunately, researchers and strategists disagree on which technologies will ultimately be most beneficial and which cause more harm than good. This report provides three examples showing that, while the future of technology is impossible to predict with certainty, there is enough empirical data and mathematical theory to have these debates with more rigor.

In the current cyber-threat environment, a well-educated workforce is critical to U.S. national security. Today, however, nearly six hundred thousand cybersecurity positions remain unfilled across the public and private sectors. This report explores high school cybersecurity competitions as a potential avenue for increasing the domestic cyber talent pipeline. The authors examine the competitions, their reach, and their impact on students’ educational and professional development.

We aim to demonstrate the value of mathematical models for policy debates about technological progress in cybersecurity by considering phishing, vulnerability discovery, and the dynamics between patching and exploitation. We then adjust the inputs to those mathematical models to match some possible advances in their underlying technology.