Artificial intelligence systems are rapidly being deployed in all sectors of the economy, yet significant research has demonstrated that these systems can be vulnerable to a wide array of attacks. How different are these problems from more common cybersecurity vulnerabilities? What legal ambiguities do they create, and how can organizations ameliorate them? This report, produced in collaboration with the Program on Geopolitics, Technology, and Governance at the Stanford Cyber Policy Center, presents the recommendations of a July 2022 workshop of experts to help answer these questions.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This five-part series uses data from the U.S. Department of Education and other select sources to complement existing CSET work on the U.S. AI workforce.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This five-part series uses data from the U.S. Department of Education and other select sources to complement existing CSET work on the U.S. AI workforce.

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 Research Analyst Dahlia Peterson 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."

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.

U.S. policies on artificial intelligence education and the AI workforce must grow, cultivate, attract, and retain the world’s best and brightest. Given China’s role as a producer of AI talent, understanding its AI workforce could provide important insight. This report provides an analysis of the AI workforce demand in China using a novel dataset of 6.8 million job postings. It then outlines potential implications along with future reports in this series.

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.

CSET's Catherine Aiken testified before the National Artificial Intelligence Advisory Committee on measuring progress in U.S. AI research and development.