The emergence of artificial intelligence as a general-purpose technology could profoundly transform work across industries, potentially affecting a variety of occupations. While previous technological shifts largely enhanced productivity and wages for white-collar workers but led to displacement pressures for blue-collar workers, AI may significantly disrupt both groups. This report examines the changing landscape of workforce development, highlighting the crucial role of community colleges, alternative career pathways, and AI-enabled training solutions in preparing workers for this transition.

The Emerging Technology Observatory’s AGORA (AI GOvernance and Regulatory Archive) is a living collection of AI-relevant laws, regulations, standards, and other governance documents from the United States and around the world. Updated regularly, AGORA includes summaries, document text, thematic tags, and filters to help users quickly discover and analyze key developments in AI governance.

This report proposes an approach to systematically identify promising research using big data and analyze that research’s potential impact through structured engagements with subject-matter experts. The methodology offers a structured way to proactively monitor the research landscape and inform strategic R&D priorities.

Read our translation of a draft Chinese national standard addressing the safety and security of generative AI services.

Read our translation of a notice from China’s Ministry of Commerce that bans the export of gallium, germanium, antimony, and superhard materials to the United States.

Dr. Steph Batalis and Vikram Venkatram offered the following comment in response to the National Institute of Standards and Technology's request for information on safety considerations for chemical and biological AI models.

Artificial intelligence (AI) tools pose exciting possibilities to advance scientific, biomedical, and public health research. At the same time, these tools have raised concerns about their potential to contribute to biological threats, like those from pathogens and toxins. This report describes pathways that result in biological harm, with or without AI, and a range of governance tools and mitigation measures to address them.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This three-part series uses data from a variety of sources to track how three cloud providers—Amazon, Alphabet, and Microsoft—distribute their financial resources to create and sustain demand for their cloud services. By investing in data centers & workforce training, the large tech platforms of Amazon, Google, and Microsoft draw developers, companies, and governments to their tools & services.

Automation bias is a critical issue for artificial intelligence deployment. It can cause otherwise knowledgeable users to make crucial and even obvious errors. Organizational, technical, and educational leaders can mitigate these biases through training, design, and processes. This paper explores automation bias and ways to mitigate it through three case studies: Tesla’s autopilot incidents, aviation incidents at Boeing and Airbus, and Army and Navy air defense incidents.

Sam Bresnick testified before the Senate Judiciary Subcommittee on Privacy, Technology, and the Law regarding tech companies' ties to China and their implications in a future conflict scenario.