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.

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.

The Chinese Academy of Sciences is among the most important S&T organizations in the world and plays a key role in advancing Beijing’s S&T objectives. This report provides an in-depth look into the organization and its various functions within China’s S&T ecosystem, including advancing S&T research, fostering the commercialization of critical and emerging technologies, and contributing to S&T policymaking.

How to govern artificial intelligence is a concern that is rightfully top of mind for lawmakers and policymakers.To govern AI effectively, regulators must 1) know the terrain of AI risk and harm by tracking incidents and collecting data; 2) develop their own AI literacy and build better public understanding of the benefits and risks; and 3) preserve adaptability and agility by developing policies that can be updated as AI evolves.

China’s leadership believes that artificial intelligence will play a central role in future wars. However, the author's comprehensive review of dozens of Chinese-language journal articles about AI and warfare reveals that Chinese defense experts claim that Beijing is facing several technological challenges that may hinder its ability to capitalize on the advantages provided by military AI. This report outlines these perceived barriers and identifies several technologies that Chinese experts believe may help the country develop and deploy military AI-enabled systems.

In February 2024, CSET introduced its new cybersecurity jobs dataset, a novel resource comprising ~1.4 million LinkedIn profiles of current U.S. cybersecurity workers. This data snapshot uses the dataset to identify top-producing institutions of cybersecurity talent.

The celebrated return to China of its overseas scientists, as evidenced in the recent case of physicist Gao Huajian, is typically cited as a loss to the United States. This report argues a contrarian view that the benefits equation is far more complicated. PRC programs that channel diaspora achievements “back” to China and the inclination of many scientists to work in familiar venues blur the distinction between returning to China and staying in place.

China’s brain-computer interface research has two dimensions. Besides its usual applications in neuropathology, China is extending the benefits of BCI to the general population, aiming at enhanced cognition and a “merger” of natural and artificial intelligence. This report, authored in collaboration with researchers from the Department of War Studies at King’s College London uses bibliometric analysis and expert assessment of technical documents to evaluate China’s BCI, and conclude that the research is on track to achieve its targets.

This data snapshot is the first in a series on CSET’s cybersecurity jobs data, a new dataset created by classifying data from 513 million LinkedIn user profiles. Here, we offer an overview of its creation and explore some use cases for analysis.

Understanding the current state of the AI workforce is essential as the U.S. prepares an AI-ready workforce. This Data Snapshot provides the latest estimates for the AI workforce by using data from the U.S. Census Bureau’s 2022 American Community Survey. It also highlights the changes in size and composition of the AI workforce since our earlier analysis of data from 2018.