In a report for the Observer Research Foundation, Research Analyst Husan Chahal writes about the ethics of artificial intelligence and how the multitude of efforts across such a diverse group of stakeholders reflects the need for guidance in AI development.

Digital technology, the defining innovation of the last half century, has deep and unaddressed insecurities at its core. This paper, authored by two prominent technologists and strategic thinkers, argues that a new form of “digital environmentalism”—marked by a re-evaluation of our relationship to technology, growth, and innovation—is the only way to fix such insecurities, and to bring meaningful change to the digital world.

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 submitted the following comment in response to the National Institute for Standards and Technology's second draft of its AI Risk Management Framework.

In a study for Harvard's Misinformation Review, Research Fellow Josh Goldstein looks at how tactics used in political influence operations are used for commercial purposes.

A CSET report shares insights on community college-level artificial intelligence workforce training and where further investment is needed.

Kathleen Curlee is a Research Analyst at CSET focusing on the national security applications of artificial intelligence.

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 an opinion piece for the Council on Foreign Relations, Research Fellow Diana Gehlhaus discussed why the United States needs to make AI education a priority.