Real-world harms caused by the use of AI technologies are widespread. Tracking and analyzing them improves our understanding of the variety of harms and the circumstances that lead to their occurrence once AI systems are deployed. This report presents a standardized conceptual framework for defining, tracking, classifying, and understanding harms caused by AI. It lays out the key elements required for the identification of AI harm, their basic relational structure, and definitions without imposing a single interpretation of AI harm. The brief concludes with an example of how to apply and customize the framework while keeping its modular structure.

On July 21, the White House announced voluntary commitments from seven AI firms to ensure safe, secure, and transparent AI. CSET’s research provides important context to this discussion.

With the rapid integration of AI into our daily lives, we must all learn when and whether to trust the technology, understand its capabilities and limitations, and adapt as these systems — and our functional relationships with them — evolve.

In an article published by The Washington Post that discusses the competition between the United States and China in the field of artificial intelligence and the differing approaches of regulation in both countries, CSET's Helen Toner provided her expert insight.

In an article published by The New York Times that discusses the increasing use of artificial intelligence in political campaigns and the concerns it raises regarding disinformation and manipulation, CSET's Josh A. Goldstein provides his expert insight.

CSET's AI Assessment team provides a template that helps organizations create profiles to guide the management and deployment of AI systems in line with NIST's AI Risk Management Framework.

In a weekly digest published by Foreign Policy, CSET's Emily S. Weinstein offered her expert analysis on a recent study conducted by the Australian Strategic Policy Institute.

Process frameworks provide a blueprint for organizations implementing responsible artificial intelligence (AI), but the sheer number of frameworks, along with their loosely specified audiences, can make it difficult for organizations to select ones that meet their needs. This report presents a matrix that organizes approximately 40 public process frameworks according to their areas of focus and the teams that can use them. Ultimately, the matrix helps organizations select the right resources for implementing responsible AI.

A report by CSET's Josh Goldstein, Micah Musser, and CSET alumna Katerina Sedova in collaboration with OpenAI and Stanford Internet Observatory was cited in an article published by Forbes.

In an op-ed published in TIME, CSET's Helen Toner discusses the challenges of understanding and interacting with chatbots powered by large language models, a form of artificial intelligence.