CSET Executive Director Dr. Dewey Murdick testified before the Senate Homeland Security and Governmental Affairs Emerging Threats Subcommittee on challenges related to emerging technologies and national security.

This explainer defines criteria for effective AI Incident Collection and identifies tradeoffs between potential reporting models: mandatory, voluntary, and citizen reporting.

Translation Snapshots are short posts that highlight related translations produced by CSET’s in-house translation team. Each snapshot identifies relevant translations, provides short summaries, and links to the full translations. Check back regularly for additional Translation Snapshots highlighting our work.

Technical talent is vital to innovation and economic growth, and attracting these highly mobile workers is critical to staying on the cutting-edge of the technological frontier. Conventional wisdom holds that the defense community generally struggles to access this talent pool. This policy brief uses LinkedIn data to track the movement of tech workers between industries and metro areas, with a particular focus on the U.S. Department of Defense, the defense industrial base, and the so-called “Big Tech” companies.

CSET submitted the following comment in response to a Request for Information (RFI) from the National Science Foundation (NSF) about the development of the newly established Technology, Innovation, and Partnerships (TIP) Directorate, in accordance with the CHIPS and Science Act of 2022.

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.

Creating adequate talent pipelines for the cybersecurity workforce is an ongoing priority for the federal government. Understanding the effectiveness of current education initiatives will help policymakers make informed decisions. This report analyzes the National Centers of Academic Excellence in Cyber (NCAE-C), a consortium of institutions designated as centers of excellence by the National Security Agency. It aims to determine how NCAE-C designated institutions fare compared to other schools in graduating students with cyber-related degrees and credentials.

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.

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.