Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the second in a series of Snapshots exploring CSET’s Private-sector AI-Related Activity Tracker (PARAT). Check in every two weeks to see our newest Snapshot, and explore PARAT, which collects data related to companies’ AI research and development to inform analysis of the global AI sector.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the first in a series of Snapshots exploring CSET’s Private-sector AI-Related Activity Tracker (PARAT). Check in every two weeks to see our newest Snapshot, and explore PARAT, which collects data related to companies’ AI research and development to inform analysis of the global AI sector.

​​This Classifying AI Systems Interactive presents several AI system classification frameworks developed to distill AI systems into concise, comparable and policy-relevant dimensions. It provides key takeaways and framework-specific results from CSET’s analysis of more than 1,800 system classifications done by survey respondents using the frameworks. You can explore the frameworks and example AI systems used in the survey, and even take the survey.

CSET's Emily Weinstein and Ainikki Riikonen of the Center for a New American Security submitted this comment to the Office of Science and Technology Policy in response to a request for recommendations on securing U.S. government research and development against foreign government interference and exploitation.

Created through a joint partnership between CSET and the AI Education Project, the AI Education Catalog aims to raise awareness of the AI-related programs available to students and educators, as well as to help inform AI education and workforce policy.

CSET submitted this comment to the Office of Science and Technology Policy and the National Science Foundation to support the work of the National Artificial Intelligence Research Resource (NAIRR) Task Force to develop an implementation roadmap that would provide AI researchers and students across scientific disciplines access to computational resources, high-quality data, educational tools, and user support.

CSET Senior Fellow Anna Puglisi testified before the Senate Select Committee on Intelligence on "Beijing's Long Arm: Threats to U.S. National Security." She offered recommendations to counter China's S&T collection efforts.

CSET Research Analyst Will Hunt testified before the Strategic Technologies and Advanced Research (STAR) Subcommittee on "Microelectronics: Levers for Promoting Security and Innovation." He offered recommendations to advance the U.S.' semiconductor industry.

Growing popular and industry interest in high-performing natural language generation models has led to concerns that such models could be used to generate automated disinformation at scale. This report examines the capabilities of GPT-3--a cutting-edge AI system that writes text--to analyze its potential misuse for disinformation. A model like GPT-3 may be able to help disinformation actors substantially reduce the work necessary to write disinformation while expanding its reach and potentially also its effectiveness.

The advantages of nations depend in part on their access to new inventions—and modern applications of artificial intelligence can help accelerate the creation of new inventions in the years ahead. This data brief is a first step toward understanding how modern AI and machine learning have begun accelerating growth across a wide array of science and engineering disciplines in recent years.