Artificial intelligence and machine learning (AI/ML) is a set of technologies that includes automated systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, and decision-making. AI/ML has promising applications in health care, including drug development. For example, it may have the potential to help identify new treatments, reduce failure rates in clinical trials, and generally result in a more efficient and effective drug development process. However, applying AI/ML technologies within the health care system also raises ethical, legal, economic, and social questions. GAO was asked to conduct a technology assessment on the use of AI technologies in drug development with an emphasis on foresight and policy implications. This report discusses (1) current and emerging AI technologies available for drug development and their potential benefits; (2) challenges to the development and adoption of these technologies; and (3) policy options to address challenges to the use of machine learning in drug development. -- from Foreword

Report on an economic study related to artificial intelligence: "This report is intended to highlight the economics behind AI-driven technological change with a particular focus on the institutional and policy decisions that will shape its future impact on the workforce. [...] Parts I and II of this report introduce AI and document its widespread adoption in the European Union and the United States; part III focuses on AI’s impact on labor; part IV contains case studies on hiring and logistics; part V concludes" (p. 3).

This report discusses ways that artificial intelligence could potentially automate manual tasks and relieve human labor. However, the authors recognize this shift would displace the livelihoods of millions of Americans. The pros and cons of artificial intelligence on the economy is discussed.

This report provides guidance to assist transportation agencies with better preparation for the potential impacts of AI on operational activities, resources, system needs, and decisionmaking.

This report summarizes the technological developments in AI and generative AI, explains the FTC's jurisdictional interest in AI, then summarizes and memorializes information provided by participants in a roundtable. It is intended as a useful resource for the legal, policy, and academic communities who are considering the implications of generative AI.

In this report, GAO reviewed the implementation of AI at major federal agencies. It focused on agencies with government-wide roles in AI implementation as well as agencies with individual responsibilities for AI implementation.

In this report, GAO reviewed the implementation of AI at major federal agencies. It focused on agencies with government-wide roles in AI implementation as well as agencies with individual responsibilities for AI implementation.

This report reviewed the use of machine learning to model severe storms, hurricanes, floods, and wildfires across development and operational stages. The authors identified policy options in this report.