Artificial Intelligence Index Report 2024

The 2024 AI Index broadens its scope to more extensively cover essential trends such as technical advancements in AI, public perceptions of the technology, and the geopolitical dynamics surrounding its development. The 2024 edition introduces new estimates on AI training costs, detailed analyses of the responsible AI landscape, and an entirely new chapter dedicated to AI’s impact on science and medicine.

The Foundation Model Transparency Index (October 2023)

The Foundation Model Transparency Index is a new project that assesses the transparency of foundation model developers. The Index is designed around 100 transparency indicators, which codify transparency for foundation models, the resources required to build them, and their use in the AI supply chain. The 2023 Index scores 10 leading developers providing a snapshot of AI transparency.

Artificial Intelligence Index Report 2023

The 2023 AI Index report introduces more original data than any previous edition, including a new chapter on AI public opinion, a more thorough technical performance chapter, original analysis about large language and multimodal models, detailed trends in global AI legislation records, a study of the environmental impact of AI systems, and more.

A Policy Primer and Roadmap on AI Worker Surveillance and Productivity Scoring Tools

The paper provides stakeholders (policymakers, advocates, workers, and unions) with insights into AI-powered algorithmic worker surveillance and productivity-scoring tools. Topics explored include the assumptions embedded in workplace surveillance and scoring technologies, how employers use these systems in ways that affect human rights, and actionable recommendations for federal agencies and labour unions.

Artificial Intelligence Index Report 2022

The 2022 edition of Stanford’s annual AI Index includes an expanded technical performance chapter, a new survey of robotics researchers around the world, data on global AI legislation records in 25 countries, and a new chapter with an in-depth analysis of technical AI ethics metrics.