Foundation Model Transparency Reports
To codify how foundation model developers should provide transparency, we propose Foundation Model Transparency Reports, drawing upon the transparency reporting practices in social media. While external documentation of societal harms prompted social media transparency reports, our objective is to institutionalize transparency reporting for foundation models while the industry is still nascent.
The 2024 Foundation Model Transparency Index
To understand how the AI transparency landscape has changed, the 2024 Foundation Model Transparency Index conducts a follow up 6 months following the initial launch, scoring developers on the same 100 indicators. Developers now score 58 out of 100 on average, a 21 point improvement over the first version.
Bias in Text Embedding Models
Text embedding is becoming an increasingly popular AI methodology, especially among businesses, yet the potential of text embedding models to be biased is not well understood. This paper examines the degree to which a selection of popular text embedding models are biased, particularly along gendered dimensions.
How Much Does It Cost to Train Frontier AI Models?
The cost of training frontier AI models has grown by a factor of 2 to 3x per year for the past eight years, suggesting that the largest models will cost over a billion dollars by 2027.
The Rising Costs of Training Frontier AI Models
The costs of training frontier AI models have grown dramatically in recent years, but there is limited public data on the magnitude and growth of these expenses. This paper develops one of the first detailed cost models to address this gap, estimating training costs using three approaches that account for hardware, energy, cloud rental, and staff expenses.
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.
Adjudication of Artificial Intelligence and Automated Decision-Making Cases in Europe and the USA
This article contributes to the understanding of how the legal system is reacting to the ongoing uptake of AI and the disputes or right infringements this uptake creates. Select legal cases regarding the use of AI technology for automated decisions are reviewed, with a focus on filings in Europe and the USA.
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.