Human-AI Collaboration Framework & Case Studies
Case Studies
Human-AI Collaboration Framework & Case Studies
This report includes a framework to help users consider key aspects of human-AI collaboration technologies, and case studies which illustrate real world applications.
learn moreHuman-AI Collaboration
Trust Literature Review -
Key Insights and Bibliography
Report
Human-AI Collaboration
Trust Literature Review -
Key Insights and Bibliography
This project highlights key themes and high-level insights from a review of multidisciplinary literature on AI, humans and trust, and includes a thematically tagged bibliography of 78 articles.
learn moreVisa Laws, Policies, and Practices: Recommendations for Accelerating the Mobility of Global AI/ML Talent
Policy paper
Visa Laws, Policies, and Practices: Recommendations for Accelerating the Mobility of Global AI/ML Talent
PAI’s policy paper offers recommendations that will enable multidisciplinary AI/ML experts to benefit from the diverse perspectives offered by the global AI/ML community.
learn moreABOUT ML - Annotation and Benchmarking on Understanding and Transparency of Machine learning Lifecycles
Ongoing Project
ABOUT ML - Annotation and Benchmarking on Understanding and Transparency of Machine learning Lifecycles
This multi-year, iterative, multistakeholder effort works towards establishing evidence-based ML transparency best practices throughout the ML system lifecycle.
learn moreAI, Labor, and the Economy Case Study Compendium
Case study
AI, Labor, and the Economy Case Study Compendium
These case studies examine the labor implications and productivity impacts of AI implementation across different applications, geographies, and sectors.
learn moreReport on Algorithmic Risk Assessment Tools in the U.S. Criminal Justice System
Report
Report on Algorithmic Risk Assessment Tools in the U.S. Criminal Justice System
This report documents the serious shortcomings of algorithmic risk assessment tools in the U.S. criminal justice system, and includes ten requirements that jurisdictions should weigh heavily prior to the use of these tools.
learn more