{"id":941334,"date":"2023-05-17T12:12:35","date_gmt":"2023-05-17T19:12:35","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2023-07-28T14:11:10","modified_gmt":"2023-07-28T21:11:10","slug":"responsible-ai-maturity-model","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/responsible-ai-maturity-model\/","title":{"rendered":"Responsible AI Maturity Model"},"content":{"rendered":"

The Responsible AI Maturity Model (RAI MM) is a framework to help organizations identify their current and desired levels of RAI maturity.<\/strong><\/p>\n

Download executive summary & FAQ<\/a><\/p>\n

The RAI MM contains 24 empirically derived dimensions that are key to an organization\u2019s RAI maturity. The dimensions and their levels are based on interviews and focus groups with over 90 RAI specialists (e.g., RAI champs, MSR experts) and AI practitioners (e.g., user experience (UX) researchers, UX designers, data scientists). Each dimension has five levels, going from low (Level 1: Latent) to high (Level 5: Leading) maturity. The dimensions are organized into three main categories:<\/p>\n