Metadata
| Source Table | publications |
| Source ID | XWEqRQOscN |
| Description | Loredana Fattorini, Nestor Maslej, Ray Perrault, Vanessa Parli, John Etchemendy, Yoav Shoham, 2024-11 |
| Source URL | hai.stanford.edu/assets/files/global_ai_vibrancy_tool_paper_november2024.pdf |
| Parent | Stanford Institute for Human-Centered Artificial Intelligence (HAI) |
| Children | — |
| Created | Mar 23, 2026, 2:42 PM |
| Updated | Mar 23, 2026, 2:42 PM |
| Synced | Mar 23, 2026, 2:42 PM |
Record Data
id | XWEqRQOscN |
entityId | Stanford Institute for Human-Centered Artificial Intelligence (HAI)(organization) |
entityDisplayName | — |
resourceId | — |
title | The Global AI Vibrancy Tool |
authors | Loredana Fattorini, Nestor Maslej, Ray Perrault, Vanessa Parli, John Etchemendy, Yoav Shoham |
url | hai.stanford.edu/assets/files/global_ai_vibrancy_tool_paper_november2024.pdf |
venue | — |
publishedDate | 2024-11 |
publicationType | report |
citationCount | — |
isFlagship | No |
abstract | — |
source | hai.stanford.edu/assets/files/global_ai_vibrancy_tool_paper_november2024.pdf |
notes | Ranks 36 countries across 42 AI indicators |
Source Check Verdicts
unverifiable95% confidence
Last checked: 4/29/2026
1 → unverifiable
Debug info
Thing ID: XWEqRQOscN
Source Table: publications
Source ID: XWEqRQOscN
Parent Thing ID: sid_YPE80Sx2VA