publication
The Global AI Vibrancy Tool
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: 3/26/2026
The source text provided is raw PDF binary/stream data that cannot be parsed to verify any of the structured data claims. While the URL in the record suggests this is indeed a Stanford HAI document from November 2024, the actual source text excerpt contains only PDF object definitions and compressed streams with no human-readable content that would confirm or contradict the title, authors, publication date, or other metadata. To verify this record, a readable version of the PDF content (title page, metadata, etc.) would be required.
Debug info
Thing ID: XWEqRQOscN
Source Table: publications
Source ID: XWEqRQOscN