AI metrics and policymaking: assumptions and challenges in the shaping of AI

AI and Society 40 (6):4655-4670 (2025)
  Copy   BIBTEX

Abstract

This paper explores the interplay between AI metrics and policymaking by examining the conceptual and methodological frameworks of global AI metrics and their alignment with National Artificial Intelligence Strategies (NAIS). Through topic modeling and qualitative content analysis, key thematic areas in NAIS are identified. The findings suggest a misalignment between the technical and economic focus of global AI metrics and the broader societal and ethical priorities emphasized in NAIS. This highlights the need to recalibrate AI evaluation frameworks to include ethical and other social considerations, aligning AI advancements with the United Nations Sustainable Development Goals (SDGs) for an inclusive, ethical, and sustainable future.

Other Versions

No versions found

Links

PhilArchive

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Analytics

Added to PP
2025-02-13

Downloads
29 (#1,622,494)

6 months
15 (#807,222)

Historical graph of downloads
How can I increase my downloads?