The intersection between AI literacy and media and information literacy scales - A bibliometric study and conceptual analysis

Abstract

This study conducted a bibliometric and thematic analysis of 9,624 publications on media and information literacy (MIL) and artificial intelligence literacy (AIL) (2004-2024) to investigate the global scholarly landscape, identify commonalities and distinctions between AIL and MIL, and explore the influence of AIL research on MIL metrics.

Findings indicate a burgeoning interest in both fields, with a notable increase in publications over time. While MIL research predominantly consists of peer-reviewed articles, conference papers dominate AIL, reflecting its nascent nature. The United States and Spain lead in contributions, with English as the dominant language, and the dominance of educational and pedagogical themes (59%) and the media and communication research (21.5%).

A bibliometric analysis of scientific publications indexed in the Web of Science (WoS) and Google Scholar (GS) databases revealed five dominant research themes: digital and information literacy, AI and data literacy, critical literacy and curriculum, media literacy and education, and health literacy. While initial interests were directed towards media literacy and health literacy, recent attention has shifted towards AIL. The COVID-19 pandemic notably renewed interest in digital health literacy as a critical research area during and after the crisis.

A comparative and thematic analysis of metrics for MIL and AIL identifies shared dimensions in usage and evaluation. However, AIL uniquely prioritizes ethical considerations and an understanding of machine learning principles. Contemporary MIL metrics are undergoing a transformation to incorporate awareness of information ecosystems, algorithmic bias, and privacy concerns. To address the rapid pace of technological change, interdisciplinary research is essential for the development of comprehensive AIL metrics that extend existing MIL frameworks.