AI literacy extends beyond technical proficiency to encompass ethical considerations, societal impacts, and practical applications across diverse educational contexts.

Objective: The main goal of this systematic literature review was to evaluate the current state of literature on Artificial Intelligence (AI) literacy, identify thematic and recent research trends, and explore the evolving landscape of AI literacy in education and beyond.

Methods: The researchers conducted a systematic literature review following the PRISMA guidelines. They began with 632 records from databases including Web of Science, SCOPUS, ERIC, and IEEE Xplore, which was narrowed down to 87 high-quality studies after applying rigorous inclusion and exclusion criteria. Two independent researchers analyzed the selected papers using both quantitative (bibliometric network analysis) and qualitative (thematic analysis) approaches. The data extraction focused on publication trends, geographical distribution, target audiences, definitions of AI literacy, and key thematic areas.

Key Findings:

• AI literacy research has shown significant growth, particularly in 2022-2023, with China (31%) and the US (23%) leading global contributions.
• The research revealed that AI literacy extends beyond technical skills to include ethical considerations, societal impacts, and practical applications.
• Ten primary themes emerged from the analysis: developing AI literacy curriculum and interventions; AI literacy models and frameworks; ethical and social implications of AI; AI literacy in K-12 education; AI literacy assessment tools; integration of AI in education and workplaces; family and informal learning environments; AI literacy for early childhood education; AI in healthcare and medical education; and AI and digital literacy.
• Definitions of AI literacy have evolved from focusing primarily on technical proficiency to more holistic approaches that incorporate ethical, social, and cultural dimensions.
• Two main frameworks for AI literacy were identified: technical frameworks aligned with STEM education, and holistic frameworks better suited to interdisciplinary approaches.
• The study identified the importance of adapting AI literacy education to different age groups and learning contexts.

Implications: The findings contribute significantly to the field of AI in education by providing a comprehensive understanding of how AI literacy is conceptualized and implemented across various educational contexts. The study advocates for an adaptable, comprehensive educational paradigm that incorporates AI literacy, reflecting its diverse interpretations and the dynamic nature of AI. It emphasizes the need for interdisciplinary collaboration in developing AI literacy programs to equip future generations with the knowledge, skills, and ethical discernment needed to navigate an AI-driven world.

Limitations: The study acknowledges several limitations. The research primarily represents contributions from China and the US, potentially missing diverse cultural perspectives from underrepresented regions like Africa and Latin America. The methodological categorization of the selected studies was not explicitly coded, which might have provided additional insights into research approaches. Additionally, the focus on English and Italian language publications may have excluded valuable research published in other languages.

Future Directions: The study suggests several avenues for future research:

• Exploring how AI literacy can be effectively tailored to different age groups and learning contexts
• Understanding the role of cultural context in shaping AI literacy education
• Conducting longitudinal studies to examine the long-term impact of AI literacy on career development, civic engagement, and societal attitudes toward AI technologies
• Developing standardized assessment tools that measure both technical skills and ethical/critical thinking aspects of AI literacy
• Incorporating systematic classification of methodologies in future research
• Expanding research to include underrepresented regions, such as Africa and Latin America

Title and Authors: "Towards an AI-Literate Future: A Systematic Literature Review Exploring Education, Ethics, and Applications" by Gabriele Biagini.

Published On: February 22, 2025 (accepted date), with online publication on March 12, 2025.

Published By: International Journal of Artificial Intelligence in Education, through Springer.

The study provides a panoramic view of the evolving AI literacy landscape, highlighting the transformation from a narrow technical focus to a more comprehensive understanding that encompasses ethical, social, and practical dimensions. The author emphasizes that AI literacy should be considered as important as traditional literacy skills like reading and writing due to AI's growing influence across various sectors.

The author identifies two distinct approaches to AI literacy: technical frameworks centered on computational skills and machine learning concepts, and holistic frameworks that integrate ethical, social, and cultural considerations. This distinction is crucial for curriculum development, as it informs how AI literacy should be taught across different educational levels.

A significant contribution of this study is the identification of a gap in practical guidance on teaching AI ethics. While there is widespread recognition of the importance of ethical considerations, many curricula still focus primarily on technical skills, with less emphasis on how to integrate ethics into the classroom. This gap highlights the need for further research and development of pedagogical tools to address ethical questions alongside technical training.

The geographical analysis indicates that countries with robust AI policies, such as China and the US, are leading in AI literacy research. However, the study calls for more research in underrepresented regions to ensure AI literacy education is contextualized for diverse cultural and educational settings.

Overall, this systematic review serves as a foundational resource for educators, researchers, and policymakers seeking to understand and implement AI literacy programs, emphasizing that such initiatives should prepare individuals not only to use AI technologies but also to understand and critique their broader implications in an increasingly AI-driven world.