"AI literacy goes beyond understanding AI tools; it equips individuals to critically evaluate, ethically navigate, and practically apply AI in real-world scenarios; [it is] is the ability to understand, use, and think critically about AI technologies and their impact on society, ethics, and everyday life. (…)
This broad definition, provided by Leo S.Lo in his article [Lo, L. (2025). AI Literacy: A Guide for Academic Libraries. College &Research Libraries News, 86(3), 120-122] encompasses several interconnected components, each essential for developing a well-rounded understanding of AI. Lo provides a guide to AI literacy that addresses technical, ethical, critical, and societal dimensions of AI.
Several AI Literacy Frameworks are now available (See below). They provide a roadmap for individuals to navigate the increasingly AI-driven world, ensuring they can critically evaluate AI outputs, understand its limitations, and use it effectively and ethically.
An AI literacy framework equips individuals with the knowledge and skills to understand, evaluate, and use AI systems and tools ethically and effectively. It emphasizes critical thinking, responsible AI usage, and awareness of potential biases and limitations.
Key Components of an AI Literacy Framework:
Understanding AI Basics: This includes grasping fundamental concepts like machine learning, neural networks, and different types of AI (e.g., narrow AI, general AI).
Evaluating AI Systems: Critically assessing the strengths and weaknesses of AI systems, including their potential biases, limitations, and ethical implications.
Using AI Responsibly: Applying AI tools and systems in a way that is ethical, safe, and beneficial, while being mindful of potential misuse.
Ethical Considerations: Understanding the ethical implications of AI, such as fairness, accountability, and transparency.
AI Pedagogy: Learning how to effectively use AI in educational settings to enhance teaching and learning.
Self-Reflection and Continuous Learning: Recognizing the need for continuous learning and self-reflection to stay current with the evolving landscape of AI technologies.
Human-Centered Approach: Emphasizing the importance of human skills like critical thinking, creativity, and emotional intelligence when interacting with AI.