Artificial Intelligence: The Basics & Citations

• Artificial intelligence (AI): the development of machines to accomplish tasks and reproduce thought processes normally seen in humans; this simulation of intelligent behaviour is unique from other automation as it requires the computer to use human reasoning or thinking to perform tasks.
• Machine Learning (ML): a subset of AI; the application of machine learning begins with its ability to learn from data and make decisions without the express intervention of a human. An ML algorithm can observe and detect patterns in data with the goal of being able to predict future decsiions and outcomes from said data. ML learns as it goes.

From: The Rise of AI, ACRL Publications in Librarianship No. 78

AI literacy can be defined as a set of skills that enable a solid understanding of AI through three priority axes:

1. learning about AI
2. learning about how AI works
3. and learning for life with AI (Long & Magerko, 2020; Miao et al., 2021).

The first axis focuses on understanding AI concepts and techniques to enable the recognition of which artifacts/platforms use AI and which do not. The second axis addresses the understanding of how AI works, to effectively interact with it. The third axis seeks to understand how AI can affect our lives, allowing us to critically evaluate its technology.

From: Casal-Otero, L., Catala, A., Fernández-Morante, C. et al. AI literacy in K-12: a systematic literature review. IJ STEM Ed 10, 29 (2023). https://doi.org/10.1186/s40594-023-00418-7