The National Artificial Intelligence Initiative Act (2020) defines AI as:
"A machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. Artificial Intelligence systems use machine and human-based inputs to: (A) perceive real and virtual environments; (B) abstract such perceptions into models through analysis in an automated manner; and (C) use model inference to formulate options for information and action." (Congressional Digest, May 2024, p. 3)
Examples of Artificial Intelligence:
In higher education, it is critical to distinguish between AI and Generative Artificial Intelligence (GAI), as GAI specifically employs algorithms to create content in written, spoken, and visual formats.
Generative AI refers to a category of artificial intelligence systems designed to generate content, including text, images, video, music, computer code, and other forms that closely resemble human-created material. These systems leverage machine learning, particularly deep learning, to identify and replicate patterns, styles, and structures found in the training data.
"A category of software that generates an output after learning common patterns and structures. This category includes not only text but also images and video. Those that focus on text are called Large Language Models (LLMs). LLMs generate text based on billions or even trillions of
pages of text, often described as having been ‘trained on’ various sources, including the internet, published books, academic articles, and other relevant printed and digital material." (AI Hacks for Educators: Practical Tips to Save Time by Using Gen AI, FCTL, Orlando, 2024, p. iii)
Examples of Generative Artificial Intelligence: