Artificial intelligence (AI) is technology that learns how to learn, and then applies that knowledge to a specific task or purpose.
Generative artificial intelligence is technology that learns to recognize patterns in content used in its training (text, images, data, etc.) and then produces content that mimics those patterns.
Large Language Models (LLMs) are a type of generative AI that can understand and produce natural-sounding paragraphs of text. LLMs use probability to predict the next word in a sentence as they produce text, but they do not "understand" what they are saying the way a human would.
Despite its name, AI (Artificial Intelligence) does not think or feel or have intentions, so it cannot lie the way a human might. However, AI is capable of producing false, misleading, or inaccurate information.
Generative AI such as Large Language Models frequently "hallucinate" false information that cannot be found in or explained by the information used to train the AI tool. Examples of AI hallucinations include fake people and data, and citations for sources that do not exist. Information that AI presents as fact is not necessarily accurate!
AI tools reflect the bias of the information used in their training materials. For example, if an AI image generator is trained on pictures of doctors that are mostly white men, it will be likely to produce an image of a white male doctor when prompted for a picture of a doctor, even when the prompt does not specify race or gender.
You can use the same fact checking and source selection strategies for AI that you use for human-created sources. For example:
The links below provide some information on citing text or images generated by AI. Ask a librarian for help citing any AI sources you use in the citation style required by your assignment.
The following video tutorial explores academic integrity, including: seeking information from a range of sources; looking at issues from a range of perspectives; acknowledging that information has value; and taking ownership of your own learning by accessing and crediting the ideas of others appropriately (from off campus you will need to log in using your Pipeline username and password):