Training Data Sources: Generative AI models are trained on vast amounts of internet data which contains both accurate and inaccurate information, as well as biases (Weise & Metz, 2023).

Limitations of Generative Models: Their goal is to generate plausible content, not to verify its truth. As a result, they might produce content that sounds plausible but is inaccurate (O’Brien, 2023).

Inherent Challenges in AI Design: AI tools are not designed to differentiate between what’s true and what’s not true. Even if a tool is given only accurate data, it can still generate , new, potentially inaccurate content (Weise & Metz, 2023).

Explanations and citations from When AI Gets It Wrong: Addressing AI Hallucinations and Bias. (2024). MIT Sloan Teaching & Learning Technologies. Retrieved 2024, July 23 from https://mitsloanedtech.mit.edu/ai/basics/addressing-ai-hallucinations-and-bias/

Flowchart from Artificial Intelligence Writing Tools (n.d.) Simon Fraser University Centre for Educational Excellence. Retrieved 2024, July 23. from https://www.sfu.ca/cee/teaching-resources/teaching-strategies/AI-writing-tools.html.

Machine Learning is “a branch of artificial intelligence (AI) and computer science that focuses on the using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy.” What is Machine Learning (ML)? (n.d.). IBM. Retrieved 2024, July 22 from https://www.ibm.com/topics/machine-learning.

Large language models (LLMs) “are a category of foundation models trained on immense amounts of data making them capable of understanding and generating natural language and other types of content to perform a wide range of tasks.” What are Large Language Models (LLM)? (n.d.). IBM. Retrieved 2024, July 22 from  https://www.ibm.com/topics/large-language-models.

Generative Artificial Intelligence is “a machine-learning model that is trained to create new data, rather than making a prediction about a specific dataset. A generative AI system is one that learns to generate more objects that look like the data it was trained on.” Zewe, A. (2023, November 9). Explained: Generative AI. MIT News. Retrieved 2024, July 22 from  https://news.mit.edu/2023/explained-generative-ai-1109.

Prompts are “the information, sentences, or questions that you enter into a Generative AI tool…” Getting started with prompts for text-based Generative AI tools. (2023, August 30). Harvard University Information Technology. Retrieved 2024, July 22 from https://huit.harvard.edu/news/ai-prompts.

Hallucination is a generated, “fabricated information in response to a user’s prompt, but presents it as if it’s factual and correct.” DeVon, C. (2023, December 22). AI chatbots can ‘hallucinate’ and make things up—why it happens and how to spot it. CNBC. Retrieved 2024, July 22 from  https://www.cnbc.com/2023/12/22/why-ai-chatbots-hallucinate.html.