Artificial Intelligence (AI) Help Guide

Generative artificial intelligence, also called gen AI, is one type of artificial intelligence (AI) that creates content—like text, images, videos, audio, or software code—in response to a prompt or request. 

This guide shares information and resources to help the UDC community leverage the benefits of generative AI, recognize its limitations, and develop the skills to use, evaluate, and cite generative AI outputs. Always check with your instructor, supervisor, or publisher before using generative AI in your work.

AI tools are rapidly advancing, and discussions about their legal and ethical implications are evolving just as quickly. We will periodically update this guide to ensure the information shared is accurate and relevant.

Last Updated: March 11, 2025

Watch this webinar presented by Cathy Meals, Assessment and Reference Librarian at UDC Library, to learn more about the basics of generative AI.

Definitions are adapted from Artificial Intelligence Terms: A to Z Glossary (Coursera, 2024).

Artificial Intelligence (AI): Artificial intelligence (AI) refers to the ability of machines or computer systems to perform tasks that normally require human intelligence, such as communication and speech recognition, visual perception, decision-making, and natural language understanding.

Types of AI

• Generative AI (Gen AI): Generative artificial intelligence refers to algorithms and models that generate new content or data, such as text, images, videos, or code. Generative AI systems are trained using large amounts of existing data and information, so they can find and learn patterns for generating new content.


• Chatbot: A chatbot is a software application that imitates human conversation through text or voice commands.


• Machine learning (ML): Machine learning, a subset of AI, involves creating algorithms and models that enable machines to learn from data, forecast trends and behaviors autonomously, and improve their performance over time through experience.


• Natural language processing (NLP): Natural language processing is a type of AI that enables computers to understand spoken and written human language. It encompasses text and speech processing, facilitating features such as text and speech recognition on devices.


• Large language model (LLM): A large language model is a type of machine learning (ML) model that has been trained on large amounts of text data so that it can understand language and generate human-like text. Large language models are the foundation technology upon which many generative AI tools, like ChatGPT and Microsoft CoPilot, are built and specialized.

Using Generative AI Tools

• Prompt: A prompt is a specific task, instruction, or question you give to an AI system to guide its responses or actions.


• Prompt engineering: Prompt engineering is the process of designing and refining prompts to guide AI systems to generate your desired responses or behaviors.


• Hallucination: Hallucinations refer to false or misleading information generated by AI systems and presented as factual. Hallucinations may take the form of inaccuracies, contradictions, or partially or fully fabricated citations.

What happens behind the scenes when you use an AI tool? Check out this brief explanation from Dr. Hal Daumé III, Professor of Computer Science at the University of Maryland and Director for the Institute for Trustworthy AI in Law & Society (TRAILS).

"AI Overview" video by the University of Maryland Libraries and Dr. Hal Daumé III is licensed under a Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) license.

Do you see something missing from this guide? Let us know!

The library is always open to adding missing content to our guides. We are happy to add new links, information, and resources you may be aware of. Please email us at ask@udc.libanswers.com to share any links or information you would like to see us include.