Research Guides: Artificial Intelligence: Introduction

Things Change ...Quickly!

Before we begin... Generative artificial intelligence is fundamentally changing how we find, create, and share information. These AI tools are evolving quickly, with new details emerging daily regarding their use, regulation, and societal impact. While efforts will be made to maintain the relevance and currency of this guide, it's important to acknowledge that the information contained within may become outdated before we can update it. The Hayden Memorial Library at Citrus College does not endorse any specific AI technologies, and advises students to exercise discretion regarding the disclosure of personal information while using such tools.

And another thing...

Know the policy for your courses... Until Citrus College comes up with comprehensive guidelines regarding student use of AI tools, your best bet for knowing whether it's acceptable to use AI for college (and how to cite it) is to simply ask your instructor. Many instructors are now including AI guidelines in their syllabus, but if you don't see it there, you can always ask your instructor directly.

A Very Brief Introduction

Generative artificial intelligence is a complicated set of technologies. While it's not necessary to have a deep knowledge of how these technologies work to use AI tools, it's helpful to have a basic understanding of some fundamental concepts, especially for being able to critically evaluate their output.

Generative AI refers to technology that can create new content, such as text, images, code, audio, or video.
Put very simply, AI text generators work by predicting the next word in a sequence. They do not "understand" your questions in the way that another person would.
AI text generators, such as ChatGPT, are trained on a large amount of text scraped from the Internet. This training is supplemented by annotation and feedback testing done by humans. AI image generators, such as Midjourney and DALL-E are trained in a similar way.
With some exceptions, we don't have a lot of information about how the models that drive these tools were trained. That means that, in most cases, users have no way of knowing what information an AI tool has had access to.
Many other applications are being developed that make use of generative AI technology. In fact, AI technology is already at work in many of the tools that you use.

Adapted from JISC. Generative AI - a Primer

Common terms and definitions

Common terms used in this guide:

Artificial Intelligence (AI): "The capacity of computers or other machines to exhibit or simulate intelligent behavior." (Oxford English Dictionary, n.d.)

Generative AI (Gen-AI): A type of AI technology that generates content such as text, images, audio, and video. Also sometimes referred to as a generator.

Large Language Model (LLM): A complex model trained on vast amounts of data that generates language that resembles human-generated language. Open AI's GPT series, Google's Gemini, and Meta's LLaMA are examples of LLMs.

Chatbot: A computer program that uses an LLM to simulate a conversation with human users, typically through typed text in a software application.

Algorithm: A set of instructions or rules for performing a computation. Developers typically design algorithms used in AI to progressively iterate themselves, which we can consider a form of machine learning.

Training: The process of supplying algorithms with large data sets, and then "teaching" them to develop progressively sophisticated outputs for their intended purpose.

Definitions are adapted from the "Defining AI and Chatbots" page of the Artificial Intelligence Teaching Guide, Stanford Teaching Commons.

Acknowledgement

This page was adapted from Generative AI for Students at Los Angeles Valley Community College