Skip to Main Content

AI on Campus: Home

What is Artificial Intelligence?

AI 101

Artificial Intelligence (AI) is a very big umbrella term for a wide range of programs, and the popular definition has only gotten fuzzier as tech companies jump on the hype and make bold claims about the abilities of their products. Encyclopedia Britannica's definition is "the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings ... [especially] systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience." While we are a far cry away from computers that can think like people, there are already very specialized programs that can out-preform human experts in certain tasks, and billions of dollars are being spent on expanding and refining the technology. This Libguide is focused on the basics of how these machines work, the strengths and weaknesses of the most popular programs, and how they can affect our campus.


ChatGPT and Large Language Models 

Large Language Models (LLMs) are some of the most significant AIs to our campus as they include popular text-generating AI like ChatGPT and Google's Bard. They are generative AIs, meaning that they seemingly create new works like stories, letters, realistic conversations, and more when prompted. While this can give the illusion of a computer with a human's creativity and expertise in any subject, these systems actually work like the world's most advanced set of magnetic poetry. LLMs work by being fed and trained on billions of pages of text, including huge swaths of the freely accessible internet, public domain books, etc, and then break them down into strings of symbols called tokens. Once its broken down, a LLM studies what patterns the tokens follow: It might learn that the letters that spell out "Hello, how are you today?" are commonly put together in that order, so when you ask it to write a greeting, it follows that common pattern. By knowing these patterns, programs like ChatGPT can create responses that read like clear English without actually having to understand any of the words; it just has to move letters around to look like what it's read before.

Strong AI vs Weak AI

Just How Powerful is AI?

There are lots of programs being labelled artificial intelligence, but there is a wide gap between sci-fi dreams and the tech being developed today. AI's can be put into two categories: artificial narrow intelligence and artificial general intelligence, or "weak AI" and "strong AI"

Strong AI

Strong AI or artificial generalized intelligence would be a computer program that can take in information, process and learn from that information, and act accordingly without human involvement. It would be a "generalized" intelligence because it could take in lots of different ideas and observations and develop new skills and creative ideas based on them. This is the AI you see in science fiction and sometimes in bold claims by current engineers. However, no AI today has been proven to be anywhere close to this level of autonomy or complexity.

Weak AI

Weak AI is often called "narrow" intelligence because it is about creating a program that can respond to a focused set of inputs and be specialized at producing related outputs. Whenever you hear about AI beating a human grandmaster at chess, that is an example of a program that is extremely skilled at a narrow scope of actions. However this program is built entirely around the task it was designed to excel in: a chessbot only knows the world of chess, is entirely designed for chess, and cannot be given or even tweaked enough to take on new task like driving a car. 

ChatGPT and other LLMs are extremely complex and able to create a wide scope of different text outputs, from poetry to chatbots to short stories, but are still very limited in the types of information they can process and then act on, making them a very powerful form of weak AI.

Warnings for Use

What're the Issues?

Despite their popularity, Large Language Models are still a new technology and suffer from several pitfalls. Here are a few important limitations and warnings to keep in mind before using any form of AI in your college career. 

  • Plagiarism: YES, submitting text or images generated by AI as your own work is plagiarism! Plagiarism is when you submit the work or ideas of someone else as your own or without providing proper credit through citations. Even if you write the prompt for a generative AI, what it generates is the work of the machine and the company that created it, not your own. You also cannot cite those ideas because they are the blended together works of the uncited authors and creators who made the content the AI was trained on. No product of a generative AI should be submitted in any part of an assignment.


  • Unreliable as a fact search: If you try to use an LLM like a search engine and prompt it to give you a fact or explain an idea, it will produce a response based on the related documents it has been trained on. However, the program is only rearranging words and does not have the ability to understand the words or fact check itself. As such, anything it produces has a chance of being incorrect or carry the biases of the works it was trained on, especially for nuanced or complex topics, meaning you will have to research the fact on your own anyway to confirm what it generates.


  • Confabulations: a confabulation is when an AI generates something that seems realistic but is actually false. These often develop when the user is asking for a list of resources, citations, a reference list, etc. Each piece of the response in a confabulation make sense but together make a false statement: if you were to ask an AI to cite a psychology article, it might generate text that includes the name of a real researcher, a title that matches the topic requested, and a scholarly journal that it could feasibly have been published in, all in the proper APA formatting, but that author has never actually written anything by that title for that journal. These are clear giveaways of AI generated content and can lead to the spread of misinformation


AI in the News

Loading ...

Good Uses for LLMs

How Can It be Helpful?

The best uses of AI and LLMs as a student are as productivity tools, not as writing replacements. Here are some ways a program help inspire and streamline your own work.

  • Brainstorming: A great use of AI is to help you brainstorm new ideas, like what topics you could use for an essay, a short story prompt to inspire your writing, or for it to play devils' advocate as you prep for a debate. What it generates should only be taken as jumping off points for your own research and writing, but sometimes a kick-start is what you need to overcome a blank page.

  • Making study materials: A LLM can be used to produce things like a study schedule to break up the amount of work you have to do over the time you have, or turn your notes into flash cards or multiple choice practice tests. Experiment and see what other useful tools it can help you make!


  • Simplifying readings: You can prompt an AI with a phrase like "Simplify the following text: [insert text here]" with a copy and pasted section of a reading to have the machine break it down for easier and faster reading.

Digital Media Librarian

Profile Photo
Aidan Sonia-Bolduc
Mabee-Simpson Library, Room #203



2300 HIGHLAND ROAD • BATESVILLE, ARKANSAS 72501 • PHONE: (870-307-7205) • FAX: (870) 307-7279