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Artificial Intelligence Literacy

Guide to Artificial Intelligence (AI) literacy and AI use in research.

Types of AI

There are two ways of categorizing artificial intelligence: by what they are capable of and by their functionality.


  1. Artificial Narrow Intelligence (weak AI)
    • These AI are trained to perform specific tasks. While they are capable of doing these tasks much quicker than humans, they cannot perform anything else.
  2. General AI (strong AI)
    • Artificial General Intelligence (AGI) that is able to learn and adapt without the need of new training of the model, much like a human would.
  3. Super AI
    • Artificial Superintelligence is theoretical, often seen in science fiction. This type of AI would be able to feel, think, learn, make judgements quicker than humans due to increased cognitive ability. They may even feel emotions and possess beliefs as a human would.


  1. Reactive Machine AI
    • As a weak AI, these perform specific tasks but have no memory for previous outcomes, so they can only react in the present. IBM's Deep Blue, for example, is a chess supercomputer AI that predicts the outcomes of moves based on the board at any given time.
  2. Limited Memory AI
    • This form of AI has the ability to use past and present data for some amount of time and can improve performance over time. Included in this category are Generative AI such as ChatGPT, virtual assistants and chatbots, and self-driving cars.
  3. Theory of Mind AI
    • This type of AI would be considered a General AI.
  4. Self-Aware AI
    • This type of AI would be considered a Super AI.


Large Language Models (LLMs) like ChatGPT learn statistical relationships between words from input text. They can then generate text by predicting the next word based on probability and a user-entered prompt. While these models are powerful, they do not know what is true and what is not.


IBM Data and AI Team. Understanding the different types of artificial intelligence. IBM. October 12, 2023. Retrieved January 9, 2024.

IBM Data and AI Team. What are large language models? IBM. Retrieved January 11, 2024.


Generative Artificial Intelligence

Generative artificial intelligence (AI) is a category of web-based tools that use algorithms, data, and statistical models to draw reasonable inferences to create content of its own (e,g., text, images, etc.). They are not search engines but rather trained chatbots. Using a prompt, a chatbot strives to fill in the next missing content piece, "what one might expect" (Wolfram). 

These tools use large language models to provide bots with the data they need to reply to a prompt you have given it appropriately. For example, when ChatGPT writes a response to a prompt, it provides text based on what words came before and what is the most likely next word. Because AI uses natural language and computes so quickly, it can often seem like the chatbot is, in fact, intelligent. 

The field of AI is changing at a rapid pace. We know that these generative tools help users synthesize information and create content (code, essays, art, music, etc.). However, these tools can also "hallucinate", or make up facts or sources and create biased content. 

Be sure to make sure it is ethical to use AI (see AI and Academic Integrity) and fact-check any content and sources you plan to use in the work you share with others or publish that has been generated by AI.


Source: Copied from UC San Diego Research Guide, which referenced the source below.

Last Update

Artificial Intelligence is an emerging technology and is evolving quickly. As such, this guide may have some outdated information if a change was recent.

Check the bottom of this page for the last update to this guide.