Skip to Main Content

Artificial Intelligence

Currency of Information: Information about ChatGPT and other AI tools is continuously evolving. We are doing our best to ensure this guide is accurate and up to date, and will be updating information as it emerges. Wherever possible, we've identified dates for articles and information to help users understand when the information we are using was published. 
If you find discrepancies or outdated information, please email:


Family tree diagram of Data Science, AI, and Machine Learning

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Wheatley, A & Hervieux, S. (2020). The AI family tree [diagram]. The LibrAIry.

Artificial Intelligence

A term used to describe the use of a system to emulate human decision making and learning abilities. The founding father of artificial intelligence is Alan Mathison Turing, through his writings that include Computing Machinery and Intelligence (1950). Turing OBE, an English mathematician, Second World War code-breaker and computer scientist and inventor, also described the ‘Turing machine’, and how it could theoretically implement logical processes. Expert systems, or knowledge based systems (KBS), and neural networks are perceived as part of AI. It is believed that massively parallel processing (MPP) systems will unleash and emulate many human-like thought processes.

AI (artificial intelligence). (1999). In F. Botto, Dictionary of multimedia and internet applications: a guide for developers and users. Wiley. 

Machine Learning

Machine learning is the branch of artificial intelligence (AI) concerned with creating systems that can automatically improve their ability to perform tasks such as classifying images, interpreting text, or finding patterns in data.

Henderson, H. (2021). Machine learning. In H. Henderson, Encyclopedia of computer science and technology (4th ed.). Facts On File. 

Neural Network

or neural computing, computer architecture modeled upon the human brain's interconnected system of neurons. Neural networks imitate the brain's ability to sort out patterns and learn from trial and error, discerning and extracting the relationships that underlie the data with which it is presented. Most neural networks are software simulations run on conventional computers.

Neural network. (2018). In P. Lagasse, & Columbia University, The Columbia encyclopedia (8th ed.). Columbia University Press. 

Large Language Model (LLM) or Chatbot

"A large language model, or LLM, is a deep learning algorithm that can recognize, summarize, translate, predict and generate text and other forms of content based on knowledge gained from massive datasets." from the NVIDIA blog via ChatGPT FAQ by Nicole Hennig

Generative AI

Generative Artificial Intelligence (AI) is a machine learning technology that uses AI technology to understand natural language inputs (called prompts) and to generate natural language outputs (called completions). Users interact with generative AI tools and systems in a question and answer style “conversation."

Australian National University (2023) Chat GPT and other generative AI tools: What ANU academics need to know (PDF, 103KB)

AI Tools

Video based generative tools are also emerging. Meta's Make-A-Video and Stable Diffusion Video can generate short animations based on text prompts in a similar way to the tools above. 

There are also a wide range of AI-enhanced video platforms for the generation of explainer or marketing videos, These platforms allow for the creation of videos based on text prompts, using a basis of templates, AI avatars and stock footage. Examples include Synthesia and  InVideo: these are typically subscription based tools though free plans may be available. 

ROBOT test

Being AI Literate does not mean you need to understand the advanced mechanics of AI. It means that you are actively learning about the technologies involved and that you critically approach any texts you read that concern AI, especially news articles. 

Librarians at McGill University have created a tool you can use when reading about AI applications to help consider the legitimacy of the technology.






  • How reliable is the information available about the AI technology?
  • If it’s not produced by the party responsible for the AI, what are the author’s credentials? Bias?
  • If it is produced by the party responsible for the AI, how much information are they making available? 
    • Is information only partially available due to trade secrets?
    • How biased is they information that they produce?
  • What is the goal or objective of the use of AI?
  • What is the goal of sharing information about it?
    • To inform?
    • To convince?
    • To find financial support?
  • What could create bias in the AI technology?
  • Are there ethical issues associated with this?
  • Are bias or ethical issues acknowledged?
    • By the source of information?
    • By the party responsible for the AI?
    • By its users?
  • Who is the owner or developer of the AI technology?
  • Who is responsible for it?
    • Is it a private company?
    • The government?
    • A think tank or research group?
  • Who has access to it?
  • Who can use it?
  • Which subtype of AI is it?
  • Is the technology theoretical or applied?
  • What kind of information system does it rely on?
  • Does it rely on human intervention? 

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Hervieux, S. & Wheatley, A. (2020). The ROBOT test [Evaluation tool]. The LibrAIry.

AI Ethics

There are a number of ethical considerations with using generative AI. Because AI is "trained" on existing creative material (images, text, video, etc), including copyrighted works in some cases, the owners and copyright holders object. Midjourney in particular has been criticized for its ability to create images "in the style of" a particular artist or that mimic a particular artwork. The results are often very similar to the work of living artists; artists who make their living selling their work. In addition, members of the Writers Guild of America and SAG-AFTRA both cited concerns about AI being used to replace their members as reasons for striking in 2023. (Writers strike: Why A.I. is such a hot-button issue in Hollywood’s labor battle with SAG-AFTRA | Fortune). Janelle Shane, of the AI Weirdness blog and You Look Like a Thing and I Love You: How AI Works and Why it’s Making the World a Weirder Place has written: "In my opinion, the most interesting creative use of large language models is to generate text that's nothing like a human would have written. If your AI is just going to lift human creative output virtually verbatim, you're not only shortchanging the humans you could have hired to write similar things, but also plagiarizing the original humans from the training data" (23 Aug 2023).

You should always discuss your plans to use AI with your instructor and cite it in any submitted work. Here are some examples of how AI could be used in academic work:

  • LLM chatbots like ChatGPT might be a useful way to get a quick overview on a topic. As with Wikipedia, we'd recommend that you follow references and check the source. Remember, LLMs can produce credible sounding yet incorrect content, or create references to sources that don't exist. 
  • You could use an LLM to refine the style or composition of (non-assessed) writing. This can be helpful for work or professional contexts such as social media posts or sending emails.
  • To summarise a longer document
  • To brainstorm ideas
  • To generate keywords for searches