Artificial Intelligence (GAI) Text Generation: Considerations for Teaching and Learning

Artificial Intelligence (AI) tools have been in existence for quite some time; however, the launch of Open AI’s tool ChatGPT in late November 2022 garnered considerable attention specifically due to the impact on teaching and learning. 

Some institutions have established institutional guidelines to aid student and faculty when making decisions around the appropriate use of GAI, yet most veered away from the “one-size fits all” policy approach as it proved to create more confusion in specific cases.

What is Artificial Intelligence in the broad sense? 

Artificial Intelligence refers to the development of systems that can perform tasks typically requiring human intelligence, such as reasoning, learning, and problem-solving.” These systems can mirror various aspects of human intelligence when attempting to analyze data, make decision, recognize patterns etc. Some examples of AI are fraud detection systems, chatbots, self-driving (autonomous) vehicles, medical diagnostic tools, to name but a few. 

What is Generative Artificial Intelligence (GenAI) more specifically? 

“Generative AI refers to AI systems that produce new content, such as text, images, music, or videos, by learning patterns from existing data.”  As a specific and specialized branch of AI, it utilizes advanced large language models (LLM) and datasets to generate new content and thus emphasizes creativity and synthesis as opposed to raw analysis or prediction. Some examples of GenAI are MusicLM (for composing original music); GitHUB Copilot (for writing snippets of computer language code); ChatGPT, Copilot, or Gemini (for text generation of summaries, conversational responses, essays etc.); and DALL-E or MidJourney (for generating artistic images), to name but a few.

Memorial’s Statement on Generative Artificial Intelligence (GAI) Tools 

References

Resource created by: Ruth H. & Gil S. last updated January 28, 2026

Originally Published: January 28, 2026


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