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Northwestern University

What Instructors Need to Know

Understanding the language in this changing landscape


Artificial Intelligence

Artificial intelligence (AI) is an umbrella term used to describe a range of different fields, processes, models and tools. 

Machine Learning

The process by which AI systems learn from data and improve their performance over time.

Generative AI (GAI)

An AI model that learns from training data and uses it to generate new content that resembles the original data.

Large Language Models (LLMs)

AI that is trained on large quantities of text in order to interpret prompts and generate human-like text-based outputs. ChatGPT, Bard, Bing and Claude are all examples of LLM applications.

Available LLMs include:

Large language models










The process of teaching AI to recognize patterns and make decisions based on input data. You may have encountered this when a photo app asked you to help it learn about the people in your photos.












LLMs like ChatGPT produce output based on patterns observed in training. They do not understand the content: They predict language based on the prompt they have received.


Prompts are the commands or instructions that tell the LLM what you'd like it to generate. Prompt engineering refers to the process of developing and refining queries to obtain better results from the LLM.


Because LLMs predict text, rather than producing verified content, they may make up information. These inaccuracies are termed "hallucinations" and their presence means that every piece of text produced by an LLM should be verified.

Ethics and Bias

AI tools may be biased. The information on which they were trained (the internet, social media, etc.) is biased. Thus, bias in AI tools is a reflection and perpetuation of larger systems of inequity in the world. Articles showing bias in AI tools against minority groups abound. As academics, with deep knowledge of individual disciplines and well-honed analytical thinking skills, faculty are well suited to identifying hallucinations or bias, working with students to shape their interactions with GAI, and helping to create better experiences.

Guidance on the Use of AI

Generative AI offers the potential for new capabilities in research, education, and productivity. In areas beyond the classroom, it is important to understand what to look for when adopting these tools as a way to ensure that the intended use is met while still protecting University data. Please see the Northwestern IT Guidance on the Use of Generative AI for more information.


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