Artificial Intelligence

Artificial intelligence (AI) has existed for decades. AI replicates human intelligence by leveraging computers and machines to complete problem-solving and decision-making tasks. While AI is not a new concept, the field of higher education has had to adapt to the proliferation of generative AI tools, such as Chat GPT.

Since the introduction of Open AI’s ChatGPT in the fall of 2022, many possibilities and challenges have arisen in higher education, concerning the use of Artificial Intelligence (AI). The goals of this guide are to:

  • Help the University community gain an understanding of Artificial Intelligence
  • Share curated resources related to AI in Higher Education
  • Provide information to assist AU community members as they make decisions related to AI use

What is Chat GPT and How Does it Work?

Chat GPT, created by Open AI, is a chat bot that users can engage with conversationally. Users can ask for information, writing, or for help with a specific task (Harvard Online, 2023). It relies on large amounts of data and computing techniques which predict how to put words together in way that mimics human speech (Sundar, 2023). It is important to understand that generative AI systems like ChatGPT do not perform actual thinking like humans do.

Artificial Intelligence (AI)

Artificial Intelligence leverages computers and machines to attempt to mimic the problem-solving and decision-making capabilities of the human mind (IBM).


A procedure that produces that answer to a question or the solution to a problem (Britannica).

Generative AI

A type of AI that can generate text, images, or other information based on the data it was trained on (Martineau, 2023).


In regards to AI, a hallucination refers to computer-generated information that is not factual. Generative AI works by responding to patterns, thereby producing results that may not be accurate (Mair, 2023).


The information or request provided to an AI to let it know what the user is looking for. A question posed to ChatGPT, for example (Martineau, 2023).

Large Language Model (LLM)

A large language model is an algorithm that can recognize, summarize, translate, predict and generate text and other content types based on knowledge provided by large datasets (Lee, 2023).

Glossary Bibliography



Lee, Angie. (2023, January 26) What Are Large Language Models and Why Are They Important? NVIDIA Blog.

Martineau, K. (2023, February 15) What is Prompt Tuning? IBM.

Martineau, K. (2023, June 30) IBM.

The following recorded webinars contain guidance on how to navigate the integration of artificial intelligence in higher education.

SUNY FACT2 Spring 2024 Webinar Series Playlist, SUNY FACT2 AI Task Group

How Should Academics Respond to Emerging AI Technology? Future Trends Forum, Bryan Alexander

Open Source AI for Higher Education Future Trends Forum, Bryan Alexander

AI in Higher Ed: Opportunities and Threats, Online Learning Consortium

The best way to gain a deeper understanding of generative AI tools it to try them out. 

Chat GPT – Free, account required

Perplexity – No account required; provides sources for responses

Claude - Free option, account required

Almanac - Free option, account required; designed to help educators create lessons and resources

The article How to Use Chat GPT to Save Time includes suggestions for how instructors may use generative AI to assist with routine tasks.

After you decide what level of AI use will be permitted in your courses, those expectations will need to be communicated with your students so they are aware of their responsibilities. One way to communicate those expectations is with a syllabus statement.

AI Syllabus Statements

A syllabus statement on the permitted level of generative AI use can help students have a clear understanding of the instructor’s requirements. When creating a syllabus statement, please consider including the following information:

  • What level of generative AI use is permitted?
    • None
    • Some with guidelines, or under specific circumstances
    • Encouraged/ required
  • How does the permitted level of AI use support the learning objectives of the course?
  • Is AI permitted for specific tasks?
    • Schedule creation/ time management
    • Idea generation
    • Analyzing text or images
  • Is AI permitted for certain types of assignments, but not for others?
  • Are students expected to fact-check AI output?
    • What evidence must they provide?
  • What citation format must students follow in order to properly cite content generated by AI?
  • Do students need to provide the prompt and output in addition to the citation?

For additional guidance on AI syllabus statements, please the chapter of the SUNY FACT2 Guide to Optimizing AI in Higher Education entitled Setting Expectations in Your Classes.

Citation Guidelines for AI-Generated Content





In May of 2023, The SUNY Faculty Advisory Council on Teaching & Technology (FACT2) created a task group to investigate how AI could be optimized for teaching and learning in higher education. The resulting report discusses the benefits and challenges associated with AU, and serves as a guide for faculty and educational technologists as they learn more about AI, and consider its potential uses. An updated second edition of the report was released in June 2024.  Both editions are available below.

FACT2 Guide to Optimizing AI in Higher Education, Second Edition 2024

FACT2 Guide to Optimizing AI in Higher Education, First Edition 2023