Using Artificial Intelligence

OSU is committed to preparing you for a future where generative artificial intelligence (GenAI) use is commonplace. Because of this, your faculty are at the forefront of the GenAI conversation, exploring ways to integrate Artificial Intelligence into the university’s curriculum. Though advanced, artificial intelligence has limitations, including hallucinations and bias. It is important to understand those shortcomings and the continued value of human creation.

The misuse of GenAI on an assignment could violate the university's Academic Integrity Policy. Relevant provisions that GenAI misuse could violate include:

• Plagiarism: directly copying GenAI-generated material without a citation or reference is considered plagiarism
• Cheating: using GenAI to complete an assignment without prior authorization from your instructor
• Fabrication: using GenAI to create counterfeit citations, interview responses, or research results

At OSU, individual faculty have the freedom to set course-specific expectations for artificial intelligence use. It is important to recognize that different classes may have widely varying or even contradictory expectations. You must follow the specific expectations for each course. Always begin the term by carefully reading your syllabus to understand your instructor's expectations regarding GenAI usage. In order to use GenAI on an assignment, you must be able to answer “yes” to two questions:

1. Has your instructor provided expectations on how GenAI can be used on this assignment?
2. Do you understand what your instructor’s expectations are?

Potential uses of GenAI within course settings could include the following:

• Idea generation: Brainstorming research topics, thesis statements, or outlines.
• Clarification: Explaining difficult concepts or assignment prompts.
• Editing and proofreading: Checking grammar, tone, and clarity in writing.
• Coding assistance: Debugging, explaining algorithms, or generating sample code for learning.
• Formatting help: Creating citations, tables, or properly formatted documents.
• Practice and feedback: Simulating exam questions or providing feedback on drafts.
• Summarization: Condensing readings or lecture notes to highlight key points.
• Translation or accessibility: Translating text or converting it into plain language or alternate formats.

You should always seek clarification on what type of use is permitted and what is prohibited. It is ok to ask questions about GenAI!

Whenever GenAI usage is allowed, make sure to cite how you employed it in your work. The following decision tree will help walk you through whether or not you should use AI on a particular assignment.

• The flow chart helps students decide whether they can use generative GenAI on an assignment.
• It begins with the question: “Does your instructor have a statement on GenAI use in their syllabus or on Canvas?
• If the answer is yes, students should follow the guidelines provided in the syllabus or on Canvas.
• If the answer is no, students are instructed to ask their instructor for clarification about whether GenAI can be used for the assignment.
• After asking, students should follow whatever guidelines the instructor provides.
• If a student is unsure of the instructor’s expectations or cannot get clarification, the chart directs them to not use GenAI on the assignment.
• Overall, the flow chart emphasizes checking course materials, communicating with instructors, and avoiding GenAI use when expectations are unclear.

Citing Generative Artificial Intelligence

Citing generative artificial intelligence (GenAI) in an academic setting is critical, as it reflects both the rigorous scholarly approach to research and the ethical considerations surrounding AI technology. When incorporating AI-generated content, such as text or art, into academic work, proper citation not only gives credit to the underlying algorithms and data sources but also acknowledges the human input in training and fine-tuning these models. Additionally, citing AI sources helps maintain transparency and integrity in academic discourse, allowing readers to trace the origins and authenticity of the information presented.

However, the nuances of citing generative AI lie in the evolving landscape of AI capabilities and the ethical complexities involved. The MLA Style Center and the American Psychological Association (APA), among others, have provided guidelines on how to cite AI in your work. Links to these resources are linked below.

You should always check your syllabus to confirm your instructor’s expectations for AI citations. If you have questions, ask!

How to Cite Artificial Intelligence

AI-generated content should be cited much like content used from journals, books, and websites, with the company used as the author. Examples provided by common academic style guides are below.

• Modern Language Association (MLA Style)

Format: “Title of Source” prompt. Title of Container/AI Tool, Day Month version, Publisher, Date, URL.

MLA Example of Works-Cited citation:

OpenAI. ChatGPT, Mar. 14 version, OpenAI, 2023, https://chat.openai.com/chat.

• American Psychological Association (APA Style)

Format: Author. (Date). Title (Version) [Large language model]. URL

APA Example of Works-Cited citation:

OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat

Glossary of Important Artifical Intelligence Terms

Generative Artificial Intelligence (GenAI): artificial intelligence that is capable of generating new content (such as images or text) in response to a submitted prompt (such as a query) by learning from a large reference database of examples

Machine Learning: a computational method that is a subfield of artificial intelligence and that enables a computer to learn to perform tasks by analyzing a large dataset without being explicitly programmed

Deep Learning: a form machine learning in which the computer network rapidly teaches itself to understand a concept without human intervention by performing a large number of iterative calculations on an extremely large dataset

Neural Network: a computer architecture in which a number of processors are interconnected in a manner suggestive of the connections between neurons in a human brain and which is able to learn by a process of trial and error

Hallucination: a plausible but false or misleading response generated by an artificial intelligence algorithm

Definitions provided by Merriam-Webster Dictionary

Library Resources

OSU's Library provides a helpful primer on GenAI.

Academic Integrity

If an instructor has alleged that you may have misused an artificial intelligence tool, review the Academic Integrity Process page for more information.