MSU Extension Organizational Development

MSU Extension Artificial Intelligence (AI):

Frequently Asked Questions and Examples 

What is Artificial Intelligence? 

Artificial Intelligence (AI) is a technology that makes predictions by training algorithms through large language models (LLMs), small language models or other information available via the internet. It is not the same as a Google search or search function that returns links to information related to the search terms. 

What is a large or small language model? 

A Large Language Model (LLM) or Small Language Model (SLM) is a type of artificial intelligence (AI) designed to process and generate human-like text. It is trained on vast amounts of text data and can understand, generate, summarize, translate, and analyze language. Examples include: GPT-4, Microsoft Copilot and Google Gemini.  

Am I required to use AI as a part of my job? 

No, the use of AI is not required for staff to complete the requirements of their position.   

When can I use AI in my position? 

An employee interested in utilizing AI to supplement their work should be familiar with the MSU Extension Policy for Use of Artificial Intelligence, Guidelines | AI | Michigan State University including understanding MSU’s acceptable use and institutional data policies. Employees must ensure data privacy and security. 

AI can be used to brainstorm and generate ideas for various projects including newsletters, articles, emails, social media posts, grant applications, survey questions.  AI can also be used to create draft images, graphics, generate alternative text for images, analyze publicly available and non-sensitive data and many more tasks associated with Extension work.  

Employees are responsible for and can be held accountable to decisions made based on AI output, AI information used and/or presented in their work, employment application materials, or areas where AI was used. 

When should I not use AI? 

Some research activities should not utilize AI. Examples include the peer review process and publishing in scientific journals. Further guidance can be found at: Guidelines | AI | Michigan State University. https://research.msu.edu/generative-ai/guidance.  

What are some examples of times I should verify outputs? 

Always! All outputs should be reviewed and edited as necessary. If the output generated includes information that is not evidence or research based, it should be removed.   

One specific example is qualitative coding of interview data when you are not familiar with the data, how to code data or using AI to singularly code qualitative data. When coding data best practices recommend using dual coders to avoid mistakes. 

How do I know if my AI generated output is biased?  

• Check if the AI reinforces stereotypes about race, gender, religion, or culture.
• Research key points to ensure accuracy – check names, title, quotations, number/ statistics, events, etc.
• Utilize evidence or research-based sites or tools, and subject matter experts to verify information.
• Ask the AI the same question in different ways and analyze whether it gives skewed or one-sided answers.

Can I use ChatGPT?  

Staff may use the enterprise licensed version of ChatGPT by purchasing the software through the MSU Tech Store.

Can I use AI for translating materials into other languages? 

While AI translation tools (like Google Translate or AI platforms with translation features) are improving, they should not replace MSU Extension’s established translation process. It is best practice to first submit materials through the official MSU Extension Translation Request Process. If AI is used to support translation efforts, the resulting text must always be reviewed through a peer review process to ensure cultural and linguistic accuracy. AI translations can contain errors or lack cultural nuance, so human verification is essential.