Resources for students

This portal offers information to help students navigate the use of AI technologies in their classwork and research.

Frequently Asked Questions
Can I use generative AI tools for my class assignments at UGA?
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UGA’s default policy prohibits using generative AI tools for coursework unless your instructor explicitly allows it in your syllabus or approves it for specific assignments. Understanding these guidelines helps ensure you’re using AI tools appropriately and following UGA’s Academic Honesty Policy. 

How can AI tools assist in my learning, and what are the risks?
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AI tools can help you summarize readings, brainstorm ideas, create study aids and practice questions, provide writing feedback, and more. However, these tools work by predicting likely text based on patterns in their training data, so they produce responses that sound reliable but might be inaccurate or biasedThese AI tools are not authoritative sources, and overreliance on them can hinder your critical thinking skills. Always fact-check your AI outputs against credible sources and use AI to supplement, not replace, your own original thinking. 

How should I cite AI-generated content?
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When your instructor permits AI use, it’s important to cite it transparently in your assignments, indicating how it was used and following proper citation format (APA, MLA, etc.). Including acknowledgment of AI involvement will help you maintain academic integrity and avoid plagiarism. View the Libraries AI Literacy Guide for Students to learn more about proper AI citation. 

What AI tools does UGA provide access to?
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UGA provides campus access to several AI tools, available using your MyID login.  

  • Google Gemini supports content generation, brainstorming, and multimodal tasks using text, images, and other inputs.  
  • Google’s NotebookLM serves as a research assistant with document management, conversational AI, and content creation features like study guides and podcast overviews.  

These tools meet university privacy and data security standards, meaning your input and output data stay protected and are not used to train external models or shared with external parties.

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