The resources listed here are for general use, such as how to cite ChatGPT in the most common citation styles; what types of AI. Resources are available for AI detection in addition to various text-based, image-based, and video-based AI generator tools; and a list of Academic Associations in which faculty may find additional information specific to ChatGPT or AI generators.
General Resources
Popular AI tools
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Academic RAGs
Retrieval-augmented generation (RAG) models pull info from specific knowledge bases such as academic and research databases. They have access to current content where as LLS models such as ChatGTP use dated information and are trained with a much broader content range.
PROS | CONS |
You know were the info comes from; it is limited. | Cannot breach subscription paywalls. |
Pulls from open access resources. | Students cannot get a broad view of topics. |
Fewer "hallucinations." | |
Help bridge complex ideas. | |
Content is not dated; it uses current info. |
General LLMs
Large Language Models (LLMs) are good at predicting the next word sequence from a very large knowledge base. They are not as accuracy and reliability as RAGs and have a tendency to "hallucinate" and make things up. LLS models such as ChatGTP are more broadly trained.
PROS | CONS |
good for background research. | cannot evaluate credibility of info. |
natural conversation and easy to understand. | cannot breach paywalls. missing info |
easy to ask follow up questions. | trained on dated content. |
opposing view points are readily available. | may "hallucinate" and make things up. |
help grasp terminology use in fields of study. |
Image-Based AI Generators
Below is a list of well-known AI generators that are specifically geared toward creating images.
Video-Based AI Generators
Below is a list of well-known AI generators that are specifically geared toward creating videos.
AI Detectors
AI detectors are not very reliable. Temple University tested Turnitin and found it to be "incredibly inaccurate" (Assoc. Press, 8/10/23). According to an associate vice provost at Temple, it worked "best at confirming human work... but was spotty in identifying chatbot-generated text and least reliable with hybrid.
Students may get falsely flagged for cheating with AI. For example, a Texas A&M professor wrongly accused an entire class of using ChatGPT on final assignments. He pasted their responses into ChatGTP and asked if it generated the answers. ChatGPT affirmed that it had written the responses when it really hadn't.
According to the conclusions of a 2023 research article by Deora Weber-Wullf et al., current detection tools are neither accurate or reliable. All detection tools, including Turnitin, that were tested scored below 80% accuracy. Only five of the twelve tools tested above 70% accuracy. Educators "should focus on the process of development of student skills rather than the final product."
There are several ways to spot AI content: