These definitions are from: https://academics.waldenu.edu/artificial-intelligence/glossary
Bias: The presence of systematic and undesired preferences or imbalances in the output generated by an AI model. Bias can emerge in various forms, such as in the content, language, or perspectives generated by the AI system.
Burstiness: The abrupt shifts in quality, coherence, or relevance often observed in AI generated content, particularly in writing. It refers to the inconsistencies in style, tone, or factual accuracy that can occur within a short span. Identifying burstiness helps distinguish AI-generated content from human-created content.
Generative AI: AI systems that can generate new content such as text, images, or music. It involves developing algorithms and models that can understand patterns in existing data and use that understanding to generate novel output.
Hallucinations: Misinformation or made-up information based on a pattern that the AI model has learned as part of its training. For example, the model could create references that do not actually exist.
Large Language Models (LLMs): Components of artificial intelligence developed based on the training of vast datasets of documents from various sources. The computer program analyzes data input and maps out words in the dataset. It next tries to predict which words are positioned before or after other words using predictive patterns of most likely combinations.
Output: The generated content produced by a generative AI system. It can be text, images, audio, music, video, or other data the model is designed to produce.
Probabilistic: In generative AI, probabilistic means that the models incorporate probability, which is used to estimate the likelihood of different outcomes and generate outputs that align with the learned probabilities.
Prompts: The initial input text or instructions given to a model to generate new content based on that starting point. It provides context and guides the model's output. The prompt can be a few words or sentences that set the tone or specify the desired content, and subjective experiences.
Sentient: The capability to possess consciousness, self-awareness, and subjective experiences. Achieving true sentience in AI systems is a topic of scientific exploration and philosophical debate.
Tokens: Discrete units used to represent meaningful components of text, such as words or phrases. Breaking down text into these units allows AI models to process and analyze language at a granular level, enabling tasks like language generation.
From: The Journal of Academic Librarianship, The CLEAR path: A framework for enhancing information literacy through prompt engineering by Leo S. Lo
Concise - a concise prompt eliminates unnecessary information from the prompt.
Logical - a logical prompt is structured and coherent
Explicit - an explicit prompt provides clear specifications
Adaptive - an adaptive prompt is flexible and customizable
Reflective - a reflective prompt allows for continuous evaluation and improvement to prompts
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From College and Research Libraries News - Where does ChatGPT fit into the Framework for Information Literacy by Amy B. James and Ellen Hampton Filgo
Authority is Constructed and Contextual: "ChatGPT provides a disclaimer to let users know that the information that it provides may contain biases that it has a limited knowledge of current events. As the usage of ChatGPT increases it will become even more important that students know how to evaluate whether information that they come across is authoritative within the context of their research" (p.6).
Information Creation is a Process: this frame state "learners who are developing their information literate abilities accept the ambiguity surrounding the potential value of information creation expressed in emerging formats or modes." (ACRL). "To us, this is direct confirmation the ChatGPT has a place in the library instruction classroom both for its use in instruction and for discussion with students" (p.7).
Research as Inquiry: "ChatGPT can help refine research questions, determine search terms, come up with synonyms or related terms or phrases for searching" (p.11).
Scholarship as Conversation: "As we teach about how students can join the scholarly conversation with their own voice we need to emphasize the use of ChatGPT as a supportive resource along with librarians and other academic mentors" (p.14).
From Grammarly Blog - 9 Best Tips for Using AI Prompts for Writing
1 Create a . . .”
2 “Act as a . . .”
3 “Complete this sentence . . .”
4 “Mimic this style . . .”
5 “Give me examples of . . .”
6 “Show this as a . . .”
7 “Write a list of . . .”
8 “Compare . . .”
9 “Tell me about . . .” or “Explain . . .”
"Last but not least, with the entirety of the internet as their reference point, AI assistants can make great teachers. Simply ask one to tell you about or explain something, and it will usually respond with a clear and reasonable answer. Just be careful: There’s a lot of misinformation on the internet, so AI may cite incorrect sources and give you false information."
Ellis, Matt. (2023). The 9 Best Tips for Using AI Prompts for Writing. Grammarly Blog August 7, 2023. https://www.grammarly.com/blog/ai-writing-prompts/
James, A. B., & Filgo, E. H. (2023). Where does ChatGPT fit into the Framework for Information Literacy? The possibilities and problems of AI in library instruction. College & Research Libraries News, 84(9), 334. https://doi.org/10.5860/crln.84.9.334
Kim, B. (2023). ChatGPT and Generative AI Tools for Learning and Research. Computers in Libraries, 43(6), 41-42. https://mccc.idm.oclc.org/login?url=https://www.proquest.com/trade-journals/chatgpt-generative-ai-tools-learning-research/docview/2830977489/se-2
Lo, Leo S. (2023). The CLEAR Path: A Framework for Enhancing Information Literacy through Prompt Engineering. The Journal of Academic Librarianship, 49(4),p.2. https://www.sciencedirect.com/science/article/abs/pii/S0099133323000599
Walden University. (2023). Key AI Terms Glossary. Academics at Walden University. https://academics.waldenu.edu/artificial-intelligence/glossary