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Artificial Intelligence - Student Guide: AI Literacy

artificial intelligence student guide

Use for AI in Everyday Life

  • Mapping out a road trip
  • Created graphics for anything
  • Doing quick research on the web
  • Quick reference data look-up How to write a Haiku
  • Summarizing text "with citations"
  • Generate music and lyrics 

Academic AI Survival Guide: How to avoid the RED

Academic AI Survival Guide

Do's

Assistance in generating ideas

• Clarifying course concepts

• Generating ideas for essay titles and outlines(outlines do not copy paste)

• Asking for feedback on snippets of code or help with Excel formulas

Do not's

• It is prohibited to type, dictate, copy, paste or otherwise transfer content owned by

DeVry University and subject to copyright, such as course content and materials with

the copyright symbol, into non-DeVry AI tools.

• Use of AI tools is prohibited for challenge exams, entrance

exams, appeals, or for other submitted materials to derive academic or financial

benefit, without express written permission from an appropriate DeVry

administrator.

• It is prohibited to use generative AI to complete the written portion of any DeVry

scholarship application. For more information, see the DeVry Scholarship Fund

Applications AI Guidelines

AI Literacy Framework

Artificial Intelligence Information Literacy Components

Authority Is Constructed and Contextual

  • Artificial Intelligence (AI) large language models are based on data inputs.
    • AI Chatbots that use data from the internet like Gemni, CoPilot, ChatGPT, and like are still evolving and suffer from invalid data output. It will hallucinate.
    • AI Chatbots based in a Library database or with a defined dataset have better accuracy.
  • Data sets contain biased information. Sometimes extremely biased.
  • AI uses probability to formulate its responses, not necessarily facts.
  • Opinions expressed in the prompt will be expressed in the results.
  • AI applications in library databases sometimes misrepresent the data.  

Information Creation as a Process

  • The response is only as good as the prompt. AI tends to be vague and general.
  • AI aggregates information from disparate sources. Not all are authoritative, unless in a database environment.
  • Large Language Models (LLM) probability programming to produce natural-sounding language, however, intended and unintended bias may be displayed in the results. 

Information Has Value

  • Hallucinations! It will make up sources and facts depending on the dataset.
  • Verify all resources cited in a response.
  • AI applications in the library databases pull from a defined pool of information (dataset/scholarly sources/articles). 

Research as Inquiry

  • AI may be used to narrow or expand a topic. 
  • AI applications in library resources can summarize sources and allow the user to explore a topic more efficiently.
  • AI is useful for generating search terms.
  • AI is useful for generating lists.
  • AI is useful for generating outlines (caution, the outlines are very general and lack details found in academic outlines). Do not copy and paste.
  • Bias is an issue due to an incomplete dataset. AI does not have access to everything.

Scholarship as Conversation

  • AI can not speak for a student, it can summarize complex technical writing.
  • Useful for creating and refining ideas and concepts.
  • AI application may be used to summarize the "conversation/research to date." 

Searching as Strategic Exploration

  • AI does not evaluate resource validity in responses. 
  • Generates keywords for searching and further prompt engineering.
  • Generates topics for research and further prompt engineering.
  • Generates outlines that assist in research strategy and subtopic selection.

Artificial Intelligence

What is Artificial Intelligence?

"Artificial intelligence refers to the branch of computer science that is focused on giving computers human intelligence. Upon hearing the term, most people think of HAL 9000 from 2001: A Space Odyssey, or maybe the character David from the movie A.I. Artificial Intelligence. The truth is that those forms of AI are still a long way off." 

National Geographic (Ed.). (2011). Artificial intelligence. In The Big Idea: How Breakthroughs of the Past Shape the Future (1st ed.). National Geographic Society. https://search.credoreference.com/articles/Qm9va0FydGljbGU6MzI1NDIxMQ==?aid=107032

What is Fuzzy Logic?

"The concept of a fuzzy set, introduced by L. A. Zadeh in 1965, deals with the representation of classes whose boundaries are not sharp."

"Different semantics (interpretations) can be associated with the use of fuzzy sets. One—historically the oldest one—is the expression of closeness, proximity, similarity, indiscernibility, indistinguishability and the like." 

Reilly, E. D., Ralston, A., & Hemmendinger, D. (Eds.). (2003). Fuzzy logic. In Encyclopedia of Computer Science (4th ed.). Wiley. https://search.credoreference.com/articles/Qm9va0FydGljbGU6MTY2NTM5Nw==?aid=107032

What is an LLM or Large Language model?

"Large language model (LLM), a deep-learning algorithm that uses massive amounts of parameters and training data to understand and predict text. This generative artificial intelligence-based model can perform a variety of natural language processing tasks outside of simple text generation, including revising and translating content."

Encyclopædia Britannica. (n.d.). Large language model (LLM). Britannica Academic. Retrieved August 20, 2024, from https://academic-eb-com.devry.idm.oclc.org/levels/collegiate/article/large-language-model/641255

What is an AI hallucination?

"Hallucinations are instances when models produce outputs that, though coherent, might be detached from factual reality or from the input's context."

Pradhan, R. (2023, October 23). Addressing AI hallucinations with retrieval-augmented generation. InfoWorld.com, NA. https://link-gale-com.devry.idm.oclc.org/apps/doc/A769960305/GBIB?u=devry_downergrov&sid=summon&xid=8bf33a37