Ethical Use of Generative AI in University Studies
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Questions and Answers

What should you consider when evaluating the ethics of using a generative AI tool?

  • The tool's system requirements
  • The tool's font size and style
  • The user's personal data collection and usage (correct)
  • The tool's color scheme and design
  • Why is referencing the AI tool appropriately important when using it?

  • To increase the tool's speed and accuracy
  • To acknowledge the sources of data used by the tool (correct)
  • To change the tool's functionalities
  • To add unnecessary information to the task
  • What could lead to academic misconduct when using Generative AI in assignments?

  • Not using a Generative AI tool at all
  • Referencing the AI tool correctly
  • Prohibited use of Generative AI in assignments (correct)
  • Asking the tool to recite something
  • In what scenario would using Generative AI be considered unethical?

    <p>When there are clear conflicts with the task goal</p> Signup and view all the answers

    How can plagiarism occur when using a Generative AI tool?

    <p>By not referencing the tool correctly</p> Signup and view all the answers

    What is the primary reason the author suggests using generative AI in university studies?

    <p>All of the above</p> Signup and view all the answers

    What is the main limitation of generative AI mentioned by the author?

    <p>Generative AI does not have the capacity to make judgements or think independently</p> Signup and view all the answers

    According to the author, what acronym can be used to evaluate the reliability of information from generative AI?

    <p>CRAPP-E</p> Signup and view all the answers

    Which of the following is NOT one of the criteria in the CRAPP-E acronym mentioned by the author?

    <p>Presentation</p> Signup and view all the answers

    What is the main purpose the author suggests for using the CRAPP-E criteria when evaluating information from generative AI?

    <p>All of the above</p> Signup and view all the answers

    Study Notes

    Ethical Use of Generative AI in University Studies

    • Generative AI can be used ethically in university studies to assist with time efficiency and develop AI literacy, a valuable skill in the modern job market.

    Limitations of Generative AI

    • Generative AI lacks the capacity to make judgments or think independently, which may compromise the validity and credibility of its responses.

    Evaluating Generative AI Responses using CRAPP-E

    • C Currency: Evaluate the tool's creation date, information currency, and potential impacts of new data or tools on its quality.
    • R Relevance: Assess whether the tool meets your needs and provides relevant responses to your topic, which may depend on your research and prompting skills.
    • A Accuracy: Verify the accuracy of responses, check for citations and references, and ensure they are real and trustworthy.
    • A Authority: Identify the tool creators, their expertise, and potential biases, which can influence their perspective and tool design.
    • P Purpose: Understand the tool's purpose, its design, and potential effects on user behavior and thought patterns.
    • E Ethics: Evaluate the tool's data collection and usage practices, ensure proper attribution of sources, and consider the ethical implications of its use.

    Responsible Use of Generative AI in Assignments

    • Check the exam policy to ensure the use of generative AI is permitted in assignments.
    • Reference the AI tool properly using the format found in the MQ resource guide.
    • Failure to do so may constitute academic misconduct, particularly if the tool is used where prohibited or not properly referenced, which can be considered blatant plagiarism.

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    Description

    Explore the ethical considerations of utilizing generative AI in university studies, particularly in the context of improving time efficiency and developing AI literacy. Understand the limitations of AI in making independent judgments and the importance of validating generated responses before drawing conclusions.

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