Demystifying AI: A Practical Introduction for Instructors · LibreTexts
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3.3: Student Privacy and Data Security
Opening the book…
As AI tools become more common in education, concerns about student privacy and data security grow more urgent. Many AI systems rely on user inputs to improve performance, which means that anything a student types—personal details, assignments, or sensitive reflections—could be stored, analyzed, or used in ways that are not transparent. Instructors must consider not only how they use AI, but also how their students interact with it.
???? Understand Data Risks
Use AI to:
Discuss how AI systems collect, store, or process user data
Explore what happens to information typed into free or commercial AI tools
Examine privacy policies to determine how data is retained or shared
✅ Prompt Example:
“Review the privacy policy of a generative AI tool. What data is collected, and who can access it?”
✅ Prompt Example:
“Explain the difference between using AI with a personal login versus through an institutional account.”
???????? Promote Safe Use of AI
Use AI to:
Help students understand what not to share with AI (e.g., personal identifiers, grades, health info)
Design activities that avoid collecting unnecessary student data
Create classroom norms for ethical and secure AI use
✅ Prompt Example:
“List five types of information students should avoid entering into generative AI tools.”
✅ Prompt Example:
“Write a classroom announcement explaining the privacy limits of using AI in this course.”
???? Why This Matters for Instructors
Student trust depends on maintaining a safe, respectful digital environment. Instructors who model privacy awareness and set clear expectations around AI use help protect students from unintended data exposure. Being proactive about data ethics isn’t just about compliance—it’s about safeguarding student dignity and autonomy in the digital age.
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