✨Guide: Ethically Using AI with Student Data

Canvassing options for professors to use AI without risking student data.

[image created with Dall-E 3 via ChatGPT Plus]

Welcome to AutomatED: the newsletter on how to teach better with tech.

Each week, I share what I have learned — and am learning — about AI and tech in the university classroom. What works, what doesn't, and why.

In this fortnight’s Premium edition, I present a guide for how to ethically use student data with AI tools.

With the rapid advancement of AI technologies, there is a pressing need to harness these tools responsibly, especially when it comes to the privacy and security of student data. The integration of large language models (LLMs) like ChatGPT, Gemini, and Claude into the educational sphere offers unprecedented opportunities for personalized and responsive pedagogy. However, these opportunities come with significant privacy challenges.

The utility of AI tools is contingent on their access to large volumes of high-quality data — data that, in many contexts, includes personally identifiable or otherwise protected student data. This requirement raises significant concerns about data security, as data breaches or misuse can lead to privacy violations.

Addressing these privacy issues requires more than just technological safeguards; it demands a comprehensive approach involving knowledge, expertise, and deliberate action. Educators must become adept not only at using AI tools but also at understanding the implications of their use, especially when it comes to student data privacy.

In this Guide, I canvas the option space and offer considerations related to each of the seven main options that I outline.

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