Editing Openai/685c0d4c-c498-800c-a453-8e1a327151d8 (section)

==== ✅ Use AI to Handle Large-Scale Data, but Validate Outputs ====
* AI is excellent for processing large text datasets (e.g., interviews, syllabi, policy documents).
* However, human validation is needed to ensure relevance and accuracy of extracted information.

✅ Be Transparent About Training Data
* If using AI models for analysis (e.g., NLP tools for coding), clarify: - What data was used to train the model? - Are there potential biases in the dataset? - How might these biases affect research findings?

✅ Respect Data Privacy & Security
* When handling confidential or personal data, ensure AI tools comply with: - GDPR (General Data Protection Regulation) - IRB ethics approval for qualitative research - Anonymization best practices (e.g., removing personal identifiers from datasets).

✅ Use AI for Preprocessing, Not Just Analysis
* AI can assist in: - Transcribing interviews (e.g., Otter.ai, Descript) - Cleaning text data (e.g., removing noise from survey responses) - Organizing qualitative data for thematic analysis