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AI in Healthcare

A guide introducing artificial intelligence as it applies to healthcare

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Teaching with AI

Things to keep in mind when teaching and learning with generative AI.

  • Keep humans in the loop: humans should be involved at all stages of evaluation and decision-making when using generative AI tools for teaching and learning.
  • Confirm results: beware "hallucinated" information and do not assume accuracy, quality or completeness of AI generated content. Also, be aware that AI tools may not have access to the most recent information.
  • Emphasize discovery and experimentation: generative AI may be best suited to learning activities that call for exploration, where learners can generate content and then improve on it or investigate it for accuracy.
  • Be mindful of privacy risks: be sure to follow institutional policies and avoid using any personal data in interactions with generative AI tools.
  • Be mindful of bias: limitations in the information used to train language models used by AI tools may reinforce biases in generated content.
  • Consider assumptions: Generative AI is a hotly discussed topic, inspiring both fascination and fear. Make space to explore and address learner preconceptions about use of these tools.
  • Beware of Plagiarism: Plagiarism with generative AI is an ongoing concern without easy solutions. Plagiarism checkers may fail to detect AI-generated content or incorrectly flag original or adapted content. Consider addressing AI in academic integrity policies.
Further reading:
  1. 1. U.S. Department of Education, Office of Educational Technology. (2023). Artificial Intelligence and Future of Teaching and Learning: Insights and Recommendations (PDF) [Report]. Washington, DC.
  2. 2. Mollick, E., & Mollick, L. (2023). Assigning AI: Seven Approaches for Students with Prompts. arXiv preprint: 2306.10052.
  3. 3. Hodges, Charles & Ocak, Ceren. (2023). Integrating Generative AI into Higher Education: Considerations. EDUCAUSE Review.