Generative AI: Home

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• Han, E. R., Yeo, S., Kim, M. J., Lee, Y. H., Park, K. H., & Roh, H. (2019). Medical education trends for future physicians in the era of advanced technology and artificial intelligence: an integrative review. BMC medical education, 19(1), 460. https://doi.org/10.1186/s12909-019-1891-5

• Kyaw, B. M., Saxena, N., Posadzki, P., Vseteckova, J., Nikolaou, C. K., George, P. P., Divakar, U., Masiello, I., Kononowicz, A. A., Zary, N., & Tudor Car, L. (2019). Virtual Reality for Health Professions Education: Systematic Review and Meta-Analysis by the Digital Health Education Collaboration. Journal of medical Internet research, 21(1), e12959. https://doi.org/10.2196/12959

• Lindqwister, A. L., Hassanpour, S., Lewis, P. J., & Sin, J. M. (2021). AI-RADS: An Artificial Intelligence Curriculum for Residents. Academic radiology, 28(12), 1810–1816. https://doi.org/10.1016/j.acra.2020.09.017

• McCoy, L. G., Nagaraj, S., Morgado, F., Harish, V., Das, S., & Celi, L. A. (2020). What do medical students actually need to know about artificial intelligence? NPJ digital medicine, 3, 86. https://doi.org/10.1038/s41746-020-0294-7
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• Rambukwella, M., Balamurugan, A., Klapholz, H., & Beninger, P. (2021). The Application of Engineering Principles and Practices to Medical Education: Preparing the Next Generation of Physicians. Medical science educator, 31(2), 897–904. https://doi.org/10.1007/s40670-021-01217-x

• Ravi, S. P. Artificial Intelligence in Health Professions Education. Archives of Medicine and Health Sciences10(2), 256-261. 10.4103/amhs.amhs_234_22
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When you ask questions of one of the major generative AI tools, you’ll learn how to have conversations similar to human interactions and then critique the results carefully. These back-and-forth exchanges will produce the best results.

Adapted from: UHN Libraries (2025). "Generative AI at UHN". Retrieved from: https://guides.hsict.library.utoronto.ca/UHNvirtuallibrary/genai

• Understand the Tool: Familiarize yourself with the capabilities and limitations of the AI tool. This includes understanding the type of tasks it can perform, the data it was trained on, and its ability to understand and generate content.
• Clear Instructions: When interacting with the AI, provide clear and concise instructions. The more specific you are with your request, the better the AI can generate the desired output.For examples see GenAI Prompting Guidance section. 
• Iterative Process: Using AI tools is often an iterative process. If the initial output isn’t what you expected, refine your instructions and try again.
• Review Outputs: Always review the outputs generated by the AI. While AI can generate useful and creative content, it’s crucial to ensure the information is accurate and appropriate for your needs.
• Ethical Use: Be mindful of ethical considerations when using AI. This includes respecting copyright laws, avoiding generating harmful or offensive content, and considering the privacy implications of the data you’re working with.
• Continuous Learning: AI tools are continually evolving and improving. Stay updated with the latest advancements and updates to the tool to make the most of its capabilities.

Reminders when using any GenAI tool 

• Always verify and validate the accuracy of returned results.
• Do not use any Gen AI tool for any type of clinical care related work, including note taking to put into a chart, generating summaries of patient information, or other. UHN has not validated the use of these tools for medical applications and teams are working on controlled pilots for such use cases.
• Never put Private or Confidential information, including patient data (PHI - Personal Health Information) employee information, research and education confidential data, corporate confidential information, or intellectual property in any Gen AI tool

AI tools are now everywhere and many people may interact with them daily without even realizing it. In this environment, it is important to have basic knowledge of how AI tools function and understand various AI terms and acronyms.

Deep Learning - ML that uses neural networks - computer models inspired by the human brain

Natural Language Processing - ML focused on understanding and generating human language

Machine Learning -  Using algorithms and data to train computers

Computer Vision - ML that enables computers to see and act on visual information

Multimodal AI - Computers that can read and generate text, images, audio and video

Generative AI - Using AI to create new text, images, audio and video

Large Language Models  -  Computers trained to analyze prompts and generate human-like responses

Before you start 

• My school and my professor allow the use of the AI tools I’m considering for this assignment
• I clearly understand when and how I can use AI for this assignment

Doing the work 

• I am using my own thoughts, words and tone of voice
• I have checked sources generated by AI and properly cited any facts, statistics or quotes
• I have critically analyzed the AI output and identified any false, biased or harmful information
• I have documented where and how I used AI and cited that use according to my professor’s expectations
• I have not used confidential, protected or copyrighted information

When the assignment is complete 

• I can explain my findings and demonstrate full understanding without the aid of AI
• I can prove what sources I used and how I verified the information

Generative AI systems produce results by learning from data. Systems that use generative AI often record and store data provided to them, helping them to improve performance. If private data is shared with generative AI, this data may be revealed later in the results that the AI produces. Keep in mind:

• No data should be provided to generative AI if any part of that data should not be included in results produced by that system.
• If multiple people are using the system, one person’s data may potentially be revealed to someone else.
• Be aware of whether the system shares data with other systems and platforms.
• Do not share personal information or patient health information with unverified or insecure generative AI tools.
• As AI functionality is increasingly added to Software-as-a-Service (SaaS) and cloud services, it’s important to examine potential changes to privacy policies, user agreements and contractual terms to ensure that data will be handled appropriately.
• Copyright and contract law around AI is an evolving area and the Michener Institute's understanding will develop as new policies, regulations and case law becomes settled.