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Artificial intelligence is fundamentally changing
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healthcare, education and research.
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At MUSC, we’re embracing this transformation while carefully
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training healthcare leaders who possess the skills necessary
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to drive healthcare innovation, both now and in the future.
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To achieve this, we’re thoughtfully assessing when
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and how our students should use ai, teaching them
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to leverage its capabilities effectively,
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while also emphasizing the importance
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of developing essential human only skills
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that can be demonstrated independently of ai.
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This commitment is why we’ve developed the AI acceptable use
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framework, a guide
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that helps students understand when the use
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of AI is acceptable, when completing academic tasks
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and what that use should look like if permitted
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instructors will specify one of five categories
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of AI use for each task.
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These categories reflect varied learning objectives
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and ensure that AI supports
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and does not replace the development
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of core human competencies.
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This framework serves as a guideline to help define
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where AI adds value
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and where unassisted practice remains Essential.
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Responsibilities are clearly defined.
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Instructors will designate which category applies
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to each task based on learning objectives
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and assessment goals.
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Students must identify the specified category for each task
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and provide any documentation required.
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Category one, no ai.
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AI may not be used at any point during the task
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board style exams
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or clinical skills demonstrations fall into this category.
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Any AI use here would undermine the intent
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to measure unassisted human performance.
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Category two, AI planning.
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AI may only assist with high level brainstorming
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or outlining, such
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as generating a draft structure for a paper.
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Final content must be, original.
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Documentation may be required
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regarding prompts used in which AI
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suggestions were integrated.
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Category three, AI limited AI may be used in a limited way
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to complete only specific aspects of the task, such
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as formatting data tables, creating visual layouts,
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or checking grammar and spelling.
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For example, all core work must be completed
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without AI assistance.
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Documentation may be required regarding each AI interaction
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and how outputs were evaluated.
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Category four, ai extensive AI may be used extensively
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to complete any element of the task as directed
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by the course instructor.
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For example, AI tools may be used
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to conduct a literature review with students,
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then verifying, critiquing,
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and correcting AI generated summaries for accuracy,
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bias and completeness.
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Documentation may be required regarding decision points,
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corrections made, and rationale for accepting
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or rejecting AI generated content.
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Category five, AI exploration.
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AI is required to complete the task
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and serves as both a subject of inquiry
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and an innovation catalyst to enhance problem solving
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or generate novel insights, critical analysis
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and thorough examination of AI strengths
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and limitations are expected.
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An example might include creating an AI chat bot
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to support patient education about diabetes management.
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Then systematically testing its responses
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for medical accuracy, cultural sensitivity,
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and communication effectiveness.
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While analyzing the ethical implications
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of AI in patient care, documentation may be required
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regarding the research process, analytic methods,
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and evaluation of AI’s impact.
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AI is a powerful resource
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but cannot replace the personalized expertise, mentorship,
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and critical thinking that define MUSC.
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Excellence Guidance is available at every stage.
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Your course faculty, they know the learning objectives
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and can clarify expectations.
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MUSC, central University and College Support Services.
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They provide expertise in information literacy,
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academic writing, citation, AI tool use, and more.
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Your peers. Collaborative learning strengthens understanding
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by following this framework.
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MUSC community members will engage AI deliberately
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uphold academic integrity
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and develop the skills needed to thrive in a digital world.