Dear Master’s Students,
We have all witnessed the rapid advancements in artificial intelligence technologies over the past several years, including rollout of large language models (LLMs) like ChatGPT. We know that these can be useful tools in healthcare and education, when used appropriately. We are therefore happy to announce that Harvard Medical School will provide all HMS master’s students access to the HUIT AI Sandbox effective immediately for the 2025-2026 academic year. You can access the AI Sandbox here by clicking “sign in” and logging in with your HarvardKey credentials.
Before using the AI Sandbox for course work or academic writing, please confirm the specific AI use policies governing the academic work in your program and individual courses with your program directors and/or individual course directors. If approved for use, remember that you must disclose use of AI tools and cite them appropriately. As detailed further below, while you may upload course materials to the AI Sandbox (unless explicitly disallowed by your course director), you should not upload materials to “free” genAI tools like Google Gemini of free ChatGPT. Finally, we encourage you to engage your peers, instructors, and program directors in conversations about how we as a community can productively engage with generative AI in our academic and professional activities without short-cutting essential learning processes.
Additional details about this resource are given below. We are incredibly excited to offer this Sandbox to all HMS students. While we work to get formal evaluation and feedback systems in place, if you have any comments or concerns, please feel free to reach out to Taralyn_Tan@hms.harvard.edu
Additional Information:
The AI Sandbox contains multiple AI models, including the latest versions of ChatGPT, Claude, Llama, Gemini, and DALL-E, as well as smaller models. It also has the ability to directly upload multiple documents, to generate charts and graphs to visualize data insights, and create visual content based on text prompts. Our goal is to encourage both educational experimentation and the development of a community of learning. With that in mind, we are providing the following policies to guide use of the HUIT AI Sandbox:
1. Privacy. The AI Sandbox has many privacy protections, but it is not HIPAAcompliant. No identifiable patient information should ever be entered into the Sandbox. Similarly, patient notes, even if stripped of identifiers, should not be uploaded. We also caution you about uploading any sensitive or embargoed research data. However, the sandbox does have many other privacy protections in place, and personal information about yourself, including items such as course evaluations, as well as curricular materials from Harvard Medical School, are safe to upload. Unlike public models, none of the information that you put into the Sandbox can be accessed outside of the
Harvard environment and cannot be used to train future models. The Harvard AI Sandbox is approved for up to Medium Risk Confidential (L3) data.
2. Academic integrity. Please refer to the HMS Master’s Student Handbook, Section 3.09 on the expectations on the use of AI. You must first follow the guidance of course instructors and program directors about whether AI may be used at all; unless otherwise specified by your instructor, it is a violation of the HMS Code of Conduct to use the Sandbox to generate either part of or the entirety of an assignment and to pass it off as your own. When in doubt about the policy on AI use for an assignment, contact your instructor for guidance. If AI use is allowed by your course instructors/program leadership and you use it, whether for writing, brainstorming, outlining, or critiquing, you must disclose its use, describing the model and manner in which you used the tool. For permissible uses of AI in the context of academic writing, it must be cited appropriately.
3. A focus on learning. We are in a transition period in education. While AI models might enhance the learning experience by providing knowledge assessments, quizzing, and tutoring, they might also shortcut some of the learning processes in a way that is ultimately harmful. Learning theory posits that many of our learning gains come from “desirable difficulties” – the sometimes unpleasant cognitive work that eventually leads to mastery. We recognize that we are in a new era of education, but ask that you be thoughtful about how you decide to use these tools as you embark on your lifelong journey of learning.
4. Uploading documents. Any course materials, unless explicitly disallowed by an instructor, can be uploaded into the sandbox because of its privacy protections. Please note that course materials and other copyrighted materials should not be uploaded into public-facing chatbots or AI tools such as ChatGPT or Google Gemini because of issues surrounding copyright and model training; those restrictions do not apply to the models in the Sandbox.
5. Information accuracy. Be aware that information you receive through the sandbox may not be accurate, and that this will likely vary between models. Language models encode information from a large variety of sources, many of which are unverified, and the sum total of which is not known. They are also vulnerable to hallucinations, where a model can generate information that is plausible sounding, but false.
6. A culture of experimentation. We encourage you to experiment with this technology, accepting that you are likely more advanced than your faculty. We also ask that you share your experiences with your peers, your faculty, and with us. We encourage you to use University resources on AI including the Harvard VPAL prompt library and the HMS Generative AI knowledgebase article.
7. Ongoing evaluation. We will be performing ongoing evaluation of this resource, including anonymized use statistics and both surveys and focus groups of your experiences. We will use this information to further refine the
experience around the Sandbox, including offering future trainings for students as well as new features.
TARALYN TAN, PhD
Assistant Dean for Educational Innovation and Scholarship Lecturer on Neurobiology