Artificial Intelligence (AI) Policy

Students are expected not to use GenAI tools for any work in this course, apart from those tools which are so embedded in the applications or systems they use (such as spellcheck or google search) that they cannot be avoided. Optional embedded AI Assistants should not be used for core learning activities and assignments (e.g., revising documents, summarizing readings or conducting literature searches).

ENGN 1860: Advanced Fluid Mechanics

Professor Kenny Breuer

Using AI is not discouraged, but should be used with caution. There are a few concerns:  

1. Using AI as an additional source to help you understand the material or to help you prepare for an exam is great, but sometimes (often) AI gets it wrong, so make sure that you check the AI for accuracy.
2. Using AI to proof-read or to format a document is fine, but using AI to generate content for an assignment is terrible for your learning, and is strictly prohibited.
3. If you use AI, you must include either a specific citation (as you would cite a paper or textbook) or document your usage (prompt history etc) with a footnote or appendix for more extensive uses.

IMPORTANT: Be careful that you understand what the AI tells you - learning requires doing, and relying on the AI can remove the “doing” part. Make sure you maintain the “human-in-the-loop”

You are personally responsible for everything you submit.  If asked, you must be able to defend and explain your work in a verbal face-to-face conversation.  People may be called on in class or in private to present and/or explain their submissions.

Artificial Intelligence (AI) Policy

Many students are looking for ways to enhance, supplement, or speed up their learning with GenAI tools. However, many uses of GenAI can undermine students’ learning and instructors’ ability to assess students’ learning and give feedback for growth. Permitted GenAI use varies by assignment in this course with specific guidelines. Unless a specific GenAI use is explicitly permitted, students should consult with me before engaging in this kind of GenAI usage.

DSIO 2000: Technical Foundation for Data Science Success

Professor Linda Clark

The emergence of AI tools presents both exciting opportunities and important considerations for academic work. Our approach to AI usage in this course is aligned with the online Data Science Program AI Philosophy, and is designed both to promote academic integrity and to foster critical thinking. All AI usage in this course must align with the policies defined in the academic code and the student code.

By enrolling in this course you have established the goal of learning the basic foundational skills of data science. Given this intention, LLMs can do the math and coding assignments, but instead of you learning the material, the LLM will be doing the material. Additionally, in the frequent situations where the LLM code does not work, you will need to figure out how to debug your code. If you have used a code generator to generate your code and do not understand how to code, you will not learn the skills necessary to know how to debug your code.

If you ask for coding help and you cannot explain your code, the course staff will not be able to assist you.  In other words, course staff will not debug LLM code. 

Therefore, depending on what you want to get out of this course, you may choose to use the assistance of LLMs or not. Note that you must attribute the authorship of the work to the AI tool if you choose to use it. Situations where there is no attribution may result in conduct-related offenses of Academic Integrity. For assistance in citation, please see the Brown University Library guide. 

When reviewing your course AI policy, the GAITL Committee strongly encourages instructors to communicate the rationale behind their course AI policy. Communicating your “why”  helps students understand the values and knowledge that inform your stance on AI in the course. While the “why” may not appear in your syllabus statement, communicating the “why” when discussing your AI policy and specific assignments is a powerful way to build trust with students in your course.

The AI Policy Explorer is a basic web tool and does not utilize GenAI tools. However, GenAI tools were used to create the tool. The GAITL Committee used Gemini 3.6 (Thinking mode) to generate 114 course-level learning outcomes for undergraduate and graduate level courses in the arts, humanities, languages, life sciences, physical sciences and social sciences with additional focus on writing intensive, advanced reading, problem-solving, and quantitative reasoning courses. After reviewing outcomes and making revisions to generalize some statements, Gemini was directed to generate a limited list of prohibited uses of GenAI tools based on the rationale that the uses would undermine student learning or make it impossible to assess student learning. After the committee reviewed the 15 prohibitions generated using Gemini, three additional prohibitions were added including a simple “No AI” policy. Gemini was then directed to review the learning outcomes again and generate a list of GenAI uses that could support student learning and enhance accessibility for a diverse range of learners. This resulted in 19 allowed use cases. For design and programming, Claude Code was used to create the web tool through an iterative process.