Teaching & Learning
- Brown states that instructors may decide whether and how much students may use AI in their courses, and the University does not prescribe a single AI policy for all courses
- Brown also states that unapproved AI use to complete assignments is handled under the Academic Code, including violations involving submitting work that is not produced independently or that lacks proper attribution
There is a diversity of practice among faculty regarding AI, and instructors may choose whether or not to allow the use of AI tools and to what extent. While the University is not prescribing specific AI policies, faculty should offer clear, unambiguous information about what is, and is not, allowed in their courses.
Any unapproved use of AI to complete assignments would be covered by Brown’s Academic Code and Academic Code, Graduate Student Edition.
Academic achievement is ordinarily evaluated on the basis of work that a student produces independently. Students who submit academic work that uses others’ ideas, words, research, or images without proper attribution and documentation are in violation of the academic code.
- The sources provided do not define an exam- or quiz-specific AI rule university-wide, beyond stating that unapproved AI use would be covered by the Academic Code
- Brown’s provost communication indicates that AI permissions are set by instructors and that the University does not prescribe specific AI policies, which would include assessment contexts at the course level
There is a diversity of practice among faculty regarding AI, and instructors may choose whether or not to allow the use of AI tools and to what extent. While the University is not prescribing specific AI policies, faculty should offer clear, unambiguous information about what is, and is not, allowed in their courses.
Any unapproved use of AI to complete assignments would be covered by Brown’s Academic Code and Academic Code, Graduate Student Edition.
- The provided sources do not define a university-wide policy specifically addressing AI for non-graded personal study or tutoring outside course rules
- Brown indicates that instructors may choose whether to allow AI tools and to what extent, and provides examples of faculty encouraging students to use tools like ChatGPT in a course context
There is a diversity of practice among faculty regarding AI, and instructors may choose whether or not to allow the use of AI tools and to what extent.
In my Methods in Public Humanities (PHUM2020) course, I am, with some trepidation, encouraging students to use ChatGPT and similar tools. These new tools will be useful to them in their work after Brown, and we should help them learn to use them wisely.
- The provided sources do not define a separate university-wide student policy specifically for AI code generation in coursework beyond the Academic Code applicability for unapproved AI use to complete assignments
- Brown’s provost communication states that instructors may decide whether AI tools are allowed in their courses and that the University is not prescribing specific AI policies, which would cover programming assignments at the course level
There is a diversity of practice among faculty regarding AI, and instructors may choose whether or not to allow the use of AI tools and to what extent. While the University is not prescribing specific AI policies, faculty should offer clear, unambiguous information about what is, and is not, allowed in their courses.
Any unapproved use of AI to complete assignments would be covered by Brown’s Academic Code and Academic Code, Graduate Student Edition.
There is no shortage of public analysis regarding the ways in which the use of generative artificial intelligence (AI) tools (such as ChatGPT) – which are open-access tools that can generate realistic text, computer code, and other content in response to prompts from the user – provides both challenges and opportunities in higher education.
Research
- It also states that when AI is used, human authors remain fully responsible for the accuracy and integrity of content produced with AI assistance and for verification of outputs
- Brown’s research authorship guidance requires transparent disclosure of AI tool use in the research or writing process, including drafting, revising, or polishing written content, and requires authors to describe the nature and extent of AI use in appropriate sections of a publication
The use of AI tools in the research or writing process must be disclosed transparently. This includes, but is not limited to:
Text generation or editing: Use of AI to draft, revise, or polish written content.
Authors must describe the nature and extent of AI use in the methods, acknowledgments, or a dedicated disclosure statement, following the requirements of the relevant journal, funder, and Brown University.
When AI is used, human authors remain fully responsible for:
The accuracy and integrity of all content produced with AI assistance.
Verification of outputs, including ensuring that generated text, data, and images are original, non-misleading, and properly sourced.
- Brown’s OIT guidance for generative AI as a research tool prohibits sharing Level 2 or Level 3 data with AI tools
- Brown’s research authorship guidance requires transparent disclosure of AI use for data analysis and data interpretation as part of the research process
The use of AI tools in the research or writing process must be disclosed transparently. This includes, but is not limited to:
Data analysis: Use of machine learning models or AI-powered software for data interpretation.
Do not share any Level 2 or 3 data, or any algorithms or code artifacts that are proprietary, with AI tools.
- Brown’s provost communication also points to risks of plagiarism and states that unapproved AI use to complete assignments would be covered by the Academic Code and the Graduate Student Academic Code
- Brown’s research authorship guidance states that AI use must be disclosed transparently and that human authors remain fully responsible for the accuracy and integrity of AI-assisted content, including verifying outputs and avoiding inappropriate uses such as fabricated references or misrepresenting results
The use of AI tools in the research or writing process must be disclosed transparently.
When AI is used, human authors remain fully responsible for:
The accuracy and integrity of all content produced with AI assistance.
Avoiding inappropriate use, such as generating fabricated references, misrepresenting results, or failing to attribute content properly.
One of the most common concerns about AI is the potential for plagiarism, or students using the system to do work that they then present as something they created without AI assistance. Any unapproved use of AI to complete assignments would be covered by Brown’s Academic Code and Academic Code, Graduate Student Edition.
Academic Integrity
- Brown’s research authorship guidance requires transparent disclosure of AI use in research or writing processes and requires authors to describe the nature and extent of AI use in methods, acknowledgments, or a dedicated disclosure statement
- Brown’s provost communication advises that if generative AI is used for course assignments, academic work, or published writing, writers should pay special attention to acknowledging and citing AI output, and it points to library guidelines for citing AI-generated content
The use of AI tools in the research or writing process must be disclosed transparently.
Authors must describe the nature and extent of AI use in the methods, acknowledgments, or a dedicated disclosure statement, following the requirements of the relevant journal, funder, and Brown University.
If you choose to use generative AI tools for course assignments, academic work, or other forms of published writing, you should give special attention to how you acknowledge and cite the output of those tools in your work. The Library has compiled general guidelines for citing AI-generated content, as well as more specific guidance from the three major style guides.
- The provided sources do not define an institutional position on AI detection tools or specific AI-detection enforcement methods
- Brown’s Academic Code pages state that violations of the Academic Code entail penalties up to suspension, dismissal, or expulsion, and the provost communication states that unapproved AI use to complete assignments is covered by the Academic Code (and the Graduate Student Academic Code)
Infringement of the academic code entails penalties ranging from reprimand to suspension, dismissal, or expulsion from the University.
Any unapproved use of AI to complete assignments would be covered by Brown’s Academic Code and Academic Code, Graduate Student Edition.
Infringement of the Academic Code entails penalties ranging from reprimand to suspension, dismissal or expulsion from the University.
Institutional & Administrative
- Brown’s provost communication states that instructors may decide whether and to what extent AI tools are allowed in their courses, and asks faculty to provide clear information about what is and is not allowed
- Brown’s OIT guidance on protecting information when using AI tools states that individuals are responsible for content they produce, share, or publish using AI tools and that AI-generated content should be extensively reviewed before sharing or publishing
There is a diversity of practice among faculty regarding AI, and instructors may choose whether or not to allow the use of AI tools and to what extent. While the University is not prescribing specific AI policies, faculty should offer clear, unambiguous information about what is, and is not, allowed in their courses.
One of the most popular uses of AI tools is to help you quickly create new context-aware content, including communications, documentation, images, and software code. But ultimately you are responsible for any content you produce, share, or publish, even if you used an AI tool to help create it.
Be mindful of AI’s limitations, and extensively review any AI-generated content before sharing it with others or publishing it.
- Brown’s OIT guidance for generative AI as a research tool prohibits sharing Level 2 or Level 3 data (and proprietary algorithms/code artifacts) with AI tools
- Brown’s data security review process states that OIT must conduct or confirm a data security review for contracts involving software/services that store or access Brown or research participant data
- Brown also provides institutionally accessible AI services (Google Gemini Chat and NotebookLM) and states these can be used with data classified as Risk Level 3, contrasting them with consumer AI services where Brown does not have agreements
Do not share any Level 2 or 3 data, or any algorithms or code artifacts that are proprietary, with AI tools.
The two Artificial Intelligence (AI) services Google Gemini Chat and NotebookLM are now accessible at no cost to Brown. These services can be used with data classified as Risk Level 3 (unlike consumer AI services such as ChatGPT, DeepSeek, and Claude with whom Brown does not have agreements).
OIT either needs to conduct a data security review or confirm that the vendor has been vetted by an OIT approved standardized security assessment vendor (FedRAMP) for any contract associated with software or a service that stores or has access to Brown or research participant data.
- Brown’s provost communication describes institution-level efforts to align AI use with Brown’s values, encourages experimentation, and describes upcoming campus-wide discussions and working groups related to AI
- Brown’s OIT guidance notes that Brown’s current technology policies address AI and that experts across Brown are tracking developments and adopting policies, standards, procedures, and guidelines to support productive, secure, compliant, and ethically appropriate use
As we identify the ways in which AI can enhance academic activities for faculty and student success and administrative activities for staff, we must also ensure these tools are understood and used appropriately and ethically.
Beginning in the fall, the Data Science Institute will partner with the Office of the Provost for “Conversations on AI and our data-driven society,” a series of monthly campus-wide discussions about the impact of AI on how we live, work, and educate the next generation The Library has also planned weekly discussions and working groups to address various issues surrounding AI from different perspectives.
AI technology is evolving rapidly. However, Brown’s current technology policies address the use of AI. Experts across Brown are tracking AI system developments, and adopting policies, standards, procedures, and guidelines to help support our community to leverage this evolving technology in a productive, secure, compliant, and ethically appropriate manner.
DocuMark: Responsible AI Use for Academic Integrity
Knowing your institution's AI policy is step one. DocuMark helps enforce it fairly by empowering universities to manage AI-generated content, prevent cheating, and support student writing through responsible AI use.
Common Questions About Brown University's AI Policies
Brown University has defined AI policies in 12 of 12 categories, with an overall coverage score of 100%.
Brown’s research authorship guidance requires transparent disclosure of AI use in research or writing processes and requires authors to describe the nature and extent of AI use in methods, acknowledgments, or a dedicated disclosure statement. Brown’s provost communication advises that if generative AI is used for course assignments, academic work, or published writing, writers should pay special attention to acknowledging and citing AI output, and it points to library guidelines for citing AI-generated content.
Brown’s Academic Code pages state that violations of the Academic Code entail penalties up to suspension, dismissal, or expulsion, and the provost communication states that unapproved AI use to complete assignments is covered by the Academic Code (and the Graduate Student Academic Code). The provided sources do not define an institutional position on AI detection tools or specific AI-detection enforcement methods.
Brown’s OIT guidance for generative AI as a research tool prohibits sharing Level 2 or Level 3 data (and proprietary algorithms/code artifacts) with AI tools. Brown also provides institutionally accessible AI services (Google Gemini Chat and NotebookLM) and states these can be used with data classified as Risk Level 3, contrasting them with consumer AI services where Brown does not have agreements. Brown’s data security review process states that OIT must conduct or confirm a data security review for contracts involving software/services that store or access Brown or research participant data.