Teaching & Learning
- SLU also provides syllabus templates showing that instructors may prohibit AI entirely or set course-specific allowances
- Use of AI for coursework and assignments is not uniformly set at the university level; it is governed by instructor authorization and course-level guidance
- If AI or other technology is not authorized by the instructor, using it to complete assignments is treated as cheating, and submitting AI-prepared work as one’s own without proper citation is treated as plagiarism
• Using assistance, notes, aids, artificial intelligence or other technology, cell phones,
calculators, translation software, or internet-based applications not authorized by the
instructor in taking quizzes or examinations or to complete assignments.
• Submitting as the student’s own, any work that has been prepared, either entirely or in
part, by another person, group, commercial firm, artificial intelligence, or by other
technology without proper citation.
The following four statements regarding the allowance or disallowance of the use
of generative AI may offer different templates for use in course syllabi.
Generative AI, including but not limited to [ChatGPT, Gemini, Microsoft Copilot,
Midjourney, DALL-E or Github Copilot] may not be used for work in this class.
- AI use during exams, quizzes, and formal assessments is prohibited unless the instructor authorizes it
- The academic integrity policy explicitly classifies unauthorized AI use in quizzes or examinations as cheating, defining cheating as the use of unauthorized assistance to gain an advantage over others and/or failure to comply with directions relating to the conduct of a formal examination or assessment
Cheating is the use of unauthorized assistance to gain an advantage over others, and/or a failure to comply with any reasonable direction or instruction of an officer, employee or agent of the University relating to the conduct of a formal examination or assessment.
• Using assistance, notes, aids, artificial intelligence or other technology, cell phones, calculators, translation software, or internet-based applications not authorized by the instructor in taking quizzes or examinations or to complete assignments.
- SLU does not set a blanket university-wide student entitlement to use AI for study support; course use is left to faculty decisions and communicated in course guidelines
- Faculty resource guides describe possible learning benefits of generative AI, including rough drafts, outlines, idea generation, and simplifying difficult text, but these are advisory materials rather than mandatory student permissions
As we come to our decisions regarding whether we should employ generative artificial
intelligence (AI) into our courses, an intentional and overt set of guidelines will be important
for us and for our students. When or if use of AI is allowed, under what circumstances, on one
assignment or another, and to what extent will need to be communicated clearly to prevent
students running afoul of our intentions and keeping within our expectations for their work.
• The use of generative AI may be helpful for students to produce rough drafts, outlines,
or ideas about a topic.
• Generative AI can simplify dense or complicated text, making it easier to understand,
which for non-native English speakers could save precious time which would otherwise
be spent trying to translate and decipher these texts.
- Programming-related AI use is left to instructor or course-level rules rather than a single university-wide permission
- SLU’s sample syllabus statement explicitly lists GitHub Copilot among generative AI tools that an instructor may prohibit, and the academic integrity policy treats unauthorized AI use to complete assignments as cheating
Generative AI, including but not limited to [ChatGPT, Gemini, Microsoft Copilot,
Midjourney, DALL-E or Github Copilot] may not be used for work in this class.
• Using assistance, notes, aids, artificial intelligence or other technology, cell phones,
calculators, translation software, or internet-based applications not authorized by the
instructor in taking quizzes or examinations or to complete assignments.
Generative AI - Generative AI is a broad label that’s used to describe any type of artificial intelligence (AI) that can be used to create new text, images, video, audio, code or synthetic data. ChatGPT is a type of generative AI.
Research
- SLU also warns against uploading unpublished manuscripts into generative AI tools
- Researchers may use AI in research writing only with transparency and human accountability
- AI use in research must be disclosed, AI-generated research output must be clearly identified, authorship must reflect substantive human contributions, and researchers remain responsible for the accuracy of AI-created content
### For Faculty Researchers (Research)
* Transparency in Methods and Authorship: Be transparent regarding AI use in research, including describing methods, acknowledgements, or elsewhere, as appropriate. AI-generated research output must be clearly identified, and authorship must reflect substantive human contributions.
Researchers must comply with the terms of any federal, state or private grants with regards to AI use or allowability, as well as any written policies outlined by scientific or other journals where research output is published.
* Accuracy Responsibility: Researchers are responsible for the accuracy of any content created by AI that is included in any research output. Use caution, as AI has been known to generate non-existent citations or images for experiments that were never conducted.
This includes unpublished manuscripts or funding proposals that researchers may be asked to peer review, as some funding agencies (e.g., NIH, NSF) prohibit using generative AI for peer review.
- SLU does not provide a detailed AI policy for data analysis methods, but it does set data-handling limits for research use
- Researchers are told to avoid uploading unpublished research data or confidential information into generative AI tools, and AI use in sensitive research areas may require IRB or other research compliance approvals
* Unpublished Research Data: Avoid uploading or using as input any unpublished research data, including data provided by or pertaining to researchers or research subjects into generative AI tools. Doing so may lead to the disclosure of unpublished work, impede future intellectual property protection, or create privacy violations.
* Confidential Data: Avoid uploading, or using as input, confidential information belonging to SLU or other individuals or organizations. Generative AI tools may not provide protection for confidential information, and their use could create the potential to breach confidential contractual commitments. Examples of confidential information include unpublished manuscripts, research funding proposals, and personal information related to research subjects.
* IRB Approval: The application of AI in sensitive research areas (e.g., biomedical, social sciences) may require Institutional Review Board (IRB) or other research compliance committee approvals, as applicable.
- SLU requires researchers using AI to comply with institutional and external research integrity rules
- The guidelines also note that some funding agencies prohibit generative AI in peer review of manuscripts or funding proposals
- AI use in research must follow federal and institutional research misconduct policies, grant terms, journal policies, and, where applicable, IRB requirements
* Compliance and Integrity: Researchers utilizing AI must comply with federal and institutional research integrity policies, including the responding to allegations of research misconduct policy.
Researchers must comply with the terms of any federal, state or private grants with regards to AI use or allowability, as well as any written policies outlined by scientific or other journals where research output is published.
This includes unpublished manuscripts or funding proposals that researchers may be asked to peer review, as some funding agencies (e.g., NIH, NSF) prohibit using generative AI for peer review.
* IRB Approval: The application of AI in sensitive research areas (e.g., biomedical, social sciences) may require Institutional Review Board (IRB) or other research compliance committee approvals, as applicable.
Academic Integrity
- These requirements appear in both the university-wide AI guidelines and in faculty-facing syllabus resources
- In course settings, sample syllabus language directs students to identify AI-aided work, include a brief narrative of how AI was used, and fact-check AI-generated content
- SLU requires disclosure when AI is used to produce written materials or work product, and it requires proper citation when AI-generated material is quoted, paraphrased, or submitted in academic work
* Transparency and disclosure: Usage of AI tools in academic work, research, or administrative activities must be clearly disclosed. The disclosure should be transparent, prominent, and sufficient to allow others to understand the role AI played in the work product.
* Disclose the use of generative AI tools: SLU community members who leverage generative AI to produce any written materials or other work product must disclose that those materials and that work product is based on or derives from the use of generative AI. Always be transparent if you are relying on the output of a generative AI tool.
• Directly presenting the written, artistic, or spoken work generated or created by someone other than the student, by artificial intelligence, or by other technology without quotation marks or indented quotations and without proper citation to the source.
• Paraphrasing or incorporating the ideas, concepts, arguments, observations, images, objects, music, or statements generated or created by someone other than the student, by artificial intelligence, or by other technology without proper citation of the source.
Please include a brief narrative relating the ways you utilized generative AI in your work. Proper citation format for generative AI use can be found here [APA, MLA, etc]. Any work generated with AI should be fact checked to ensure accuracy. You are responsible for the content of your work.
- SLU cautions faculty that AI detection tools are unreliable and carry risks of misidentification, so their use requires careful consideration before being applied to student work
- Unauthorized AI use is enforceable through existing academic misconduct categories: using AI without instructor authorization constitutes cheating, and submitting AI-generated work without permission or proper citation constitutes plagiarism under the academic integrity policy
* AI Detection Tools: Be aware that AI detection tools carry risks of misidentification and have not been widely proven to detect AI use. Careful consideration should be given when deciding if the use of these tools is appropriate for assessing student work.
• Using assistance, notes, aids, artificial intelligence or other technology, cell phones, calculators, translation software, or internet-based applications not authorized by the instructor in taking quizzes or examinations or to complete assignments.
Plagiarism is the presentation of content as if the content were the student's own without proper citation or permission. Examples include: cutting and pasting from another source, incorrect or missing citations, or using generative AI to create work without the instructor's permission.
Institutional & Administrative
- Automated administrative decision-making must include human review and appeal
- SLU permits faculty and staff to use AI in teaching and administrative settings, but requires responsible use, human oversight, and compliance with institutional standards
- Instructors should not use generative AI in teaching activities in ways that violate policy, and administrative staff should not plagiarize or share confidential or protected data with AI providers
* Human oversight: AI should support, not replace, human decision-making in critical academic and administrative functions.
* Responsible Employment: Instructors should not inappropriately employ GAI in their teaching activities, including the design of courses, syllabi development, assignment development, course materials development, or the formative and summative assessment of student learning, in ways that violate institutional standards and policies.
* Human Review and Appeal: Automated decision-making processes must include a mechanism for human review and appeal.
* Responsible Use of AI Tools: Staff should not inappropriately employ GAI in their work, plagiarize by submitting work that is not their own creation, or inappropriately share confidential or protected data with a GAI provider.
- SLU sets explicit data protection restrictions for AI use across the community
- Administrative AI implementations must go through normal contract approval processes, ITS review, and relevant university approvals including the University AI Committee, Office of General Counsel, and Compliance
- Restricted-use data may not be entered into generative AI tools, and confidential data or personal information may only be entered when validated contract language and ITS-approved security controls are in place; for SLU Madrid, DPO approval is also required
* Privacy and data security: AI use must comply with SLU data protection policies and relevant laws (e.g., FERPA, HIPAA, GDPR).
* Do not input restricted use data: SLU community members must not input any restricted use data into generative AI tools.
* Do not input confidential data: SLU community members must not input any confidential data into generative AI tools, except when permitted by validated contract language and security controls (approved by Information Technology Services (ITS)). SLU Madrid students, faculty and staff must also receive approval from the data protection officer (DPO). The DPO may be contacted at dpo-madrid@slu.edu.
* Do not input personal information: SLU community members must not input any personal information about SLU employees, students, faculty, or other stakeholders into a generative AI tool except when permitted by validated contract language and security controls (approved by ITS). SLU Madrid students, faculty, and staff must also receive approval from the data protection officer (DPO).
* Auditing for Fairness: AI systems used in critical administrative functions such as admissions, hiring, student services, and decision-making must be regularly audited for fairness and accuracy. The implementation of such tools must go through the normal contract approval processes and be reviewed by ITS for appropriate contract language and security controls.
* Implementation Safeguards: AI tools may be implemented by an administrative unit when appropriate safeguards are in place, their use aligns with guidance from the University AI Committee, and approval is received from relevant university authorities (e.g., ITS, Office of General Counsel, Compliance).
- SLU has university-level AI guidelines that set overarching principles for ethical use, disclosure, privacy, human oversight, and bias mitigation
- The guidelines also reference governance through a University AI Committee, whose guidance is part of the approval pathway for administrative AI implementation
This page provides detailed guidelines around the use of artificial intelligence to help the members of the Saint Louis University community navigate the uses and recommended practices of artificial intelligence tools on our campuses.
* Ethical use: AI must be used in ways that uphold academic integrity, fairness and human dignity.
* Transparency and disclosure: Usage of AI tools in academic work, research, or administrative activities must be clearly disclosed. The disclosure should be transparent, prominent, and sufficient to allow others to understand the role AI played in the work product.
* Privacy and data security: AI use must comply with SLU data protection policies and relevant laws (e.g., FERPA, HIPAA, GDPR).
* Human oversight: AI should support, not replace, human decision-making in critical academic and administrative functions.
* Non-discrimination and bias mitigation: AI technologies must be assessed for potential biases and actively designed to promote equity.
* Implementation Safeguards: AI tools may be implemented by an administrative unit when appropriate safeguards are in place, their use aligns with guidance from the University AI Committee, and approval is received from relevant university authorities (e.g., ITS, Office of General Counsel, Compliance). Implementation should adhere to existing contract approval processes.
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 Saint Louis University's AI Policies
Saint Louis University has defined AI policies in 12 of 12 categories, with an overall coverage score of 100%.
SLU requires disclosure when AI is used to produce written materials or work product, and it requires proper citation when AI-generated material is quoted, paraphrased, or submitted in academic work. In course settings, sample syllabus language directs students to identify AI-aided work, include a brief narrative of how AI was used, and fact-check AI-generated content. These requirements appear in both the university-wide AI guidelines and in faculty-facing syllabus resources.
SLU cautions faculty that AI detection tools are unreliable and carry risks of misidentification, so their use requires careful consideration before being applied to student work. Unauthorized AI use is enforceable through existing academic misconduct categories: using AI without instructor authorization constitutes cheating, and submitting AI-generated work without permission or proper citation constitutes plagiarism under the academic integrity policy.
SLU sets explicit data protection restrictions for AI use across the community. Restricted-use data may not be entered into generative AI tools, and confidential data or personal information may only be entered when validated contract language and ITS-approved security controls are in place; for SLU Madrid, DPO approval is also required. Administrative AI implementations must go through normal contract approval processes, ITS review, and relevant university approvals including the University AI Committee, Office of General Counsel, and Compliance.