Northeastern University AI Policy

2. Instructors should clearly communicate to students the permitted uses of generative AI

in each course.

Expectations In Assignments: Instructors should always make it clear how the use of AI is

to be cited. Consider using an easy to spot labeling system across all assignments. The

labels below can be used or adapted for assignment instructions (other variations of this

approach can be found online).

Sample Assignment Labeling

Prohibited Use of AI is prohibited on this assignment.

Permitted Use of AI is allowed on this assignment; specific

tools and uses must be cited (Example: “AI was

used for feedback on first draft.”).

Encouraged Use of AI is encouraged on this assignment; follow

the assignment instructions for guidance and

citation requirements.

Required Use of AI is required on this assignment; follow the

assignment instructions for guidance and citation

requirements.

If AI use is allowed on assignments, instructors should consider requiring students to

disclose how they use it. A simple statement may often suffice (e.g., “I used AI to

summarize my notes”), while in other contexts providing citations or evidence of use such

as complete chat logs may be more appropriate.

Unauthorized use of aids such as, but not limited to, notes, text, the internet, artificial intelligence, chatbots, cellphones, etc., to complete any academic assignment

Unauthorized communication during an examination

Assessment and Grading: Students need to have confidence that instructors are not

outsourcing core aspects of engagement and feedback to AI. Instructors should consider

disclosing when and how they use AI in support of assessment processes.

AI systems—referring primarily, though not exclusively, to generative AI tools in this

document—can be of great value in creating new opportunities for learning and building AI

skills that students will need in the workplace.

2. Instructors should clearly communicate to students the permitted uses of generative AI

in each course.

In accordance with these beliefs, we discourage the use of generative AI early in the learning process so

that you develop expertise in research design. Later, we will encourage you to use generative AI as a

constructive collaborator, as a tool to improve your original work, and as a tool for efficiency. AI should

never be the main author or creator of any work you claim as your own.

For tasks such as writing text or code, you may be asked to start from scratch without GenAI assistance. This develops foundational skills and ensures independent thinking. ... GenAI can also be used as a programming partner. This may include generating code snippets, debugging assistance, or translating code into different languages. Always follow your instructor's guidelines on the extent and documentation of this collaboration.

1. Provide appropriate attribution when using an AI System to generate content that is included in a scholarly publication, or submitted to any body, publication or other organization that requires attribution of content authorship.

2. Regularly check the AI System’s output for accuracy and appropriateness for the required purpose, and revise/update the output as appropriate.

Generative AI may be used only if the PI understands the risks involved and adheres to the AI Policy and these Standards. PIs are responsible for signing off on the proposal and promising to do the work stated if funded. PIs should keep track of how/when they are using generative in a proposal. The PI is responsible for every part of the proposal content and should utilize generative AI in an appropriate way for their research and discipline.

Because of the potential loss of control over data submitted into AI Systems, it is important not to enter any University Confidential Information, Restricted Research Data or Personal Information (as defined by the AI Policy) into an AI System without first completing the AI Review Committee review process for your specific use-case.

4. If the AI System either (i) involves the processing of Confidential Information, Personal Information, or Restricted Research Data or (ii) takes actions that may impact the legal rights or physical safety of an individual:

o Submit the AI System and its use case for approval by the AI Review Committee (“AIRC”); and

o Submit the AI System and its use case for approval by the Office of Information Security review process for either vendor or internal systems (as applicable).

Reviewers are trusted and required to maintain confidentiality throughout the application process. Therefore, you may not use AI to assist in peer review.

Per the University’s Policy on Research Misconduct: Research Misconduct has the same definition as under federal regulations: “fabrication, falsification, plagiarism in proposing, performing, or reviewing research, or in reporting research results.” 42 C.F.R. § 93.103. It does not include honest error or honest differences in interpretations or judgments of data.

Generative AI may be used only if the PI understands the risks involved and adheres to the AI Policy and these Standards. PIs are responsible for signing off on the proposal and promising to do the work stated if funded. PIs should keep track of how/when they are using generative in a proposal. The PI is responsible for every part of the proposal content and should utilize generative AI in an appropriate way for their research and discipline.

1. Provide appropriate attribution when using an AI System to generate content that is included in a scholarly publication, or submitted to any body, publication or other organization that requires attribution of content authorship.

If AI use is allowed on assignments, instructors should consider requiring students to

disclose how they use it. A simple statement may often suffice (e.g., “I used AI to

summarize my notes”), while in other contexts providing citations or evidence of use such

as complete chat logs may be more appropriate.

Expectations In Assignments: Instructors should always make it clear how the use of AI is

to be cited.

Permitted Use of AI is allowed on this assignment; specific

tools and uses must be cited (Example: “AI was

used for feedback on first draft.”).

Unauthorized use of aids such as, but not limited to, notes, text, the internet, artificial intelligence, chatbots, cellphones, etc., to complete any academic assignment

We recommend not using AI-detection software. These tools have documented issues with accuracy and equity, and may also be trained on student work without consent. Instead of focusing on detection, we encourage instructors to design assignments that are 'AI-resistant' and have open conversations with students about appropriate AI use.

1. The university supports faculty autonomy in determining appropriate AI use in their

courses. Instructors may use AI tools to help design academic materials. However,

instructors are responsible for the quality and accuracy of the materials, including

checking outputs for accuracy and making necessary revisions prior to sharing work

with students.

Assessment and Grading: Students need to have confidence that instructors are not

outsourcing core aspects of engagement and feedback to AI. Instructors should consider

disclosing when and how they use AI in support of assessment processes.

Any faculty or staff member seeking to incorporate the use of an AI System in University Operations or Outside Professional Activities must:

1. Provide appropriate attribution when using an AI System to generate content that is included in a scholarly publication, or submitted to any body, publication or other organization that requires attribution of content authorship.

2. Regularly check the AI System’s output for accuracy and appropriateness for the required purpose, and revise/update the output as appropriate.

If the AI System either (i) involves the processing of Confidential Information, Personal Information, or Restricted Research Data or (ii) takes actions that may impact the legal rights or physical safety of an individual:

o Submit the AI System and its use case for approval by the AI Review Committee (“AIRC”); and

o Submit the AI System and its use case for approval by the Office of Information Security review process for either vendor or internal systems (as applicable).

Because of the potential loss of control over data submitted into AI Systems, it is important not to enter any University Confidential Information, Restricted Research Data or Personal Information (as defined by the AI Policy) into an AI System without first completing the AI Review Committee review process for your specific use-case.

Claude, a secure, enterprise-level generative AI platform developed by the AI company Anthropic, is now available to all active students, faculty, and staff at Northeastern University.

All active Northeastern faculty and staff now have access to Microsoft Copilot with commercial data protection. This means your prompts and the data shared in your conversations—your intellectual property—will not be used to train any public AI models.

The purpose of this policy is to establish core requirements applicable to Northeastern’s use of AI Systems in University Operations and Outside Professional Activities.

Operational components within the university may elect to publish more detailed standards implementing this policy, and are referenced in section IV below.

The following university functions / operational components have published more detailed standards implementing this Policy:

• Standards for the Use of Generative AI in Administrative Work

• Standards for the Use of AI in Research at Northeastern

• Standards for the Use of Generative AI in Teaching

If the AI System either (i) involves the processing of Confidential Information, Personal Information, or Restricted Research Data or (ii) takes actions that may impact the legal rights or physical safety of an individual:

o Submit the AI System and its use case for approval by the AI Review Committee (“AIRC”); and

o Submit the AI System and its use case for approval by the Office of Information Security review process for either vendor or internal systems (as applicable).

Claude, a secure, enterprise-level generative AI platform developed by the AI company Anthropic, is now available to all active students, faculty, and staff at Northeastern University. Access to Claude for Education, a specialized version of Claude tailored for higher education institutions, will accelerate the university’s plans to integrate AI into learning, teaching, research, and administrative operations across the global university system.