Policy presence
Northeastern University has 4 source-backed public claims for policy presence; deterministic analysis status: unclear.
Boston, United States
Northeastern University
Northeastern University is listed as QS 2026 rank 384. Northeastern University has 7 source-backed AI policy claim records from 5 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
Northeastern University is listed as QS 2026 rank 384. Northeastern University has 7 source-backed AI policy claim records from 5 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Citation-ready summary
As of this public record, University AI Policy Tracker lists Northeastern University as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 7 source-backed claims, including 7 reviewed claims, from 5 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/northeastern-university.json. The entity-level confidence is 96%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.
Policy signals in this record
- Evidence includes Security review claims.
- Evidence includes AI tool treatment claims.
- Evidence includes Research claims.
- Evidence includes Teaching claims.
- Evidence includes Privacy claims.
- Evidence includes Academic integrity claims.
- No specific AI service name is highlighted by the current public claim text.
- Disclosure, acknowledgment, citation, or attribution language appears in the public claim text.
Review: Agent reviewed
This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.
This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.
Policy profile
Deterministic source-backed dimensions derived from this record's public claims.
Review: Machine candidate
Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.
Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.
AI disclosure
Northeastern University has 1 source-backed public claim for ai disclosure; deterministic analysis status: unclear.
Coursework
Northeastern University has 3 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
Northeastern University has 3 source-backed public claims for exams; deterministic analysis status: required.
Privacy and data entry
Northeastern University has 5 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
Northeastern University has 1 source-backed public claim for academic integrity; deterministic analysis status: required.
Approved tools
Northeastern University has 4 source-backed public claims for approved tools; deterministic analysis status: restricted.
Named AI services
Northeastern University has 2 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
Northeastern University has 5 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
Northeastern University has 3 source-backed public claims for research guidance; deterministic analysis status: restricted.
Security and procurement
Northeastern University has 3 source-backed public claims for security and procurement; deterministic analysis status: restricted.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
Evidence-backed claims
7 reviewed evidence-backed public claim
Security Review
Northeastern Policy 125 says faculty or staff seeking to use an AI system in University Operations must submit the system and use case for AI Review Committee and Office of Information Security approval when the system processes confidential information, personal information, restricted research data, or may affect legal rights or physical safety.
Review: Agent reviewed
Normalized value: ai_systems_processing_sensitive_data_or_safety_rights_use_cases_require_airc_and_ois_review_for_university_operations
Original evidence
Evidence 1If 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: Submit the AI System and its use case for approval by the AI Review Committee; and Submit the AI System and its use case for approval by the Office of Information Security review process.
Ai Tool Treatment
Northeastern Policy 125 says faculty or staff seeking to use an AI system in University Operations or covered outside professional activities must provide required attribution, check AI outputs for accuracy and appropriateness, and validate anti-bias testing when the system processes personal information or affects legal rights or physical safety.
Review: Agent reviewed
Normalized value: policy_requires_attribution_accuracy_review_and_bias_validation_for_certain_ai_system_uses
Original evidence
Evidence 1Any faculty or staff member seeking to incorporate the use of an AI System in University Operations or Outside Professional Activities must: Provide appropriate attribution ... Regularly check the AI System's output for accuracy and appropriateness ... If the AI System involves the processing of Personal Information or takes actions that may impact the legal rights or physical safety of an individual, validate that it is regularly tested.
Research
Northeastern research standards say members of the Northeastern community conducting research are expected to follow the university AI Policy, complete AI Review Committee review when research uses an AI system to process confidential information, restricted research data, or personal information, and communicate permitted generative AI uses within project teams based on research activity and sponsor guidelines.
Review: Agent reviewed
Normalized value: research_ai_use_expectations_include_ai_policy_airc_review_for_sensitive_data_and_project_team_communication
Original evidence
Evidence 1The University expects all members of the Northeastern community conducting research to follow the requirements set forth in the university AI Policy and to: Complete the AI Review Committee review process if your research involves using an AI System to process Confidential Information, Restricted Research data or Personal Information ... Follow guidelines set by the funding agency or publisher ... Communicate with fellow lab and project team members about the permitted uses of generative AI.
Security Review
Northeastern teaching and learning standards state that using generative AI to grade open-ended student responses requires AI Review Committee review because it could affect student legal rights and may involve sensitive personal information and risk of illegal bias or discrimination.
Review: Agent reviewed
Normalized value: generative_ai_grading_open_ended_student_responses_requires_airc_review
Original evidence
Evidence 1Because it could impact the legal rights of students and may involve sensitive personal information and risk of illegal bias and discrimination, any use of generative AI to grade open-ended student responses, including written or multimodal work products, requires review by the AI Review Committee.
Teaching
Northeastern teaching and learning standards say instructors should clearly communicate permitted generative AI uses to students in the syllabus, assignment guidelines, and verbally in class.
Review: Agent reviewed
Normalized value: instructors_should_communicate_permitted_student_ai_uses_in_syllabus_assignment_guidelines_and_class
Original evidence
Evidence 1Instructors should clearly communicate to students the permitted uses of generative AI in coursework. This communication should be written in the syllabus, assignment guidelines, and conveyed verbally in class.
Privacy
Northeastern administrative AI standards say administrative users should use approved AI environments for data or use cases requiring AI Review Committee approval and should not enter confidential, restricted research, or personal information into an AI system that has not been reviewed and approved by the AI Review Committee and Office of Information Security.
Review: Agent reviewed
Normalized value: administrative_ai_use_restricts_sensitive_data_to_reviewed_approved_ai_systems
Original evidence
Evidence 1Use approved AI environments only when processing data or involving use-cases that require AI Review Committee approval ... Do not enter any confidential, restricted research, or personal information into an AI system that has not been reviewed and approved by the AI Review Committee and the Office of Information Security.
Academic Integrity
Northeastern's student AI guide advises students to check each syllabus, ask professors when an AI policy is unclear, use AI as a study partner rather than a substitute for their own thinking, and avoid using AI when assignment guidelines direct independent work.
Review: Agent reviewed
Normalized value: student_guide_advises_syllabus_checking_transparency_and_no_ai_when_independent_work_required
Original evidence
Evidence 1Every class is different ... Check each syllabus carefully. Ask your professors if you're unsure or if an AI policy is unclear ... The key is using AI as a study partner, not as a substitute for your own thinking ... Resist the temptation to use it when assignment guidelines direct you to work independently.
Candidate claims
0 machine or needs-review claim
Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.
Official sources
5 source attribution
AI at Northeastern: A Student Guide
learning.northeastern.edu
Policy on the Use of Artificial Intelligence Systems
policies.northeastern.edu
Standards and Recommendations for the Use of Generative AI in Teaching and Learning at Northeastern
provost.northeastern.edu
Standards for the Use of Artificial Intelligence (AI) in Administrative Work at Northeastern
uds.northeastern.edu
Standards for the Use of Artificial Intelligence in Research at Northeastern
compliance.research.northeastern.edu
Change log
Source-check timeline and diff-style claim/evidence preview.
View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.
Corrections and missing evidence
Corrections create review tasks and do not directly change this public record.
If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.