Policy presence
Washington University in St. Louis has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.
St. Louis, United States
Washington University in St. Louis
Washington University in St. Louis is listed as QS 2026 rank 167. Washington University in St. Louis has 8 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
Washington University in St. Louis is listed as QS 2026 rank 167. Washington University in St. Louis has 8 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 Washington University in St. Louis as an agent-reviewed AI policy record last checked on May 15, 2026 and last changed on May 15, 2026. The record contains 8 source-backed claims, including 8 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/washington-university-in-st-louis.json. The entity-level confidence is 98%. 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 Privacy claims.
- Evidence includes Academic integrity claims.
- Evidence includes Procurement claims.
- Evidence includes AI tool treatment claims.
- Evidence includes Teaching claims.
- Evidence includes Security review claims.
- Evidence includes Source status claims.
- Named AI services detected in public claims: DeepSeek.
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
Washington University in St. Louis has 2 source-backed public claims for ai disclosure; deterministic analysis status: recommended.
Coursework
Washington University in St. Louis has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
Washington University in St. Louis has 4 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
Washington University in St. Louis has 2 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
Washington University in St. Louis has 2 source-backed public claims for academic integrity; deterministic analysis status: required.
Approved tools
Washington University in St. Louis has 3 source-backed public claims for approved tools; deterministic analysis status: restricted.
Named AI services
Washington University in St. Louis has 4 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
Washington University in St. Louis has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
No source-backed public claim about research AI use is present in this profile.
The current public tracker record does not contain claim evidence about research use, publication ethics, research data, grants, or human-subjects compliance.
Security and procurement
Washington University in St. Louis has 2 source-backed public claims for security and procurement; deterministic analysis status: required.
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
8 reviewed evidence-backed public claim
Privacy
WashU IT guidance says users should not enter Washington University or secure data, including deidentified healthcare data, into publicly accessible non-protected AI tools.
Review: Agent reviewed
Normalized value: no_secure_data_in_public_ai_tools
Original evidence
Evidence 1The university supports and encourages the responsible and secure exploration of AI tools. When using any publicly accessible, non-protected AI tools, it is vitally important that you do not enter any Washington University or secure data, including deidentified healthcare data of any kind, into these platforms.
Localized display only
WashU IT warns users not to enter university or secure data into public non-protected AI tools.
Academic Integrity
WashU student-facing AI guidance tells students to check the instructor and syllabus about whether and how AI tools may be used for classwork, and says that if no explicit policy is outlined, it is better to assume AI use is banned.
Review: Agent reviewed
Normalized value: students_should_clarify_class_ai_policy
Original evidence
Evidence 1In regard to your classwork, please check with your instructor and the syllabus about whether and how you can use ChatGPT and other tools to help you with your classwork. Ask the instructor how AI tools are or are not to be used in the class. There is no set policy across instructors as they are also figuring out how AI fits into the future of their disciplines and how best to teach you the skills needed for future professions. If there is no explicit policy outlined, it is better to assume that AI use is banned.
Localized display only
The CTL student guide says students should check their instructor and syllabus, and assume AI use is banned if no explicit policy is outlined.
Academic Integrity
WashU CTL student guidance says students should not represent AI-tool output as their own work and should cite AI contributions when using AI tools.
Review: Agent reviewed
Normalized value: ai_output_requires_attribution_not_own_work
Original evidence
Evidence 1Never take the output from AI tools and represent it as your own work. This not only violates the Terms of Use for most AI tools, creating a legal issue, but is also clearly and unarguably plagiarism. To avoid plagiarism when you use AI tools, make sure you cite its contribution accordingly when you use it.
Localized display only
The CTL guide warns not to submit AI output as one's own work and tells students to cite AI contributions.
Procurement
WashU IT AI purchasing guidance says an Office of Information Security Vendor Security Review is required when an AI tool has not yet been approved and the user intends to use or purchase it.
Review: Agent reviewed
Normalized value: unapproved_ai_tool_vendor_security_review_required
Original evidence
Evidence 1If the AI tool has not yet been approved and you intend to use or purchase it, an OIS Vendor Security Review is required. This review evaluates privacy, security, compliance, and AI-specific risks, including how university data is accessed, processed, stored, or used for model training.
Localized display only
WashU IT says unapproved AI tools require an OIS Vendor Security Review before use or purchase.
Ai Tool Treatment
WashU identifies specific secure AI tools as reviewed and approved for use with sensitive information, including HIPAA- or FERPA-covered data.
Review: Agent reviewed
Normalized value: secure_ai_tools_approved_for_hipaa_ferpa
Original evidence
Evidence 1Secure AI Tools Approved for HIPAA/FERPA data. Specific tools have been reviewed and approved for use with sensitive information, including data covered by HIPAA or FERPA.
Localized display only
WashU IT labels secure AI tools as approved for HIPAA/FERPA data after review.
Teaching
WashU CTL course-policy guidance presents multiple possible GenAI policy categories for instructors, including allowed without restriction, allowed with citations, partially restricted, and completely restricted.
Review: Agent reviewed
Normalized value: course_ai_policy_options
Original evidence
Evidence 1There are many possible approaches to policies on the use of GenAI in a course. Your policies can also vary within a course by assignment or assignment type. The sections below describe potential policy types and offer examples of syllabus language for each type. AI Usage Level: Allowed Without Restriction; Allowed With Citations; Restricted Partially; Restricted Completely.
Localized display only
The CTL page frames course AI policy as instructor-set and lists four possible policy categories.
Security Review
WashU IT's DeepSeek advisory says DeepSeek is not safe for use with university non-public information.
Review: Agent reviewed
Normalized value: deepseek_not_safe_for_nonpublic_information
Original evidence
Evidence 1We have evaluated DeepSeek, which is an open-source large language model (LLM) and have determined it is not safe for use with university non-public information. Please note: There is a difference between using the public version of DeepSeek and the local instances of the open-source version for research purposes.
Localized display only
WashU IT determined DeepSeek is not safe for university non-public information, while distinguishing public DeepSeek from local research instances.
Source Status
The WashU+AI hub tells students that responsible generative-AI use includes reviewing course expectations for authorized use and seeking clarification from instructors before using generative AI tools.
Review: Agent reviewed
Normalized value: washu_ai_hub_student_clarification
Original evidence
Evidence 1Students: Please ensure the responsible use of generative AI by reviewing your course expectations for the authorized use of generative AI. It is your responsibility to seek clarification from your instructor prior to using these or any other generative AI tools.
Localized display only
The WashU+AI hub tells students to review course expectations and seek instructor clarification before using generative AI tools.
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
ChatGPT and other AI Composition Tools: A Guide for Students
ctl.wustl.edu
Generative Artificial Intelligence (AI) - Information Technology
it.wustl.edu
Language for Course Policies on Artificial Intelligence (AI)
ctl.wustl.edu
Specific guidance on the use of generative AI - DeepSeek
it.wustl.edu
Welcome to WashU Artificial Intelligence - Artificial Intelligence
ai.wustl.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.