Moscow, Russia

HSE University

HSE University is listed as QS 2026 rank =440. HSE University has 4 source-backed AI policy claim records from 3 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Short answer

v1 public contract

HSE University is listed as QS 2026 rank =440. HSE University has 4 source-backed AI policy claim records from 3 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 HSE University as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 4 source-backed claims, including 4 reviewed claims, from 3 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/hse-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.

Claim coverage4 reviewedSource languageruPublic JSON/api/public/v1/universities/hse-university.json

Policy signals in this record

  • Evidence includes Academic integrity claims.
  • Evidence includes AI tool treatment claims.
  • Evidence includes Teaching claims.
  • Evidence includes Source status 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.
  • Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims4Reviewed4Candidate0Official sources3

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.

Coverage score100/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence80%

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.

Privacy and data entry

HSE University has 1 source-backed public claim for privacy and data entry; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence77%Evidence1Sources1

Approved tools

HSE University has 1 source-backed public claim for approved tools; deterministic analysis status: blocked.

BlockedMachine candidateConfidence81%Evidence1Sources1

Named AI services

HSE University has 1 source-backed public claim for named ai services; deterministic analysis status: blocked.

BlockedMachine candidateConfidence81%Evidence1Sources1

Teaching guidance

HSE University has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence80%Evidence1Sources1

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Security and procurement

No source-backed public claim about AI security review or procurement is present in this profile.

The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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

4 reviewed evidence-backed public claim

Academic Integrity

HSE University requires students to disclose use of generative AI in written academic work, including the parts prepared with AI, the purpose and method of use, model name or source, and an effectiveness evaluation.

Review: Agent reviewedConfidence96%

Normalized value: disclosure_required

Original evidence

Evidence 1
Студент (или группа студентов) обязаны сопроводить письменное задание специальным разделом «Описание применения генеративной модели», где обозначить ... части текста ... цели и способ применения ... ее название, адреса сайта ... оценку эффективности

Localized display only

Students must include a dedicated generative-model-use description covering generated parts, purpose/method, model name/source, and effectiveness.

Ai Tool Treatment

HSE University states that there is no university-wide prohibition on student use of AI, and students may use generative models in academic work when they follow disclosure requirements.

Review: Agent reviewedConfidence95%

Normalized value: allowed_with_disclosure

Original evidence

Evidence 1
В НИУ ВШЭ нет общеуниверситетского запрета на использование искусственного интеллекта (ИИ) студентами — они могут использовать технологии генеративных моделей ... в процессе выполнения учебных работ

Localized display only

HSE says there is no university-wide ban on student AI use and students may use generative models in academic work.

Teaching

HSE University says an instructor may prohibit the use of generative models during assessment elements if the prohibition is stated in the course syllabus.

Review: Agent reviewedConfidence94%

Normalized value: instructor_may_prohibit_in_syllabus

Original evidence

Evidence 1
Преподаватель может запретить использование генеративных моделей во время проведения элементов контроля — в таком случае, он указывает это в программе учебной дисциплины (ПУД).

Localized display only

An instructor may prohibit generative-model use for assessment elements by stating that in the course syllabus.

Source Status

HSE University has an official university-scope regulation page for checking written student work for plagiarism and generative-model use; the page identifies the regulation as adopted on May 8, 2024, effective May 13, 2024, and indefinite.

Review: Agent reviewedConfidence91%

Normalized value: official_regulation_page_found

Original evidence

Evidence 1
Вид:регламентДата принятия:8.05.2024Вступил в силу:13.05.2024 Срок действия:Бессрочный документ ... Область действия:Университет

Localized display only

The official document page identifies this as a university-scope regulation, adopted May 8, 2024, effective May 13, 2024, and indefinite.

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

3 source attribution

Правила использования искусственного интеллекта студентами НИУ ВШЭ

hse.ru

Snapshot hash
8e05e49ef70cde7e47119f305023ec77104f12f73b03b37a45ab3b93a26c3282

Регламент организации проверки письменных учебных работ на наличие плагиата, использования генеративных моделей и размещения выпускных квалификационных работ

hse.ru

Snapshot hash
505bc49f60a26a51e6d995ad76a384bbd33d20dde015a89076524c2e85c9dc3d

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.

Last checkedMay 16, 2026Last changedMay 16, 2026Open change log

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.

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