Policy presence
Universidade Federal do Rio de Janeiro has 3 source-backed public claims for policy presence; deterministic analysis status: unclear.
Rio de Janeiro, Brazil
Universidade Federal do Rio de Janeiro
Universidade Federal do Rio de Janeiro is listed as QS 2026 rank =317. Universidade Federal do Rio de Janeiro has 5 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
Universidade Federal do Rio de Janeiro is listed as QS 2026 rank =317. Universidade Federal do Rio de Janeiro has 5 source-backed AI policy claim records from 2 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 Universidade Federal do Rio de Janeiro as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 5 source-backed claims, including 5 reviewed claims, from 2 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/universidade-federal-do-rio-de-janeiro.json. The entity-level confidence is 90%. 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 Source status claims.
- Evidence includes Academic integrity claims.
- Evidence includes AI tool treatment claims.
- Evidence includes Teaching claims.
- Evidence includes Privacy claims.
- No specific AI service name is highlighted by the current public claim text.
- Privacy, sensitive-data, or security 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
Universidade Federal do Rio de Janeiro has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.
Coursework
Universidade Federal do Rio de Janeiro has 3 source-backed public claims for coursework; deterministic analysis status: conditionally_allowed.
Exams
Universidade Federal do Rio de Janeiro has 3 source-backed public claims for exams; deterministic analysis status: conditionally_allowed.
Privacy and data entry
Universidade Federal do Rio de Janeiro has 1 source-backed public claim for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
Universidade Federal do Rio de Janeiro has 2 source-backed public claims for academic integrity; deterministic analysis status: recommended.
Approved tools
Universidade Federal do Rio de Janeiro has 1 source-backed public claim for approved tools; deterministic analysis status: recommended.
Named AI services
Universidade Federal do Rio de Janeiro has 2 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
Universidade Federal do Rio de Janeiro has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.
Research guidance
Universidade Federal do Rio de Janeiro has 1 source-backed public claim for research guidance; deterministic analysis status: restricted.
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.
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
5 reviewed evidence-backed public claim
Source Status
UFRJ publicly announced preliminary documents on academic integrity and AI-use recommendations for the academic community.
Review: Agent reviewed
Original evidence
Evidence 1A Universidade Federal do Rio de Janeiro (UFRJ) tornou público dois documentos preliminares que orientam a comunidade acadêmica sobre o uso ético e responsável da inteligência artificial, em especial nas atividades de ensino e pesquisa.
Localized display only
The university announced two preliminary documents guiding ethical and responsible AI use in teaching and research.
Academic Integrity
UFRJ states that delegating monographs, dissertations, and theses to generative AI systems is considered academic dishonesty under the proposed integrity guidance.
Review: Agent reviewed
Original evidence
Evidence 1Simplesmente delegar a responsabilidade de elaboração desses trabalhos a terceiros ou a sistemas de Inteligência Artificial Generativa (IAGen) é considerado desonestidade acadêmica e pode resultar em sanções institucionais, inclusive a perda do título, de acordo com a proposta do documento.
Localized display only
Delegating academic works to generative AI is described as academic dishonesty and may lead to institutional sanctions under the proposed document.
Ai Tool Treatment
UFRJ guidance allows generative AI to assist preparation and development of academic work, while keeping final responsibility with human authors.
Review: Agent reviewed
Original evidence
Evidence 1As diretrizes também destacam que o uso de ferramentas de IAGen pode auxiliar na preparação e elaboração desses trabalhos, incluindo exploração de temas de pesquisa e organização de ideias, mas a responsabilidade final sobre o conteúdo produzido deve permanecer vinculada à autoria humana.
Localized display only
Generative AI may assist preparation and organization, but final responsibility remains with human authorship.
Teaching
CRIA/UFRJ recommends that instructors define acceptable and unacceptable generative AI uses in their course teaching plans.
Review: Agent reviewed
Original evidence
Evidence 1Cada professor deve definir claramente, no plano de ensino da sua disciplina, o que constitui uso aceitável e inaceitável de ferramentas de IAG.
Localized display only
Each professor should define acceptable and unacceptable IAG uses in the discipline teaching plan.
Privacy
CRIA/UFRJ recommends warning researchers about risks of uploading or processing confidential or proprietary third-party data through generative AI tools.
Review: Agent reviewed
Original evidence
Evidence 1Pesquisadores devem ser alertados sobre os riscos de se fazer upload e/ou processar dados/programas confidenciais ou proprietários de terceiros por meio de ferramentas de IAG, pois esses dados poderão ser incorporados no treinamentos futuros de ferramentas.
Localized display only
Researchers should be warned about uploading or processing confidential or proprietary third-party data through IAG 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
2 source attribution
Recomendações à Reitoria sobre o Uso da Inteligência Artificial na UFRJ
drive.google.com
UFRJ atualiza diretrizes de integridade acadêmica e propõe recomendações sobre o uso de inteligência artificial
conexao.ufrj.br
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.