Policy presence
UNESP has 3 source-backed public claims for policy presence; deterministic analysis status: unclear.
Sao Paulo, Brazil
UNESP
UNESP is listed as QS 2026 rank =450. UNESP has 7 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
UNESP is listed as QS 2026 rank =450. UNESP has 7 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 UNESP 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 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/unesp.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 Source status claims.
- Evidence includes AI tool treatment claims.
- Evidence includes Academic integrity claims.
- Evidence includes Privacy claims.
- Evidence includes Other policy claims.
- Evidence includes Teaching 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
No source-backed public claim about AI disclosure or acknowledgement is present in this profile.
The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.
Coursework
UNESP has 4 source-backed public claims for coursework; deterministic analysis status: required.
Exams
UNESP has 4 source-backed public claims for exams; deterministic analysis status: required.
Privacy and data entry
UNESP has 2 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
UNESP has 3 source-backed public claims for academic integrity; deterministic analysis status: recommended.
Approved tools
UNESP has 1 source-backed public claim for approved tools; deterministic analysis status: required.
Named AI services
UNESP has 2 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
UNESP has 2 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
UNESP has 2 source-backed public claims for research guidance; deterministic analysis status: recommended.
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
7 reviewed evidence-backed public claim
Source Status
UNESP has a central official AI-use resolution, Resolution 13/2025, establishing principles, guidelines, and procedures for AI use in teaching, research, extension, management, and innovation.
Review: Agent reviewed
Normalized value: central_ai_resolution_found
Original evidence
Evidence 1Esta Resolução dispõe sobre a utilização da Inteligência Artificial (IA) na Universidade Estadual Paulista “Júlio de Mesquita Filho” (Unesp), estabelecendo princípios, diretrizes e procedimentos para sua aplicação nas atividades de ensino, pesquisa, extensão, gestão e inovação por pesquisadores, discentes, servidores docentes e técnico-administrativos
Localized display only
Resolution 13/2025 says it governs AI use at UNESP and establishes principles, guidelines, and procedures for teaching, research, extension, management, and innovation.
Ai Tool Treatment
Resolution 13/2025 says every result from the use of AI techniques or tools at UNESP should be supervised and validated by human judgment.
Review: Agent reviewed
Normalized value: human_supervision_validation_required_for_ai_results
Original evidence
Evidence 1II-todo resultado proveniente do uso de técnicas ou ferramentas de IA deve ser supervisionado e validado por julgamento humano
Localized display only
Every result from AI techniques or tools should be supervised and validated by human judgment.
Academic Integrity
Resolution 13/2025 says AI use at UNESP should not justify plagiarism, fraud, or other practices that violate academic honesty.
Review: Agent reviewed
Normalized value: ai_not_justification_for_plagiarism_or_fraud
Original evidence
Evidence 1II-honestidade acadêmica: a IA não deve ser utilizada para justificar plágio, fraude ou qualquer outra prática que viole a honestidade acadêmica, devendo ser utilizada para promover a originalidade, a integridade e a autoria na produção do conhecimento
Localized display only
The resolution states that AI should not be used to justify plagiarism, fraud, or any other practice that violates academic honesty.
Academic Integrity
Resolution 13/2025 says AI use that significantly affects authorship and creation of intellectual or academic production should be publicly communicated, and non-observance may eventually be considered plagiarism.
Review: Agent reviewed
Normalized value: public_communication_for_significant_ai_authorship_impact
Original evidence
Evidence 1III-o uso da IA, quando impactar significativamente a determinação da autoria e criação de produção intelectual e acadêmica, deve ser comunicado publicamente, podendo a não observância desse inciso eventualmente ser considerado plágio
Localized display only
AI use that significantly affects authorship and creation of intellectual and academic production should be publicly communicated; not observing this may eventually be considered plagiarism.
Privacy
Resolution 13/2025 says UNESP AI use should respect Brazil's LGPD, protect personal and sensitive data, and employ security practices to avoid undesired results and damage risks.
Review: Agent reviewed
Normalized value: lgpd_privacy_sensitive_data_security_principles
Original evidence
Evidence 1V-proteção da privacidade: a utilização da IA deve respeitar a Lei Geral de Proteção de Dados (Lei 13.709/2018-LGPD), garantindo a privacidade e a segurança dos dados pessoais, com atenção especial aos dados sensíveis, e implementando medidas de segurança e proteção adequadas; VI-segurança: os sistemas de IA devem visar a segurança da sua aplicação e impactos
Localized display only
The resolution links AI use to LGPD compliance, privacy and security of personal data, special attention to sensitive data, and security practices for AI systems.
Other
Resolution 13/2025 says UNESP should implement at least area-specific AI conduct guides, AI/ethics/privacy training for teachers, staff, and students, and an Ombuds channel for reports of violations.
Review: Agent reviewed
Normalized value: minimum_compliance_measures_guides_training_ombuds
Original evidence
Evidence 1Para garantir a conformidade com esta Resolução, a Unesp deve implementar, no mínimo, as seguintes medidas: I-elaboração, sob responsabilidade de cada uma das áreas institucionais, de guias de conduta em IA; II-treinamentos e capacitações em IA, ética e privacidade de dados pessoais para docentes, servidores e alunos; III-disponibilização da Ouvidoria da Unesp como mecanismo de denúncia
Localized display only
For compliance, UNESP should implement area-specific AI conduct guides, AI/ethics/privacy training, and an Ombuds channel for reports.
Teaching
UNESP announced asynchronous training to orient the university community on responsible generative AI use in academic and administrative activities.
Review: Agent reviewed
Normalized value: official_responsible_generative_ai_training_announced
Original evidence
Evidence 1A Unesp inicia nesta semana uma ampla formação para instruir e incentivar o uso responsável de ferramentas de inteligência artificial generativa no dia a dia das atividades acadêmicas e administrativas. A formação será no formato assíncrono, com aulas gravadas e atividades disponíveis via plataforma Moodle.
Localized display only
UNESP announced asynchronous training to instruct and encourage responsible use of generative AI tools in academic and administrative activities.
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
Formação vai orientar comunidade universitária sobre o uso responsável de sistemas de inteligência artificial no dia a dia
www2.unesp.br
RESOLUÇÃO UNESP Nº 13, DE 22 DE ABRIL DE 2025
app.unesp.br
Unesp estabelece as bases para discussão sobre uso da IA na Universidade
www2.unesp.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.