Policy presence
No source-backed public AI policy or guidance record is present in this profile.
The current public tracker record does not contain a source-backed claim that establishes a policy or guidance source.
Milan, Italy
Politecnico di Milano
Politecnico di Milano is listed as QS 2026 rank =98. Politecnico di Milano has 3 source-backed AI policy claim records from 1 official source attribution. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
Politecnico di Milano is listed as QS 2026 rank =98. Politecnico di Milano has 3 source-backed AI policy claim records from 1 official source attribution. 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 Politecnico di Milano as an agent-reviewed AI policy record last checked on May 14, 2026 and last changed on May 14, 2026. The record contains 3 source-backed claims, including 3 reviewed claims, from 1 official source attribution. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/politecnico-di-milano.json. The entity-level confidence is 92%. 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 AI tool treatment 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
Politecnico di Milano has 1 source-backed public claim for coursework; deterministic analysis status: conditionally_allowed.
Exams
Politecnico di Milano has 1 source-backed public claim for exams; deterministic analysis status: restricted.
Privacy and data entry
Politecnico di Milano has 2 source-backed public claims for privacy and data entry; deterministic analysis status: blocked.
Academic integrity
No source-backed public claim about academic-integrity treatment of AI use is present in this profile.
The current public tracker record does not contain claim evidence about AI use under academic integrity, misconduct, dishonesty, plagiarism, or cheating rules.
Approved tools
Politecnico di Milano has 1 source-backed public claim for approved tools; deterministic analysis status: allowed.
Named AI services
Politecnico di Milano has 3 source-backed public claims for named ai services; deterministic analysis status: blocked.
Teaching guidance
No source-backed public claim about teaching guidance is present in this profile.
The current public tracker record does not contain claim evidence about instructor, classroom, assessment-design, or syllabus guidance.
Research guidance
Politecnico di Milano has 1 source-backed public claim 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
3 reviewed evidence-backed public claim
Privacy
Politecnico di Milano's regulation prohibits users from providing sensitive data to AI systems hosted outside the university, including credentials, personal identifying information, non-anonymized data, copyrighted data, university intellectual property, or data that could harm the university's reputation.
Review: Agent reviewed
Normalized value: no_sensitive_data_to_externally_hosted_ai_systems
Original evidence
Evidence 1È vietato fornire dati sensibili a sistemi di IA ospitati al di fuori dell’Ateneo, fra cui: password e nomi utente; informazioni di identificazione personale; dati non anonimizzati; dati protetti da diritto d’autore; dati relativi alla proprietà intellettuale dell'Ateneo; qualsiasi dato che potrebbe danneggiare la reputazione del Politecnico di Milano.
Localized display only
The regulation prohibits giving sensitive data to AI systems hosted outside the university, including credentials, personal identifying information, non-anonymized data, copyrighted data, university IP, or data that could harm Polimi's reputation.
Privacy
Politecnico di Milano's regulation says users must be informed and made aware that data supplied to commercial AI tools may be visible and recorded by third parties, creating potential security risks.
Review: Agent reviewed
Normalized value: commercial_ai_tool_data_visibility_recording_risk_notice
Original evidence
Evidence 1Gli utenti devono essere informati e resi consapevoli che i dati forniti a strumenti di IA commerciali possono essere visibili e registrati da terze parti, con potenziali rischi per la sicurezza.
Localized display only
The regulation says users must be informed that data supplied to commercial AI tools may be visible and recorded by third parties, with potential security risks.
Ai Tool Treatment
Politecnico di Milano's personal-data and ICT security regulation treats AI-system use in academic, research, and administrative activities as subject to ethical, responsible, legally compliant use aligned with the university's values.
Review: Agent reviewed
Normalized value: ai_system_use_ethical_responsible_lawful_academic_research_administrative
Original evidence
Evidence 1L'uso di sistemi di intelligenza artificiale (IA) è sempre più centrale nelle attività accademiche, di ricerca e amministrative. Per garantire un utilizzo etico e responsabile, conforme alle normative vigenti e ai valori del Politecnico di Milano occorre fornire una serie di norme di principio. Gli utenti devono assicurare che l'uso del sistema IA sia etico e conforme alle normative vigenti.
Localized display only
The regulation says AI-system use is increasingly central in academic, research, and administrative activities, and users must ensure AI-system use is ethical and legally compliant.
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
1 source attribution
Regolamento del Politecnico di Milano in materia di trattamento dei dati personali e della sicurezza ICT
normativa.polimi.it
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.