Policy presence
Ca' Foscari University of Venice has 3 source-backed public claims for policy presence; deterministic analysis status: unclear.
Open, evidence-backed AI policy records for public reuse.
Venice, Italy
Ca' Foscari University of Venice has 4 source-backed AI policy claims from 4 official source attributions. Review state: agent reviewed; 4 reviewed claims. Last checked May 18, 2026.
v1 public contract
Ca' Foscari University of Venice has 4 source-backed AI policy claims from 4 official source attributions, including 4 reviewed claims. The record review state is agent reviewed; original-language evidence snippets, source URLs, confidence, and public JSON are preserved for citation. Last checked May 18, 2026. Discovery context: Ca' Foscari University of Venice is listed as QS 2026 rank =660.
As of this public record, University AI Policy Tracker lists Ca' Foscari University of Venice as an agent-reviewed AI policy record last checked on May 18, 2026 and last changed on May 18, 2026. The record contains 4 source-backed claims, including 4 reviewed claims, from 4 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/ca-foscari-university-of-venice.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.
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.
Deterministic source-backed dimensions derived from this record's public claims.
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.
Ca' Foscari University of Venice has 3 source-backed public claims for policy presence; deterministic analysis status: unclear.
Ca' Foscari University of Venice has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.
Ca' Foscari University of Venice has 1 source-backed public claim for coursework; deterministic analysis status: recommended.
Ca' Foscari University of Venice has 1 source-backed public claim for exams; deterministic analysis status: recommended.
Ca' Foscari University of Venice has 1 source-backed public claim for privacy and data entry; deterministic analysis status: restricted.
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.
No source-backed public claim identifying approved or licensed AI tools is present in this profile.
The current public tracker record does not contain claim evidence that identifies institutionally approved, licensed, procured, or enterprise AI tools.
Ca' Foscari University of Venice has 1 source-backed public claim for named ai services; deterministic analysis status: restricted.
Ca' Foscari University of Venice has 2 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Ca' Foscari University of Venice has 2 source-backed public claims for research guidance; deterministic analysis status: recommended.
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.
4 reviewed evidence-backed public claim
Source Status
Normalized value: official_ai_guidance_hub_with_linked_guidelines
Original evidence
Evidence 1The Rector's Delegates for Digital innovation in teaching and research, supported by the staff of the Computer Services and Telecommunications Area (ASIT), have prepared the following guidelines: Guidelines for the Responsible Use of Artificial Intelligence in Research; Guidelines for the Responsible Use of Generative AI in Teaching and Learning.
Localized display only
The official AI hub links Ca' Foscari's research and teaching/learning AI guideline PDFs and separately lists administrative-services AI guidance.
Teaching
Normalized value: teaching_learning_guidance_for_faculty_students
Original evidence
Evidence 1These guidelines regarding the potential use of AI tools in teaching and learning are intended for faculty and students. They apply to all forms of AI, regardless of the type of input and output, with a particular focus on commercial applications.
Localized display only
The teaching and learning guidance is explicitly addressed to faculty and students and applies broadly to AI tools, with focus on commercial applications.
Privacy
Normalized value: admin_ai_guidance_no_personal_or_confidential_data_inputs
Original evidence
Evidence 1The staff should therefore not input the following data into AI tools: Personal data that could directly or indirectly identify individuals. Data that is important for future research use and might be protected by intellectual property law. Data subject to contracts with third parties, such as companies. Data protected by copyright or confidentiality restrictions, unless permission is obtained from the owner.
Localized display only
Administrative staff guidance says not to enter personal, contract, protected intellectual-property, or confidentiality-restricted data into AI tools unless permission applies.
Research
Normalized value: research_ai_responsible_use_transparency_citation
Original evidence
Evidence 1Researchers should ensure maximum transparency regarding their use of AI tools in scientific activities. This means that the way AI tools are used should be described in detail in ad hoc sections of the article (e.g., 'Materials and methods' and/or 'Further information'), specifying the prompts (where relevant), which tools were used and which version.
Localized display only
The research guidance advises transparent disclosure of AI tool use, including prompts where relevant, tools used, and versions.
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.
4 source attribution
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