University AI Policy Tracker

Rekod dasar AI universiti yang terbuka dan berasaskan bukti untuk kegunaan awam.

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Change log

Chiba University

Source-backed change history with no release-to-release policy diff rows recorded yet; current claims, official sources, review state, and freshness remain visible across 0 public release records.

Review: Agent reviewedLast checkedMay 20, 2026Last changedMay 20, 2026Claims5Sources1Release records0
University pagePublic JSONMonthly reportUniversity index

Change summary

Current public record freshness and review state.

Chiba University currently has 5 source-backed claim records and 1 official source attribution. Latest tracked changed date: May 20, 2026. No tracker diff rows are recorded in the latest public release.

This page combines all public release diffs for Chiba University. Individual release snapshots remain available from their release-specific URLs.

No release-to-release policy diff rows are recorded for this university yet. The page still tracks current source-backed claims, official source attributions, review state, source freshness, and public JSON for discovery and citation.

This tracker 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.

Newly extracted claims are tracker additions and are not necessarily newly published by the university. Source snapshot changes show hash changes for the same source URL and are not by themselves policy changes.

Diff categories

Semantic classification for this release diff.

Policy text0Newly extracted0Evidence0Source snapshots0Source text0Source added0Source removed0

Combined release diff

Unified tracker diff generated from all public release snapshots for this university.

Chiba University combined release diff

Initial tracked release. Lines represent public claim/evidence records entering the release snapshot.

+10-0
11 # Chiba University AI policy record
2+privacy: Chiba University's guideline tells students not to enter personal information or confidential information into generative AI and notes the information-leakage risk of entering unpublished research plans or research results.
3+Evidence (ja, 06a73425b426): 学生は、生成 AI を教育・学習で利用する際には、以下の諸点について留意する。生成 AI には個人情報や機密情報は入力しないこと（公開されても差し支えない情報のみ入力すること）。生成 AI に未公表の研究計画や研究成果などを入力すると、情報漏洩につながる危険性があること。
4+teaching: Chiba University's guideline says each course instructor judges whether generative AI use is consistent with class objectives and may prohibit or restrict generative AI use where it would significantly undermine achievement of educational objectives.
5+Evidence (ja, 06a73425b426): 生成 AI の授業での利用は、それが授業の目的に合致することが前提であり、合致するかどうかは、それぞれの授業の担当教員が判断する。生成 AI の利用によって、教育目標の達成が大きく損なわれる授業においては、教員は受講生に生成 AI の利用を禁止・制限することができる。
6+ai_tool_treatment: Chiba University's teaching-and-learning guideline says the university does not uniformly prohibit generative AI use in teaching and learning and promotes learning about, with, and aside from generative AI according to purpose.
7+Evidence (ja, 06a73425b426): 千葉大学は生成 AI の教育・学習での利用を一律に禁止することはせず、その目的に応じて、「生成 AI についての学び」「生成 AI を用いた学び」「生成 AI によらない学び」をそれぞれ推進する。
8+teaching: Chiba University's guideline says that when instructors prohibit or restrict generative AI use in a class, they should clearly state that in the syllabus or other course handouts and explain the reason to students.
9+Evidence (ja, 06a73425b426): 授業において生成 AI の利用を禁止・制限する際には、教員はその旨を当該授業のシラバス等に明記する。また、なぜ利用を禁止・制限するのかを受講生にわかりやすく説明することが望まれる。
10+teaching: Chiba University's guideline says that when instructors allow students to use generative AI in class, instructors should consider fairness because outputs may differ depending on external-service registration and paid or free versions.
11+Evidence (ja, 06a73425b426): 授業において学生に生成 AI の利用を認める場合には、外部サービス利用登録の有無、有料版か無料版かなどにより、成果物等に差が生まれ得るため、教員は公平性に配慮する。

Release history

0 public release diffs

Claim changes

5 claim records

teaching

Chiba University's guideline says that when instructors allow students to use generative AI in class, instructors should consider fairness because outputs may differ depending on external-service registration and paid or free versions.

Review: Agent reviewedConfidence92%Evidence1Languagesja

privacy

Chiba University's guideline tells students not to enter personal information or confidential information into generative AI and notes the information-leakage risk of entering unpublished research plans or research results.

Review: Agent reviewedConfidence95%Evidence1Languagesja

teaching

Chiba University's guideline says that when instructors prohibit or restrict generative AI use in a class, they should clearly state that in the syllabus or other course handouts and explain the reason to students.

Review: Agent reviewedConfidence92%Evidence1Languagesja

teaching

Chiba University's guideline says each course instructor judges whether generative AI use is consistent with class objectives and may prohibit or restrict generative AI use where it would significantly undermine achievement of educational objectives.

Review: Agent reviewedConfidence94%Evidence1Languagesja

ai_tool_treatment

Chiba University's teaching-and-learning guideline says the university does not uniformly prohibit generative AI use in teaching and learning and promotes learning about, with, and aside from generative AI according to purpose.

Review: Agent reviewedConfidence93%Evidence1Languagesja

Source snapshots

1 source attribution