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図書

研究・教育における生成AIの利活用の方法とその考え方 (高等教育研究叢書 = Reviews in higher education ; 177)

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研究・教育における生成AIの利活用の方法とその考え方(高等教育研究叢書 = Reviews in higher education ; 177)

Call No. (NDL)
M53-R19
Bibliographic ID of National Diet Library
034069863
Material type
図書
Author
野内玲, 井野瀬久美惠 編
Publisher
広島大学高等教育研究開発センター
Publication date
2025.3
Material Format
Paper
Capacity, size, etc.
92 p ; 26 cm
NDC
407
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Detailed bibliographic record

Contents:

研究活動における生成AIの利用と研究者の責任 / 野内玲技術の発展と研究公正 / 大屋雄裕産業界におけるAI倫理の現状と課題 / 樋笠尭士...

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Table of Contents

Provided by:学術機関リポジトリデータベース(IRDB)(機関リポジトリ)Link to Help Page
  • 序文 ... 野内 玲(広島大学)1 第1章 研究活動における生成AI の利用と研究者の責任... 野内 玲(広島大学) 3 第2章 技術の発展と研究公正 − 法哲学の観点から −... 大屋 雄裕(慶應義塾大学)13 第3章 産業界におけるAI 倫理の現状と課題... 樋笠 尭士(多摩大学) 25 第4章 AI 活用に伴う法的課題... 樋笠 知恵(信州大学) 37 第5章 論文執筆と発表における生成AI の適正利用と課題... 岡林 浩嗣(筑波大学) 47 第6章 中高の現場における生成AI の現状と課題... 南里 翔平(市川中学校・高等学校) 61 第7章 人文社会科学研究における生成AI... 藤井 基貴(静岡大学) 73 第8章 生成AI で研究不正は変わるのか?... 井野瀬 久美惠(人間文化研究機構) 85

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  • Hiroshima University Institutional Repository

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Bibliographic Record

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Paper

Material Type
図書
ISBN
978-4-86637-054-5
Title Transcription
ケンキュウ ・ キョウイク ニ オケル セイセイ AI ノ リカツヨウ ノ ホウホウ ト ソノ カンガエカタ
Author/Editor
野内玲, 井野瀬久美惠 編
Author Heading
編者 : 野内, 玲 ノウチ, レイ ( 034140215 )Authorities
編者 : 井野瀬, 久美恵, 1958- イノセ, クミエ, 1958- ( 00193203 )Authorities
Publication Date
2025.3
Publication Date (W3CDTF)
2025
Extent
92 p
Size
26 cm
Place of Publication (Country Code)
JP
Text Language Code
jpn
Content Type
テキスト
Media Type
機器不用
Carrier Type
冊子
Subject Heading
科学者倫理 カガクシャリンリ ( 01157690 )Authorities
生成AI セイセイ AI ( 033296281 )Authorities
NDLC
Target Audience
一般
Note (Bibliography)
文献あり
Holding library
国立国会図書館
Call No.
M53-R19
Data Provider (Database)
国立国会図書館 : 国立国会図書館蔵書
Bibliographic ID (NDL)
034069863
National Bibliography No. (JPNO)
24131617
Cataloging Rule
Nippon Cataloging Rules 2018 Edition
Bibliographic Record Category (NDL)
111

Digital

Summary, etc.
This publication reflects presentations from the National Conference on the Promotion of Research Integrity FY2023, organized by the Association for the Promotion of Research Integrity (APRIN) on February 16, 2024. The Conference featured keynote speeches and other talks, followed by subcommittees divided into research fields, including life and medical sciences, science and engineering, humanities and social sciences, and secondary education. Satellite events were also held for researchers and research administrative staff involved in promoting research integrity.  A central theme, led by the Humanities and Social Sciences Subcommittee, was “Research Integrity in Technological Innovation.” This subcommittee aimed to discuss generative AI's impact on research practices and the core values of research integrity. However, due to time constraints, the discussion did not necessarily achieve this objective. Therefore, this publication compiles perspectives from presenters across subcommittees to provide a multidimensional analysis of the relationship between research activities and generative AI (or AI technology general), as well as its implications for research integrity.  The authors, representing diverse fields such as philosophy, legal philosophy, law, pedagogy, bioscience, bioethics, medical ethics, and secondary education, have collaborated to examine the impact of generative AI on education and research. They explore fundamental approaches to handling generative AI in their respective disciplines. The interdisciplinary nature of this publication enhances its value as a resource for understanding the evolving role of AI in higher education and research.  As part of the Reviews in Higher Education series, this publication highlights AI's extensive role in research, education, and university operations, emphasizing its significance in higher education. While not exhaustive, this work aims to be a valuable resource for promoting research integrity in the face of technological advancements.  We appreciate APRIN’s support in providing conference recordings that contributed to this publication.
Format (IMT)
application/pdf
Access Restrictions
インターネット公開
Data Provider (Database)
国立情報学研究所 : 学術機関リポジトリデータベース(IRDB)(機関リポジトリ)
Original Data Provider (Database)
広島大学 : 広島大学学術情報リポジトリ