Generative AI and Research Misconduct under South Korea's National Research and Development Innovation Act.
Purpose: This study examines how the use of generative artificial intelligence (AI) in research may be interpreted and regulated under South Korea's National Research and Development Innovation Act and its Enforcement Decree. It also evaluates how AI-assisted research practices challenge the concept...
| Publicado en: | Journal of Korean Academy of Nursing Administration Vol. 32; no. 2; pp. 71 - 82 |
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| Autor principal: | |
| Formato: | glossary research tables/charts Journal Article |
| Publicado: |
Korean Academy of Nursing Administration
Mar2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=192677714&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192677714 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 12259330 DAEH jtl: Journal of Korean Academy of Nursing Administration issn: 12259330 maglogo: N pubinfo: dt: Mar2026 vid: 32 iid: 2 pid: 72190 pub: Korean Academy of Nursing Administration artinfo: ui: 192677714 192677714 192677714 10.11111/jkana.2025.0082 192677714 ppf: 71 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Generative AI and Research Misconduct under South Korea's National Research and Development Innovation Act. aug: au: Lee, Hyobin affil: Lecturer, School of International Studies, Chungnam National University sug: subj: Artificial Intelligence, Generative Utilization Scientific Misconduct Legislation and Jurisprudence Research, Nursing Legislation and Jurisprudence Artificial Intelligence, Generative Legislation and Jurisprudence Scientific Misconduct Prevention and Control Research Ethics Legislation and Jurisprudence Human South Korea Study Design Literature Review Data Collection Data Analysis Manuscripts Writing for Publication Classification Plagiarism Authorship Research Nurses Data Breach Data Security Artificial Intelligence, Generative Ethical Issues Research, Nursing Ethical Issues Government Regulations Natural Language Processing Copyright Reproducibility of Results Data Management Descriptive Statistics Instrument Construction Evidence Synthesis Surveys Serial Publications Bibliography and References Access to Information Privacy and Confidentiality Intellectual Property Audit Workflow Patient Safety Research Subjects Trust ab: Purpose: This study examines how the use of generative artificial intelligence (AI) in research may be interpreted and regulated under South Korea's National Research and Development Innovation Act and its Enforcement Decree. It also evaluates how AI-assisted research practices challenge the conceptual boundaries of the statutory categories of research misconduct. Methods: Through doctrinal legal analysis of Article 31 of the Act and Article 56 of the Enforcement Decree, common AI-assisted practices across the research cycle--design, literature review, data generation and analysis, manuscript writing, and the input of data into AI systems-- were mapped to the Act's misconduct taxonomy and related legal duties. Results: Generative AI may plausibly implicate fabrication, falsification, plagiarism, and improper authorship (Article 31(1)1), as well as improper ownership of research and development outcomes and breaches of security measures (Article 31(1)3--4). The analysis further indicates that AI use destabilizes categorical boundaries, as individual outputs may simultaneously involve invented content, distorted interpretation, and unattributed reproduction. Numerous research-integrity risks arise from failures in research processes, including nondisclosure, inadequate verification, weak provenance tracking, and irreproducible analysis pipelines. Conclusion: Legal and institutional responses should prioritize transparency across the research cycle and the development of auditable workflows, rather than focusing solely on sanctioning problematic outputs. Clear disclosure standards, verification obligations, reproducibility requirements, and stringent data-stewardship rules are necessary to address these emerging risks. pubtype: Academic Journal doctype: glossary research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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