What question did this study set out to answer?

Examine the emerging ethical dilemmas and integrity challenges posed by artificial intelligence tools across all stages of the academic publishing lifecycle.

August 5, 2026Frontiers in Research Metrics and AnalyticsOpen Access

Editorial: Research ethics and integrity in the artificial intelligence era

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Authors

JCJosiline Chigwada PNPatrick Ngulube

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Overview

Editorial review uncovers ethical risks across publishing workflows in scholarly research, highlighting the need for tiered disclosure frameworks to protect academic integrity.

Key Points

Examine the emerging ethical dilemmas and integrity challenges posed by artificial intelligence tools across all stages of the academic publishing lifecycle.
Synthesized conceptual, structural, and empirical assessments of artificial intelligence usage across idea generation, manuscript writing, peer review, editorial selection, and post-publication tracking.
Developed a three-tier disclosure governance model distinguishing mechanical language tools, paragraph-level drafting assistance, and core analytical or theoretical contributions.
Identified pervasive ethical vulnerabilities across publishing phases, including dataset bias during hypothesis generation, reviewer automation bias, and citation skew from opaque recommendation algorithms.
Established actionable disclosure standards where basic proofreading requires brief acknowledgment, drafting assistance necessitates prompt disclosure, and analytical machine involvement requires full reproducibility appendices.

Cite This Study

Chigwada et al. (2026) studied this question.

synapsesocial.com/papers/6a89cc9ff8670bac6e335afb https://doi.org/10.3389/frma.2026.1931866

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August 5, 2026Frontiers in Research Metrics and AnalyticsOpen Access

Editorial: Research ethics and integrity in the artificial intelligence era

View Full Paper

Ask AI

Bookmark

Authors

JCJosiline Chigwada PNPatrick Ngulube

Discussion

Member takes

Overview

Editorial review uncovers ethical risks across publishing workflows in scholarly research, highlighting the need for tiered disclosure frameworks to protect academic integrity.

Key Points

Examine the emerging ethical dilemmas and integrity challenges posed by artificial intelligence tools across all stages of the academic publishing lifecycle.
Synthesized conceptual, structural, and empirical assessments of artificial intelligence usage across idea generation, manuscript writing, peer review, editorial selection, and post-publication tracking.
Developed a three-tier disclosure governance model distinguishing mechanical language tools, paragraph-level drafting assistance, and core analytical or theoretical contributions.
Identified pervasive ethical vulnerabilities across publishing phases, including dataset bias during hypothesis generation, reviewer automation bias, and citation skew from opaque recommendation algorithms.
Established actionable disclosure standards where basic proofreading requires brief acknowledgment, drafting assistance necessitates prompt disclosure, and analytical machine involvement requires full reproducibility appendices.

Cite This Study

Chigwada et al. (2026) studied this question.

synapsesocial.com/papers/6a89cc9ff8670bac6e335afb https://doi.org/10.3389/frma.2026.1931866

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