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Integrity and Originality: The Indispensable Human Contribution Post-Generative AI
In 2025, the scholarly publishing ecosystem has redefined its core values with the use of Generative AI, especially through the capabilities of Large Language Models (LLMs). These tools accelerate literature review, language refinement, and simplified editorial review. However, this efficiency has triggered a growing crisis of trust, which challenges the fundamental principles of Integrity and Originality.
The Redefinition of Value
Editors and stakeholders in the Asian Council of Science Editors (ACSE) region must focus on the importance of the human mind, beyond simple plagiarism detection. AI can synthesize coherent and technically correct text, but only a human author or editor can make a unique contribution to moral accountability and genuine intellectual insight.
Human Integrity: Accountability and Moral Judgement
In the post AI era, integrity is no longer limited to avoiding plagiarism. It is about establishing human accountability for published work, because AI systems do not possess legal or moral awareness. The burden of responsibility rests entirely on the human author. This results in two specific human contributions:
A. Human Accountability as a Core Principle
The first unique contribution of the human author is the capacity to take full responsibility for the work. In 2025, a global consensus created through organizations like COPE (Committee on Publication Ethics) and major publishing groups confirms that AI cannot be listed as an author.
This policy ensures that human authors are the guarantors of integrity, responsible for verifying every claim that may be supported through AI use and confirming the accuracy of all data.
The role of editors is to enforce accountability through clear disclosure policies. Readers should know where human judgement begins and how AI assistance was used.
B. Contextual Wisdom as the Ethical Filter
AI systems operate mainly through logic and pattern recognition. They often fail when faced with ethical context, cultural nuance, and regional differences. Most AI tools are trained on global and Western data, which prioritize linguistic quality instead of the substance of research.
In the diverse ACSE region, manuscripts created by non native English authors or local academic styles may be flagged as low linguistic quality even when the research value is high. The unique authority of human editors is contextual discretion and academic compassion.
Editors can choose to support language editing instead of automated rejection, which protects valuable regional knowledge, indigenous research, and sensitive political information. Only editors with regional experience can evaluate ethical risk, social sensitivity, and cultural impact, which global AI remains unable to understand.
The Quest for Human Originality: Insight and Critical Synthesis
When AI tools can immediately generate literature reviews or structured arguments, the question becomes: Where does real originality exist in a post-AI publishing ecosystem?
A. True Hypotheses and Intellectual Leaps
AI is strong in synthesizing information and combining existing theories. However, it is rarely able to produce new intellectual breakthroughs.
True originality begins with intellectual intuition, life experience, creative curiosity, and unexpected interdisciplinary connections. These are human capacities, not computational patterns.
Editors should prioritize manuscripts that include authentic research questions, original hypotheses, and deep analytical thinking. The priority should be the strength of arguments, not the superficial quality of language.
B. Critical Synthesis and Scholarly Language
Human originality is more than summarizing existing research. It creates a unique scholarly language, shaped by the author’s intellectual journey, questions, doubts, and discoveries.
AI can imitate writing patterns, but critical synthesis requires reflective reasoning and intellectual ownership. Editors now must evaluate whether a manuscript shows true intellectual work or only the structural clarity created with AI tools.
The mission of academic publishing remains the advancement of human knowledge, not simply the fast production of technically correct text.
Conclusion: Embracing Human and AI Partnership
In 2025, the tension between human insight and the speed of AI defines the future direction of scholarly publishing. The answer is not to ban the use of AI tools but to understand their limitations and to place a higher value on human intelligence.
AI offers efficiency, speed, and analytical support.
Human editors and authors provide Integrity through moral accountability and contextual judgement, and Originality through critical synthesis and genuine hypothesis creation.
The unique contribution of humans is the creation of moral and intellectual authority. Effective publishing policies must use AI as a tool while elevating regional ethics, transparency, and human oversight as the editorial standard.
The credibility of scholarly publishing in the post AI era depends on this direct commitment.
Keywords
Generative AI Scholarly Publishing Publication Ethics Human Accountability Editorial Policies Originality Large Language Models ACSE Region Research Integrity Critical Synthesis COPE Responsible AI Editorial Judgement Regional Ethics
Dr. Marvel Reuben Suwitono is the Dean of the Indonesian Adventist University, Indonesia, and a specialist in natural product chemistry and pharmaceutical sciences. He earned his Ph.D. in Pharmaceutical Analysis from Institut Teknologi Bandung (ITB), Bandung, Indonesia. His research focuses on the chemistry of natural products, with strong interests in medicinal chemistry, phytochemical analysis, and analytical method development for drug discovery. Dr. Suwitono’s work integrates the identification of bioactive compounds from natural sources with modern pharmaceutical sciences to support therapeutic innovations and new drug targets.
View All Posts by Marvel Reuben SuwitonoDisclaimer
The views and opinions expressed in this article are those of the author(s) and do not necessarily reflect the official policy or position of their affiliated institutions, the Asian Council of Science Editors (ACSE), or the Editor’s Café editorial team.
