The use of artificial intelligence in scientific research with integrity and ethics

Authors

DOI:

https://doi.org/10.37497/sdgs.v6istudies.40

Keywords:

Artificial intelligence, Research ethics, Ethical governance, Scientific integrity, Algorithmic transparency

Abstract

Purpose: This paper examines the evolution of Artificial Intelligence (AI) in scientific research, focusing on the ethical and integrity challenges arising from its integration into knowledge production.

Design/methodology/approach: A conceptual and exploratory analysis was conducted, drawing on interdisciplinary literature on AI governance, research ethics, and academic integrity practices. The study integrates insights from international policies, good practice guidelines, and current debates on algorithmic transparency and accountability.

Findings: The analysis reveals that AI has become an indispensable tool for accelerating scientific discovery and optimizing research processes. However, its use raises concerns related to bias, transparency, accountability, and authorship. The findings highlight the urgent need for robust ethical governance frameworks, transparent and auditable algorithms, and stronger collaboration among researchers, institutions, and policymakers.

Originality/value: This paper advances the debate on AI in science by integrating risks and opportunities in a single framework. It emphasizes that ethics and integrity must remain at the core of scientific progress and proposes a holistic approach that combines governance, education, responsibility, and multi-stakeholder participation.

Practical implications: The study underscores that the benefits of AI in research will only be realized if technological innovation is balanced with ethical values, ensuring that AI-driven discoveries contribute fairly and responsibly to human well-being.

Author Biography

Ricardo Limongi, Cornell University, New York

Doctor in Business Administration in the field of Marketing Strategies from EAESP/FGV, with a doctoral internship at Cornell University under the supervision of Vithala. Post-doctorate in Behavioral Economics applied to Marketing at UnB and Post-Doctorate in Machine Learning applied to Marketing at UFRGS. Adjunct Professor III at the Federal University of Goiás (UFG). Permanent Professor, and coordinator in the biennium (2020-2022), of the Graduate Program in Administration. MBA Coordinator in Strategic Marketing. Visiting Professor and coordinated the inter-institutional collaboration project at the University of Santiago de Chile (USACH). He has additional training in Spatial Statistics, Data Science, and Machine Learning. His research has already been nominated and/or awarded by the international Emerald database (2015/2017) and scientific events. His topics of interest are: Applied Marketing Performance, company or consumer level; Marketing Analytics, and Machine Learning.

References

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Published

2025-02-03

How to Cite

Limongi, R. (2025). The use of artificial intelligence in scientific research with integrity and ethics. SDGs Studies Review , 6, e040. https://doi.org/10.37497/sdgs.v6istudies.40