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Research integrity in the era of artificial intelligence: Challenges and responses

Ziyu Chen, Chang-ye Chen, Guozhao Yang, Xiangpeng He, Xiaoxia Chi, Zhuoying Zeng, Xuhong Chen

2024Medicine82 citationsDOIOpen Access PDF

Abstract

The application of artificial intelligence (AI) technologies in scientific research has significantly enhanced efficiency and accuracy but also introduced new forms of academic misconduct, such as data fabrication and text plagiarism using AI algorithms. These practices jeopardize research integrity and can mislead scientific directions. This study addresses these challenges, underscoring the need for the academic community to strengthen ethical norms, enhance researcher qualifications, and establish rigorous review mechanisms. To ensure responsible and transparent research processes, we recommend the following specific key actions: Development and enforcement of comprehensive AI research integrity guidelines that include clear protocols for AI use in data analysis and publication, ensuring transparency and accountability in AI-assisted research. Implementation of mandatory AI ethics and integrity training for researchers, aimed at fostering an in-depth understanding of potential AI misuses and promoting ethical research practices. Establishment of international collaboration frameworks to facilitate the exchange of best practices and development of unified ethical standards for AI in research. Protecting research integrity is paramount for maintaining public trust in science, making these recommendations urgent for the scientific community consideration and action.

Topics & Concepts

Transparency (behavior)Scientific misconductEngineering ethicsResearch ethicsResearch integrityAccountabilityMedicineBest practiceEnforcementData integrityPublic relationsKnowledge managementComputer sciencePolitical scienceComputer securityAlternative medicineEngineeringLawPathologyArtificial Intelligence in Healthcare and EducationAdversarial Robustness in Machine LearningAcademic integrity and plagiarism
Research integrity in the era of artificial intelligence: Challenges and responses | Litcius