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AI Shaming: The Silent Stigma among Academic Writers and Researchers
1General Education Department, Colegio de Muntinlupa, Muntinlupa, Philippines. lgiray@cdm.edu.ph.
Annals of Biomedical Engineering
|July 8, 2024
Summary
AI shaming criticizes AI use in academia, potentially hindering innovation and researcher efficiency. Responsible and ethical AI integration should be embraced, not feared, to advance scholarship.
Area of Science:
- Artificial Intelligence
- Academic Research
- Scholarly Communication
Background:
- AI shaming is a recent phenomenon in academia, involving criticism of individuals and organizations for using AI in content generation and tasks.
- This practice often dismisses AI-assisted work as inauthentic, lazy, or less valuable than human-only efforts.
- Motivations for AI shaming stem from traditionalist, technophobic, or elitist viewpoints.
Discussion:
- AI shaming negatively impacts academic writers and researchers, leading to inhibited technology adoption and stifled innovation.
- Consequences include increased stress for researchers and missed opportunities for enhanced efficiency.
- These effects can impede academic progress and limit the benefits of AI in research and scholarship.
Key Insights:
- AI shaming profiles include traditionalists, technophobes, and elitists, each with distinct motivations.
- The practice discourages responsible AI use, despite its potential to augment human capabilities.
- Ethical and transparent AI integration is crucial for academic advancement.
Outlook:
- Academic writers and researchers should embrace AI as a tool for augmenting human capabilities.
- Transparency in AI usage is key to fostering trust and demonstrating responsible integration.
- Overcoming AI shaming can unlock significant potential benefits for research and scholarship.
Keywords:
AI ethicsAI integrationAcademic researchPostdigital academic writingShamingTechnological resistanceMore Related Videos
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