Ann Biomed Eng.
AI shaming involves criticizing individuals or organizations for using AI to generate content or perform tasks, emerging recently in academia. This paper examines AI shaming’s characteristics, causes, and effects, noting that it often dismisses AI-assisted work as deceitful, lazy, or less valuable. It identifies traditionalists, technophobes, and elitists as primary culprits, motivated by various biases. AI shaming’s effects include inhibited technology adoption, stifled innovation, increased stress, and missed efficiency opportunities, potentially hindering academic progress. The paper advocates for the responsible and ethical use of AI in academia, suggesting that transparency and embracing AI can enhance human capabilities and lead to responsible AI integration.
Ann Biomed Eng. 2024 Jul 8. doi: 10.1007/s10439-024-03582-1.
Recommended on behalf of EASE by Silvia Maina, Italy