AI Shaming: The Silent Stigma among Academic Writers and Researchers

Abstract

AI shaming refers to the practice of criticizing or looking down on individuals or organizations for using AI to generate content or perform tasks. AI shaming has emerged as a recent phenomenon in academia. This paper examines the characteristics, causes, and effects of AI shaming on academic writers and researchers. AI shaming often involves dismissing the validity or authenticity of AI-assisted work, suggesting that using AI is deceitful, lazy, or less valuable than human-only efforts. The paper identifies various profiles of individuals who engage in AI shaming, including traditionalists, technophobes, and elitists, and explores their motivations. The effects of AI shaming are multifaceted, ranging from inhibited technology adoption and stifled innovation to increased stress among researchers and missed opportunities for efficiency. These consequences may hinder academic progress and limit the potential benefits of AI in research and scholarship. Despite these challenges, the paper argues that academic writers and researchers should not be ashamed of using AI when done responsibly and ethically. By embracing AI as a tool to augment human capabilities and by being transparent about its use, academic writers and researchers can lead the way in demonstrating responsible AI integration.

Keywords: AI ethics; AI integration; Academic research; Postdigital academic writing; Shaming; Technological resistance.