Academicians’ Perceptions of “Artificial Intelligence”: A Metaphorical Review

Abstract

Purpose: This study unveils academicians' mental images regarding the concept of artificial intelligence (AI) through metaphors. Methodology: The study group included 93 academicians working at various universities in Türkiye and reached through convenient sampling. The data was collected through a semi-structured form. Content and descriptive analyses were adopted to analyse the data. The findings suggested that participants used 67 distinct metaphors and nine recurring metaphors to describe AI. Based on the justifications for the metaphors, the researchers identified categories. Then, the metaphors were ranked by their frequency and percentages. Findings: The findings showed that metaphors fell within three categories which were positive, negative and ambivalence. In the positive category “Humanized Intelligence, Efficiency and Support, Learning and Knowledge Transfer, Innovation and Creativity”; in the negative category “Security Concerns, Loss of Control, Misleading, Ethical Concerns and Inequality” and ambivalence category “Power and Danger”, Innovation and Uncertainty”, “Efficiency and Risk” were the emerging themes. The most metaphors were used under the theme of “Efficiency and Support”. Highlights: This study reveals that academicians generally perceive AI positively as a tool accelerating work processes and increasing efficiency. However, AI has negative aspects, such as security concerns, loss of control, ethical issues, and inequality. The study reveals that academicians tend to make a balanced assessment of AI, carefully weighing its potential benefits against its associated risks. This nuanced perspective offers valuable insights that can inform the development of future policies and best practices regarding AI integration.

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