Tailoring Scientific Knowledge: How Generative AI Personalizes Academic Reading Experiences

Anna Małgorzata Kamińska ()
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Anna Małgorzata Kamińska: Institute of Culture Studies, University of Silesia in Katowice, ul. Uniwersytecka 4, 40-007 Katowice, Poland

Publications, 2025, vol. 13, issue 2, 1-28

Abstract: The scientific literature is expanding at an unprecedented pace, making it increasingly difficult for researchers, students, and professionals to extract relevant insights efficiently. Traditional academic publishing offers static, one-size-fits-all content that does not cater to the diverse backgrounds, expertise levels, and interests of readers. This paper explores how generative AI can dynamically personalize scholarly content by tailoring summaries and key takeaways to individual user profiles. Nine scientific articles from a single journal issue were used to create the dataset, and prompt engineering was applied to generate tailored insights for exemplary personas: a digital humanities and open science researcher, and a mining and raw materials industry specialist. The effectiveness of AI-generated content modifications in enhancing readability, comprehension, and relevance was evaluated. The results indicate that generative AI can successfully emphasize different aspects of an article, making it more accessible and engaging to specific audiences. However, challenges such as content oversimplification, potential biases, and ethical considerations remain. The implications of AI-powered personalization in scholarly communication are discussed, and future research directions are proposed to refine and optimize AI-driven adaptive reading experiences.

Keywords: GenAI-driven content personalization in academia; recommender systems for scientific literature; generative AI in scholarly publishing; Large Language Models (LLMs) in academic research; GenAI-assisted scientific text summarization; scientific content customization using AI; personalized academic reading with AI; adaptive summaries for scholarly communication; AI-driven knowledge dissemination in science; adaptive scholarly article retrieval through AI (search for similar items in EconPapers)
JEL-codes: A2 D83 L82 (search for similar items in EconPapers)
Date: 2025
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