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Hamid Reza Saeidnia

Using ChatGPT as a Digital/Smart Reference Robot: How May ChatGPT Impact Digital Reference Services?

The emergence of OpenAI Chat technology can replace the human expert because this technology, using machine learning and intelligent algorithms, is able to automatically provide the best answers, which leads to increased productivity and reduced human error. In this study, we will explain to what extent ChatGPT can be used instead of digital services. We answer this question by chatting with ChatGPT.

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FeaturedTranslation
Yazdan Mansourian

Five functions of information sharing in serious leisure: Releasing the power of information among passionate people

Why do we feel compelled to share information with others? With serious leisure—the pursuit of hobbies, voluntary activities or amateurism that requires effort, dedication, commitment, specific skills or knowledge—the motivations behind information sharing are complex. This article explores five themes to help us gain a deeper understanding of the role of information sharing in the context of serious leisure.

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Kalervo Järvelin

Information Science Breaking up?

Many would agree that the institutional library/information service R&D, information seeking, information retrieval, and biblio/infor/scientometrics form the landscape of Library and Information Science (LIS). These subareas are also brought forward in introductions to, and analyses of LIS (e.g., curricula, lectures, textbooks). Still, scholars contributing to different subareas may increasingly turn their attention toward the territory outside LIS – and be integrated there – or remain as visitors to LIS, being based outside. Are there indications toward that in LIS research? We decided to analyze the trends.

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Translation
Brady Lund

ChatGPT and AI-Written Research Papers: Ethical Considerations for Scholarly Publishing

Our study reveals that the potential for bias within AI-driven language models, such as GPT-3, poses a significant threat to the integrity of science. These models are trained on vast amounts of data, primarily from the internet, which can lead to a bias in the data. For example, if the data source is biased or incomplete, this bias will be reflected in the model’s output.

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