The rapid evolution of Generative AI (GenAI) has transformed the ways in which knowledge is created, shared, interpreted, and applied in organization and educational contexts. While earlier studies have often focused on the technical capabilities of GenAI or on the detection of synthetic content, less attention has been given to how these tools influence knowledge management processes at the individual and group levels. This study addresses that gap by examining how GenAI affects the production, transfer, validation, and use of knowledge among individuals and within collaborative settings. The aim of this study is to explore the current state of 'AI vs AI' by generating a dataset comprising texts, images, audio and video, utilizing a set of freely available AI tools. This pilot illustrative study was based on a two-stage strategy: in the first stage synthetic media was generated with different GenAI tools to mimic human creativity. A second stage, which involved a rigorous evaluation of AI-detection tools for each modality separately. Texts were created in three different GenAI tools and Images were prompted to mimic Renaissance paintings by Michelangelo and Raphael. Audio was generated with the purpose of mimicking interviews with the Renaissance painters. Videos, finally, were created to be deceptive deepfakes, placing persons in environments and situations where they never have been in real life. Findings provide a comparative analysis of tools' accuracy and false-positive rates that could act as valuable guidelines in the increasing flood of AI-generated content. This research contributes to the growing discussion on how organizations and institutions can manage the opportunities and risks associated with GenAI in knowledge-intensive environment. The study highlights the need for critical AI literacy, transparent knowledge practices, and governance mechanisms that ensure the responsible integration of GenAI into individual and collaborative knowledge work.
Anastasiia Iufereva, Peter Mozelius· European Conference on Knowl...· 0 citations
This exploratory study presents the initial results of a comparative analysis designed to evaluate the performance of human coding and GenAI (ChatGPT 5.1) coding in qualitative content analysis. The analysis focuses on six selected articles from Italian media outlets (La Repubblica, Il Corriere della Sera, Il Giornale) covering the Russia–Ukraine conflict from 2022 onward. These six articles were selected from a broader corpus of 180 publications, which served as the basis for the sampling procedure. The findings reveal both opportunities and limitations in the use of AI for qualitative research. On the one hand, ChatGPT provided additional capacity for identifying linguistic units that had been overlooked by the human coder. On the other hand, ChatGPT showed limitations related to its constrained linguistic capabilities, which prevented it from fully capturing complex linguistic figures associated with judgment values. This research offers methodological insights for communication scholars regarding the responsible and effective integration of GenAI into qualitative media studies. Future research will extend the qualitative analysis to the broader corpus, with attention to framing strategies, manipulative practices, and objectivity markers. This continued comparative approach will allow for a more detailed mapping of similarities and differences in coding tendencies between human coding and AI, as well as for the detection of ideological patterns in Italian media coverage of the Russia-Ukraine conflict.
Anastasiia Iufereva· Journal of Media Research· 0 citations
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