| Title: | Prompt to press : evaluating human perception of AI involvement in news writing across prompt specificity |
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| Authors: | ID Sergaš, Uroš (Author)
ID Wagne, Ahmadou (Author)
ID Kolb, Thomas Elmar (Author)
ID Neidhardt, Julia (Author)
ID Ferwerda, Bruce (Author)
ID Tkalčič, Marko (Author) |
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| Files: |  RAZ_Sergas_Uros_2026.pdf (593,55 KB)
MD5: 3D0BAF949DB0AC581A6F02E9E779ED8A
 https://dl.acm.org/doi/10.1145/3742414.3795097
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| Language: | English |
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| Work type: | Unknown |
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| Typology: | 1.08 - Published Scientific Conference Contribution |
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| Organization: | FAMNIT - Faculty of Mathematics, Science and Information Technologies
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| Abstract: | Large language models (LLMs) are becoming a common feature in content creation tools, prompting important questions about how design choices influence user trust and engagement in AI- assisted journalism. Beyond output quality, factors such as prompt specificity, model choice, and authorship disclosure are themselves interaction design parameters that influence how users interpret and evaluate AI contributions. Yet, little is known about how these design decisions affect reader perceptions in journalistic contexts. To address this gap, we conducted an experiment with 150 participants who evaluated news articles on the sensitive topic of assisted suicide. The articles systematically varied in authorship (human-written, AI-edited, or AI-generated), stance (pro- or anti- legalization), and prompt specificity (vague, moderate, or highly detailed). Participants rated each article on engagement, subjectivity, and perceived AI involvement, and also provided open-ended justifications for their authorship judgments. Our findings show that prompt specificity and model choice significantly influence perceptions of authorship, underscoring how technical design decisions in AI tools can shape public trust in journalism. |
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| Keywords: | AI-generated news, prompt specificity, human vs. AI detection, media perception, assisted suicide |
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| Publication version: | Version of Record |
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| Publication date: | 22.03.2026 |
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| Year of publishing: | 2026 |
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| Number of pages: | Str. 89-92 |
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| PID: | 20.500.12556/RUP-22845  |
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| UDC: | 004.8 |
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| DOI: | 10.1145/3742414.3795097 |
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| COBISS.SI-ID: | 272747523 |
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| Publication date in RUP: | 24.03.2026 |
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| Views: | 39 |
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| Downloads: | 2 |
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