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Venturing ChatGPT's lens to explore human values in software artifacts: a case study of mobile APIs.

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Title: Venturing ChatGPT's lens to explore human values in software artifacts: a case study of mobile APIs.
Authors: Mougouei, Davoud (AUTHOR), Rafi, Saima (AUTHOR), Fahmideh, Mahdi (AUTHOR), Mougouei, Elahe (AUTHOR), Khan, Javed Ali (AUTHOR), Dam, Hoa Khanh (AUTHOR), Nurwidyantoro, Arif (AUTHOR), Chaudron, Michel (AUTHOR)
Source: Behaviour & Information Technology. Nov2025, Vol. 44 Issue 18, p4473-4509. 37p.
Subjects: Generative artificial intelligence, Mobile apps, Power (Social sciences), Data analysis, Pilot projects, Research evaluation, Benevolence, Privacy, Natural language processing, Mann Whitney U Test, Descriptive statistics, Thematic analysis, Social values, Deep learning, Happiness, Statistics, Software architecture, Medical artifacts, Reaction time, Data analysis software, Case studies, Algorithms, Values (Ethics), Medical ethics, User interfaces, Nonparametric statistics
Abstract: Software is designed for humans and must account for their values. However, current research and practice focus on a narrow range of well-explored values, e.g. security, overlooking a more comprehensive perspective. Those exploring a broader array of values rely on manual identification, which is labour-intensive and prone to human bias. Moreover, existing methods offer limited reliability as they fail to explain their findings. In this paper, we propose leveraging the reasoning capabilities of Large Language Models (LLMs) for automated inference about values. This allows for not only detecting values but also explaining how they are expressed in the software. We aim to examine the effectiveness of LLMs, specifically ChatGPT (Chat Generative Pre-Trained Transformer), in automated detection and explanation of values in software artifacts. Using ChatGPT, we investigate how mobile APIs align with human values based on their documentation. Human evaluation of ChatGPT's findings shows a reciprocal shift in understanding values, with both ChatGPT and experts adjusting their assessments through dialogue. While experts recognise ChatGPT's potential for revealing values, emphasis is placed on human involvement to enhance the accuracy of the findings by detecting and eliminating convincing but inaccurate explanations provided by the language model due to potential hallucinations or confabulations. [ABSTRACT FROM AUTHOR]
Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Venturing ChatGPT's lens to explore human values in software artifacts: a case study of mobile APIs.
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  Data: Software is designed for humans and must account for their values. However, current research and practice focus on a narrow range of well-explored values, e.g. security, overlooking a more comprehensive perspective. Those exploring a broader array of values rely on manual identification, which is labour-intensive and prone to human bias. Moreover, existing methods offer limited reliability as they fail to explain their findings. In this paper, we propose leveraging the reasoning capabilities of Large Language Models (LLMs) for automated inference about values. This allows for not only detecting values but also explaining how they are expressed in the software. We aim to examine the effectiveness of LLMs, specifically ChatGPT (Chat Generative Pre-Trained Transformer), in automated detection and explanation of values in software artifacts. Using ChatGPT, we investigate how mobile APIs align with human values based on their documentation. Human evaluation of ChatGPT's findings shows a reciprocal shift in understanding values, with both ChatGPT and experts adjusting their assessments through dialogue. While experts recognise ChatGPT's potential for revealing values, emphasis is placed on human involvement to enhance the accuracy of the findings by detecting and eliminating convincing but inaccurate explanations provided by the language model due to potential hallucinations or confabulations. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1080/0144929X.2025.2478278
    Languages:
      – Code: eng
        Text: English
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        PageCount: 37
        StartPage: 4473
    Subjects:
      – SubjectFull: Generative artificial intelligence
        Type: general
      – SubjectFull: Mobile apps
        Type: general
      – SubjectFull: Power (Social sciences)
        Type: general
      – SubjectFull: Data analysis
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      – SubjectFull: Pilot projects
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      – SubjectFull: Research evaluation
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      – SubjectFull: Benevolence
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      – SubjectFull: Privacy
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      – SubjectFull: Natural language processing
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      – SubjectFull: Mann Whitney U Test
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      – SubjectFull: Descriptive statistics
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      – SubjectFull: Thematic analysis
        Type: general
      – SubjectFull: Social values
        Type: general
      – SubjectFull: Deep learning
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      – SubjectFull: Happiness
        Type: general
      – SubjectFull: Statistics
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      – SubjectFull: Nonparametric statistics
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      – TitleFull: Venturing ChatGPT's lens to explore human values in software artifacts: a case study of mobile APIs.
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              Text: Nov2025
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