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  1. “Your friendly AI assistant”: the anthropomorphic self-representations of ChatGPT and its implications for imagining AI.Karin van Es & Dennis Nguyen - forthcoming - AI and Society:1-13.
    This study analyzes how ChatGPT portrays and describes itself, revealing misleading myths about AI technologies, specifically conversational agents based on large language models. This analysis allows for critical reflection on the potential harm these misconceptions may pose for public understanding of AI and related technologies. While previous research has explored AI discourses and representations more generally, few studies focus specifically on AI chatbots. To narrow this research gap, an experimental-qualitative investigation into auto-generated AI representations based on prompting was conducted. Over (...)
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  • Who shares about AI? Media exposure, psychological proximity, performance expectancy, and information sharing about artificial intelligence online.Alex W. Kirkpatrick, Amanda D. Boyd & Jay D. Hmielowski - forthcoming - AI and Society:1-12.
    Media exposure can shape audience perceptions surrounding novel innovations, such as artificial intelligence (AI), and could influence whether they share information about AI with others online. This study examines the indirect association between exposure to AI in the media and information sharing about AI online. We surveyed 567 US citizens aged 18 and older in November 2020, several months after the release of Open AI’s transformative GPT-3 model. Results suggest that AI media exposure was related to online information sharing through (...)
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  • Promoting responsible AI : A European perspective on the governance of artificial intelligence in media and journalism.Colin Porlezza - 2023 - Communications 48 (3):370-394.
    Artificial intelligence and automation have become pervasive in news media, influencing journalism from news gathering to news distribution. As algorithms are increasingly determining editorial decisions, specific concerns have been raised with regard to the responsible and accountable use of AI-driven tools by news media, encompassing new regulatory and ethical questions. This contribution aims to analyze whether and to what extent the use of AI technology in news media and journalism is currently regulated and debated within the European Union and the (...)
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  • Controlling the uncontrollable: the public discourse on artificial intelligence between the positions of social and technological determinism.Marek Winkel - forthcoming - AI and Society:1-13.
    Since the publication of ChatGPT and Dall-E, there has been heavy discussions on the possible dangers of generative artificial intelligence (AI) for society. These discussions question the extent to which the development of AI can be regulated by politics, law, and civic actors. An important arena for discourse on AI is the news media. The news media discursively construct AI as a technology that is more or less possible to regulate. There are various reasons for an assumed regulatability. Some voices (...)
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  • How ChatGPT Changed the Media’s Narratives on AI: A Semi-automated Narrative Analysis Through Frame Semantics.Igor Ryazanov, Carl Öhman & Johanna Björklund - 2024 - Minds and Machines 35 (1):1-24.
    We perform a mixed-method frame semantics-based analysis on a dataset of more than 49,000 sentences collected from 5846 news articles that mention AI. The dataset covers the twelve-month period centred around the launch of OpenAI’s chatbot ChatGPT and is collected from the most visited open-access English-language news publishers. Our findings indicate that during the six months succeeding the launch, media attention rose tenfold—from already historically high levels. During this period, discourse has become increasingly centred around experts and political leaders, and (...)
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  • Americans’ views of artificial intelligence: identifying and measuring aversion.Will Livingston - forthcoming - AI and Society:1-15.
    This study explores the phenomenon of artificial intelligence (AI) aversion within the context of public policy, building on prior research on algorithmic aversion. I aim to establish a clear conceptual distinction between algorithms and AI in the public’s perception and develop a robust metric for assessing AI aversion. Utilizing a national survey, I employed affective imagery testing to compare Americans emotional responses towards AI, algorithms, and advanced technology. The findings reveal that AI elicits significantly more negative emotional responses than the (...)
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