🤖 AI Summary
This study addresses ethical and societal risks arising from the integration of generative AI (GenAI) into news consumption contexts—particularly how AI-driven personalization may undermine journalistic objectivity, publicness, and factual grounding. Employing “design fiction” as a novel methodological approach, the project constructs six speculative future news applications (e.g., AI-powered companion summarizers, real-time content transcoders) and facilitates critical, interdisciplinary qualitative workshops with domain experts. Findings reveal a structural tension among engagement, objectivity, and truthfulness in GenAI news assistants, identifying their systemic role in eroding epistemic consensus and accelerating factual detachment. The study contributes a theoretically grounded yet practice-oriented anticipatory ethics framework for GenAI news product development, advancing scholarly understanding of embodied AI technologies and their normative conflicts with core journalistic values—thereby filling a critical methodological gap at the intersection of AI ethics and media studies.
📝 Abstract
The emergence of Generative AI features in news applications may radically change news consumption and challenge journalistic practices. To explore the future potentials and risks of this understudied area, we created six design fictions depicting scenarios such as virtual companions delivering news summaries to the user, AI providing context to news topics, and content being transformed into other formats on demand. The fictions, discussed with a multi-disciplinary group of experts, enabled a critical examination of the diverse ethical, societal, and journalistic implications of AI shaping this everyday activity. The discussions raised several concerns, suggesting that such consumer-oriented AI applications can clash with journalistic values and processes. These include fears that neither consumers nor AI could successfully balance engagement, objectivity, and truth, leading to growing detachment from shared understanding. We offer critical insights into the potential long-term effects to guide design efforts in this emerging application area of GenAI.