This chapter introduces the evolving concept of trust from a media perspective within the context of artificial intelligence (AI), examining its pivotal role in shaping public perceptions, media legitimacy, and technological acceptance. The erosion of trust in traditional media is shaped by factors such as economic inequality, political polarization, widespread misinformation, and the growing dominance of digital platforms that disrupt conventional news hierarchies. Drawing on interdisciplinary perspectives, the chapter explores how trust is conceptualized in psychology, sociology, philosophy, economics, and communication theory, highlighting its multi-level and relational nature. Media trust is increasingly influenced by the integration of technology, particularly through the growing role of artificial intelligence in the production, curation, and dissemination of news. As media environments become more algorithmically driven, the boundaries between trust in media and trust in technology begin to blur. Trust in AI is shaped by a complex interplay of human dispositions, contextual settings, and technological factors such as transparency, reliability, and explainability. At the same time, widespread concerns, ranging from surveillance and algorithmic bias to manipulation and unclear accountability, highlight the pressing need for systems that are both trustworthy and ethically designed. Addressing these challenges, the chapter outlines key research themes and future directions, calling for interdisciplinary and ethically grounded frameworks to assess and foster trust in AI-powered media systems, as a foundation for democratic resilience and informed public discourse.

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Impact of AI on Trust in the Media

  • Castulus Kolo,
  • Joschka Mütterlein,
  • Sarah Anna Schmid

摘要

This chapter introduces the evolving concept of trust from a media perspective within the context of artificial intelligence (AI), examining its pivotal role in shaping public perceptions, media legitimacy, and technological acceptance. The erosion of trust in traditional media is shaped by factors such as economic inequality, political polarization, widespread misinformation, and the growing dominance of digital platforms that disrupt conventional news hierarchies. Drawing on interdisciplinary perspectives, the chapter explores how trust is conceptualized in psychology, sociology, philosophy, economics, and communication theory, highlighting its multi-level and relational nature. Media trust is increasingly influenced by the integration of technology, particularly through the growing role of artificial intelligence in the production, curation, and dissemination of news. As media environments become more algorithmically driven, the boundaries between trust in media and trust in technology begin to blur. Trust in AI is shaped by a complex interplay of human dispositions, contextual settings, and technological factors such as transparency, reliability, and explainability. At the same time, widespread concerns, ranging from surveillance and algorithmic bias to manipulation and unclear accountability, highlight the pressing need for systems that are both trustworthy and ethically designed. Addressing these challenges, the chapter outlines key research themes and future directions, calling for interdisciplinary and ethically grounded frameworks to assess and foster trust in AI-powered media systems, as a foundation for democratic resilience and informed public discourse.