Human Perception of Trust in AI-Assisted Communication Systems

Abstract

Artificial Intelligence (AI) has transformed modern communication systems by enabling intelligent interactions, automated content generation, personalized recommendations, real-time translation, and conversational support. The widespread adoption of AI in areas such as social media, healthcare, education, customer service, and enterprise communication depends largely on user trust. Trust in AI communication systems is influenced by factors such as transparency, reliability, explainability, privacy, fairness, and accuracy. However, concerns regarding bias, misinformation, data privacy, and lack of explainability can reduce user confidence. This study examines technological, psychological, and social factors affecting trust in AI-based communication systems. The findings reveal that transparency, reliability, privacy protection, and explainability are critical for building long-term user trust. The study concludes that trust is a multidimensional concept involving technical performance, ethical considerations, and user experience, highlighting the need for trustworthy AI systems to support effective and responsible digital communication.