Synthetic Smiles and Robotic Voices: Decoding Kinesics in AI-Generated News Anchors in Indian Public and Private Broadcasts

Abstract

As artificial intelligence (AI) becomes more common in the field of media, the use of AI-generated news anchors raises important concerns about authenticity, emotional expressiveness, and audience connection. This study examines the kinesics, or nonverbal communication cues such as facial expressions, voice modulation, hand gestures, and body movements, of AI news anchors on public (DD Kisan) and private (Aaj Tak AI) news channels. Using a structured observation method and qualitative video content analysis, this study assessed four AI anchors (Bhoomi, Krish, Sana, and Naina) across 160 news segments broadcast between August 2024 and February 2025. The findings show that AI anchors displayed robotic and repetitive kinesics patterns, including rigid postures, misaligned lip movements, flat speech modulation, and limited gesture. While some variation was observed, particularly with Naina showing relatively better expressiveness, AI presenters overall lacked the emotional depth and dynamism of human anchormen. These limitations reduce audience engagement and credibility and contribute to the “uncanny valley” effect. This study provides a gap in prior study by focusing kinesics rather than textual or technical issues. It provides insights about how to improve the accuracy and trustworthiness of AI news anchors while also adding to discussions about AI-human interaction and the future of automated journalism.