Affective and Cognitive Engagement with Political Conversational AI Agents: Evidence from the Rubens Jr Case

This experimental study aimed to evaluate the affective and cognitive engagement of users when interacting with a conversational artificial intelligence (AI) agent using a humanized voice—specifically, that of Brazilian congressman Rubens Pereira Jr. Twenty participants were divided into two groups: one familiar with the politician and another without prior familiarity. During five minutes of free interaction with the AI agent, neurophysiological data were collected via a portable EEG device (Brainlink Dual), recording signals across delta, theta, alpha, beta, and gamma bands. The findings reveal that the humanized voice produced a significant increase in high-beta and low-gamma activity—markers of cognitive engagement—especially among younger participants and those unfamiliar with the politician. Conversely, participants who recognized the voice exhibited greater theta and low-alpha activation, indicating higher affective engagement and memory recall. Gender differences were also observed: women showed higher affective activation, while men displayed greater cognitive focus. The results suggest that voice personalization in AI agents fosters emotional bonds and enhances attention, making it a promising strategy for public communication, political marketing, and personalized education. The study advances the field by integrating continuous EEG data with qualitative self-reports, offering a multidimensional perspective on human-AI interaction. In practical terms, humanizing AI agents with familiar and expressive voices can strengthen user trust, empathy, and engagement, including among older participants. These findings highlight the value of human-like voice strategies for more effective digital communication and citizen engagement.