A new study suggests that the transparency of facial recognition technology in human–robot interaction increases users’ social presence, reduces privacy concerns and enhances users’ acceptance of robots.

The findings by Kun Xu, University of Florida College of Journalism and Communications (UFCJC) assistant professor in emerging media, UFCJC doctoral students Xiaobei Chen and Fanjue Liu, and Missouri Western State University Assistant Professor Luloing Huang were featured in “What Did You Hear and What Did You See? Understanding the Transparency of Facial Recognition and Speech Recognition Systems During Human-Robot Interaction” published in New Media & Society on June 2.

According to the authors, “This study unpacks the black box of a social robot’s working mechanisms and delves into the effects of showing participants a robot’s facial and speech recognition systems during human–robot communication breakdowns. By analyzing both quantitative and qualitative responses, we parse out the paradoxical effects of making a social robot’s AI technologies transparent and comprehensible.”

They add,  “Overall, this study suggests that proper use of transparency could relieve users’ privacy concerns and increase users’ acceptance of the robot. Although users have mixed feelings about the facial and speech recognition technologies in human-robot interaction, their overall attitudes

Posted: June 20, 2024
Category: AI at CJC News, College News, Student News
Tagged as: AI, Fanjue Liu, Human-Robot Interaction, Kun Xu, New Media & Society, Xiaobei Chen