Xiaobei Chen

About

Xiaobei Chen is a leading voice in human–machine communication, exploring how people unconsciously treat technologies as social actors. Her work centers on the “Computers are Social Actors” (CASA) paradigm and its evolution into the “Media are Social Actors” (MASA) framework, which she has advanced to better explain and predict social responses to artificial agents. Chen’s most cited paper, “Deep mind in social responses to technologies” (2022, 124 citations), introduces a novel cognitive mechanism underlying these phenomena, bridging social psychology and AI design. Her 2024 study on transparency in facial and speech recognition systems during human–robot interaction (7 citations) addresses a pressing ethical and usability challenge: how to make social robots’ inner workings understandable to users. In her 2023 theoretical synthesis of the MASA paradigm (6 citations), she consolidates decades of evidence and charts a roadmap for future research. Chen’s contributions are vital for designing more intuitive, trustworthy social robots and for deepening our theoretical grasp of human–technology relationships. Her work is essential reading for scholars in human–robot interaction, AI ethics, and media psychology.

Research Focus

Key Achievements

Top Papers

1. 1
   Deep mind in social responses to technologies: A new approach to explaining the Computers are Social Actors phenomena

   124 citations · 2022
2. 2
   What did you hear and what did you see? Understanding the transparency of facial recognition and speech recognition systems during human–robot interaction

   7 citations · 2024
3. 3
   The Media Are Social Actors paradigm and beyond: theory, evidence, and future research

   6 citations · 2023

Key Collaborators

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