The study, published in Science Robotics, is the first to examine brain activity, hormone levels, self-reported attitudes and behavior simultaneously during human-robot interaction. Researchers from Drexel University, the U.S. Air Force Academy, George Mason University and the University of Southern California tracked how people formed judgments about a humanoid robot named Pepper, and how quickly those judgments changed when the robot became unreliable.

Fifty healthy adult men took part in sessions lasting approximately two and a half hours at Drexel University’s Neuroergonomics and Neuroengineering Lab. Each participant held a face-to-face conversation with one of two versions of Pepper, which was secretly operated by a human following a scripted sequence. The expressive version made eye contact, gestured, nodded and used brief acknowledgments such as “uh-huh.” The other version delivered the same spoken content but remained completely still and offered no nonverbal signals.

The experiment consisted of three interactions. During the first two, Pepper remained accurate and coherent, allowing participants to develop familiarity and confidence in its responses. During the third, the robot began to fail in ways that resembled social misconduct rather than a simple technical malfunction. It made irrelevant comments, interrupted participants, asked them to repeat themselves and defended its recommendations with illogical explanations.

Participants also completed collaborative decision-making tasks. In one, they imagined being stranded on a deserted island and selected the most useful item from three choices before hearing Pepper argue for a different option. In another, they ranked five paintings by preference, listened to the robot’s critique and then had the opportunity to revise their rankings. Researchers recorded whether participants changed their decisions to follow Pepper’s recommendations, providing a behavioral measure of the robot’s influence.

The team collected brain data using functional near-infrared spectroscopy, or fNIRS, a wearable imaging method that estimates changes in blood oxygenation near the surface of the brain. Unlike conventional brain scanners, fNIRS can be used while a person is speaking and interacting naturally. The researchers focused particularly on prefrontal regions involved in reasoning, decision-making and interpreting the intentions of other individuals. Saliva samples taken at three points during each session were analyzed for oxytocin, a hormone often associated with social bonding and trust.

The expressive robot generated deeper engagement during its successful interactions. Participants responded more actively to it and appeared to treat it as a social partner rather than merely as a tool. However, that heightened engagement also increased the consequences of its mistakes. When the expressive Pepper began violating conversational norms, activity increased in the dorsolateral and medial prefrontal cortex—areas associated with social reasoning and the interpretation of other minds. The pattern suggested that participants were evaluating the robot’s behavior as an interpersonal event.

Trust declined after the robot’s errors in both experimental groups, but the consequences were more pronounced for the expressive machine. Participants’ willingness to follow its advice fell, and researchers calculated that the robot lost more than half of its influence over their decisions once it began making critical mistakes. With the stationary Pepper, participants appeared to interpret the same failures more like isolated mechanical glitches. Its behavior and the participants’ trust remained more loosely connected.

One of the study’s most unexpected findings involved oxytocin. Although the hormone is commonly linked with attachment and positive social relationships, participants’ oxytocin levels rose when the robot made mistakes and interrupted them—even as their trust in Pepper decreased. The researchers propose that, in human-robot interactions, oxytocin may sometimes reflect heightened social vigilance rather than emotional bonding. In the expressive-robot condition, the study found an exploratory sequence in which stronger coordination between prefrontal regions was associated with higher oxytocin, higher oxytocin was associated with lower trust, and lower trust predicted less willingness to follow the robot’s recommendations.

The findings point to a central design challenge for social robotics. Expressiveness can make a machine more engaging, understandable and socially acceptable, potentially supporting applications in healthcare, education, customer service and the home. But social cues also raise expectations. A robot that behaves like a conversational partner may be judged by standards normally applied to people, meaning that errors can be interpreted as failures of reliability or even character. The researchers therefore argue that competence must come before charm: an expressive robot that cannot consistently provide accurate and contextually appropriate assistance may not be safer or more effective, but simply more disappointing. As robots move into settings where people rely on their guidance, designers may need to balance social warmth with transparent limitations, robust performance and rapid recovery from mistakes.

Subject of Research: People

Article Title: Multilevel dynamics of the brain, hormones, mind, and behavior in social human-robot interaction

News Publication Date: 29-Jul-2026

Web References: https://drexel.edu/engineering-computing ; https://ayazlab.com/ ; https://www.science.org/doi/10.1126/scirobotics.aec1762

References: Topoglu Y, Krueger F, de Visser EJ, Ayaz H, et al. “Multilevel dynamics of the brain, hormones, mind, and behavior in social human-robot interaction.” Science Robotics. DOI: 10.1126/scirobotics.aec1762

Keywords: humanoid robots, social robotics, human-robot interaction, trust, oxytocin, fNIRS, brain activity, artificial intelligence, robot reliability, neuroergonomics

The award from ACM SIGCHI, widely regarded as the apex recognition in the Human-Computer Interaction (HCI) domain, acknowledges both academic rigor and far-reaching industrial impact. Kwak’s pioneering research trajectory explores the nuanced social cues inherent in human interactions—such as personality expression, linguistic nuances, gaze behavior, and gestural communication—and systematically incorporates these factors into robotic design. This approach is empirically substantiated to enhance user perception, build trust, and increase acceptance of robots within social and domestic contexts, thereby setting new standards in the design of human-robot interfaces.

Kwak’s vision extends beyond anthropomorphic or zoomorphic design schemas commonly found in robotics. She advocates for a transformative shift towards “robotic products”: everyday objects embedded with sophisticated perception, cognitive abilities, and action mechanisms. This conceptual evolution bridges a crucial gap between user expectations shaped by daily interactions with inanimate objects and the current technological framework deployed within robotics. The result is a seamless symbiosis where robots become invisible to users as machines, instead emerging implicitly through interactive products embedded in their environment.

Furthermore, Kwak’s work presents an advanced multi-robot system framework that enhances collaborative capabilities among distributed robotic products. This framework introduces the concept of a “mediator” entity tasked with orchestrating the interaction and coordination of multiple robotic units. Such a system architecture lays the groundwork for a highly integrated and adaptive robotic ecosystem capable of delivering complex, contextually aware services within smart environments. It anticipates not only isolated robotic functions but a networked collective intelligence that adapts fluidly to human needs and spatial dynamics.

The practical realization of Kwak’s theoretical constructs is evident in several innovative prototypes and commercial applications. Noteworthy among these is the HangulBot, an educational robot designed to facilitate language learning through interactive engagement. Additionally, CollaBot embodies a multi-robot cooperation system, showcasing intricate inter-robot communication and collaborative task execution. Modular robotic furniture like oOoBOT integrates adaptive robotic functionalities into everyday household items, while PopupBot illustrates transformative robotic spaces capable of reconfiguring environments dynamically. Each of these implementations substantiates the potential for human-centric smart environments empowered by robot-integrated products.

The significance of Kwak’s award transcends technical achievements—it underscores a paradigmatic shift in how technology institutes like KIST envision human-centered innovation. Embedding robotic intelligence within everyday objects aligns with growing societal demands for technologies that enhance quality of life without imposing cognitive or operational burdens on users. Kwak’s research encapsulates this ethos, emphasizing that the future of robotics lies not only in intelligent machines but in the invisibility of robotic augmentation embedded within our ordinary environments.

Kwak’s conceptual shift—from viewing robots as discrete entities towards perceiving them as interconnected, ambient robotic products—addresses fundamental challenges in user experience, trust-building, and ergonomic integration. Traditional robotic systems often face barriers due to their conspicuous nature and sometimes unpredictable behavior. By contrast, Kwak’s robotic products leverage subtle social cues and naturalistic interaction modalities, enabling users to engage intuitively and comfortably, thereby reducing alienation and improving acceptance.

The multi-robot ecosystem advanced in her work also introduces new paradigms in distributed intelligence and service delivery. This mediator-based coordination model exemplifies an emergent form of robotic collective cognition, where individual robotic products operate cohesively to address complex, multi-faceted human needs. Such an approach promises scalable solutions for smart homes, healthcare, education, and other application domains requiring nuanced environmental adaptation and personalized robotic assistance.

Kwak’s research trajectory further embraces AI-enabled interaction frameworks, which enhance robotic adaptability and personalization. The integration of interactive robotic furniture and the development of hyper-personalized smart spaces highlight an ambitious convergence of robotics, artificial intelligence, and environmental design. These interdisciplinary efforts aim to construct environments that are not only technologically sophisticated but empathetically attuned to their inhabitants’ preferences and routines.

The recognition by ACM SIGCHI also represents a broader validation of KIST’s foundational emphasis on placing “people” at the center of scientific inquiry and technological development. This approach aligns with international trends emphasizing ethical, user-centric design informed by comprehensive human factors analysis. Kwak’s accomplishments thus echo globally relevant themes of responsible innovation, highlighting the vital role of academia-industry collaboration in advancing next-generation human-robot ecosystems.

Looking ahead, Kwak and her research team are committed to expanding the boundaries of human-centered robot services. Future research directions include refining AI-based interactive robotic furniture, scaling collaborative multi-robot systems, and developing increasingly responsive and adaptive smart spaces. These envisioned advancements aim to further naturalize the presence of robots within ordinary environments, enhancing usability, social acceptance, and ultimately, human well-being.

Sonya S. Kwak’s SIGCHI Special Recognition Award not only celebrates individual brilliance but also heralds a new era for robotics seamlessly integrated into human lives. Her innovative paradigms demonstrate that the future of robotics lies in subtle, socially informed, and collaborative products, poised to transform everyday environments into smart, interactive spaces. Through meticulous research and visionary design, Kwak exemplifies the transformative potential of human-centered robotics on a global stage.

Subject of Research: Human-Robot Interaction, Robotic Product Design, Multi-Robot Systems, Human-Centered Robotics

Article Title: Sonya S. Kwak Receives SIGCHI Special Recognition Award for Groundbreaking Work in Human-Centered Robotic Product Design

News Publication Date: April 15, 2026

Web References: Korea Institute of Science and Technology (KIST)

Image Credits: Korea Institute of Science and Technology (KIST)

Keywords

Human-Computer Interaction, Robotics, Human-Robot Interaction, Robotic Products, Social Cues in Robotics, Multi-Robot Collaboration, AI in Robotics, Smart Environments, Human-Centered Design, Interactive Robotic Furniture, Robotic Ecosystems, ACM SIGCHI Awards