Social Neuroergonomics of Human-Agent Interaction

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Background

While neuroergonomics has been defined as “the brain at work”, social neuroergonomics can be defined as “the brain working with other agents”. Such agents can include many types of emerging technology such as robots, virtual agents, and automation that are now endowed with varying degrees of human-like social features and behaviors. Some researchers have indicated that creating a socially capable robot is as hard as creating a generally intelligent system (AI-complete). The recent 2020 US robotics roadmap has outlined many issues regarding the creation of socially intelligent robotic systems and understanding social interactions with these human-agent systems. Integrated efforts of roboticists, psychologists, ergonomists, and neuroscientists have started to elucidate a deeper understanding of social neuroergonomics. However, further integration of findings from diverse domains and different levels of explanation (i.e., genes, hormones/neurotransmitters, brain circuits, mental processes, and behaviors) into a conceptual neurobiological framework of social neuroergonomics is still lacking. Researchers have called for the need to integrate more neuroscience with robotics work to the benefit of both fields.

The goal of the proposed Research Topic is to provide a comprehensive collection of human-agent interaction studies. Researchers and scholars from diverse backgrounds —social cognitive and affective neuroscience, decision neuroscience, developmental neuroscience, cultural neuroscience, neuropsychology, computational psychiatry, and neuroergonomics— are invited to submit original empirical work. Shedding light on our understanding of how social neuroergonomics is encoded in our brain, examples for pressing, relevant, and timely research questions are:

• Automated systems (e.g., social robots, artificial intelligence) are increasingly taking on numerous roles in human society. Do human-human and human-automation trust share the same neuropsychological mechanisms and how could this information be used to calibrate human trust in autonomous systems? What types of explanations and transparency are needed to better calibrate human trust in autonomous systems?

• Many intelligent systems are designed for basic and short-term interaction. Many challenges emerge when humans have to interact with agents and robots over long periods of time. What are useful and predictive models for long-term interaction with robots, virtual agents, or AI systems?

• Passive brain-computer interface (BCI) systems have recently been developed that use mappings of functional areas of the brain to monitor and passive response to neural responses. How might these systems be adapted and used as an input for virtual or robotic agents to help respond socially to humans?

• New developments in mobile neural imagining and recording have enabled researchers to assess neural signatures in more realistic contexts with expert users such as in air traffic control and aviation. Roboticists haven’t necessarily taken advantage of this yet. For example, what are neural signatures in the context of medical, commercial, military, and educational domains?

Tackling these and other questions, the proposed work utilizes various methodologies, combining behavioral paradigms with functional neuroimaging (e.g., MRI, NIRS, MEG, EEG, ERP) and stimulation (e.g., TMS, tDCS) methodologies as well as neuroendocrinological, neuropharmacological, and neurogenetic methodologies. The research topic will facilitate, broaden, and improve the current state of social neuroergonomics research, serving as a significant milestone in understanding the neurobiological signatures of social neuroergonomics of human-agent interactions. Integrating findings into a conceptual framework will guide future investigations about the nature and mechanisms of social neuroergonomics in the context of human-agent interaction.

This Research Topic calls for submissions that cover recent approaches and emerging new directions in social neuroergonomics and attempt to chart a path toward a better understanding of the neurophysiological measures and their relationship to human-agent interaction. Submissions can be any article type covering advanced neuroscience methods and techniques as well as neuroimaging analysis approaches to investigate brain dynamics in actively behaving participants in field settings. Application of these technologies to investigate cognition, emotion, perception, decision making, attention, mental state, and performance monitoring, and related areas relevant to social and applied neuroscience are especially invited.

Keywords: Human-robot interaction, Social interaction, Automation, Long-term interaction, Trust

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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