Exoskeletons are an emerging form of technology that combines the skills of both machines and humans to give wearers the ability to complete physically demanding tasks that would be too strenuous for most humans. Exoskeleton adoption has the potential to both enhance and disrupt many aspects of work, including power dynamics in the workplace and the human-machine interactions that take place. Dyadic Power Theory (DPT) is a useful theory for exploring the impacts of exoskeleton adoption. In this conceptual paper, we extend DPT to relationships between humans and machines in organizations, as well as human-human communication where use of an exoskeleton has resulted in shifts of power.
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Who's Leading This Dance?: Theorizing Automatic and Strategic Synchrony in Human-Exoskeleton Interactions
Wearable robots are an emerging form of technology that allow organizations to combine the strength, precision, and performance of machines with the flexibility, intelligence, and problem-solving abilities of human wearers. Active exoskeletons are a type of wearable robot that gives wearers the ability to effortlessly lift up to 200 lbs., as well as perform other types of physically demanding tasks that would be too strenuous for most humans. Synchronization between exoskeleton suits and wearers is one of the most challenging requirements to operate these technologies effectively. In this conceptual paper, we extend interpersonal adaption theory (IAT) to the exoskeleton context and explicate (a) the antecedents that are most likely to shape synchrony in human-exoskeleton interactions, (b) automatic and strategic synchrony as adaptive behaviors in human-exoskeleton interactions, and (c) outcome variables that are especially important in these processes. Lastly, we offer a discussion of key methodological challenges for measuring synchrony in human-exoskeleton interactions and offer a future research agenda for this important area.
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- Award ID(s):
- 1839946
- PAR ID:
- 10290150
- Date Published:
- Journal Name:
- Frontiers in Psychology
- Volume:
- 12
- ISSN:
- 1664-1078
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fpsyg.2021.624108
