Blind Trust: How Making a Device Humanoid Reduces the Impact of Functional Errors on Trust

Christopher, Vattheuer,; Baecker, Annalena Nora; Geiskkovitch, Denise Y.; Seo, Stela H.; Rea, Daniel J.; Young, James E.

doi:10.1007/978-3-030-62056-1_18

Cited by 2 publications

(1 citation statement)

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“…Social human-robot interaction has explored the use of priming, or a variant called framing ( Westlund et al, 2016 ; Sanoubari et al, 2018 ; Liu, 2020 ; Wallkötter et al, 2020 ) in social interactions between people and social robots. More generally, it has been argued for some time that user expectations and perceptions are crucial for shaping their expectations and willingness to interact with autonomous social robots ( Lindgaard et al, 2006 ; Mitra and Golder, 2006 ; Young et al, 2009 ; Edwards et al, 2019 ; Reich-Stiebert et al, 2019 ; Vattheuer et al, 2020 ). In the priming direction, some work has shown how subtle shifts in language used to describe a robots can influence how personal ( Coeckelbergh, 2011 ) or human-like ( Anna et al, 2012 ) people view or treat the robots ( Sam and Tom, 2017 ).…”

Section: Related Workmentioning

confidence: 99%

It’s not what you think: shaping beliefs about a robot to influence a teleoperator’s expectations and behavior

Rea,

Young

2023

Front. Robot. AI

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In this paper we present a novel design approach for shaping a teleoperator’s expectations and behaviors when teleoperating a robot. Just as how people may drive a car differently based on their expectations of it (e.g., the brakes may be poor), we assert that teleoperators may likewise operate a robot differently based on expectations of robot capability and robustness. We present 3 novel interaction designs that proactively shape teleoperator perceptions, and the results from formal studies that demonstrate that these techniques do indeed shape operator perceptions, and in some cases, measures of driving behavior such as changes in collisions. Our methods shape operator perceptions of a robot’s speed, weight, or overall safety, designed to encourage them to drive more safely. This approach shows promise as an avenue for improving teleoperator effectiveness without requiring changes to a robot, novel sensors, algorithms, or other functionality.

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