Evidence map›Paper›PMID 39301050›Full record

ArticleFrontiers in robotics and AI2024

Human perceptions of social robot deception behaviors: an exploratory analysis.

Andres Rosero, Elizabeth Dula, Harris Kelly, Bertram F Malle, Elizabeth K Phillips

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Andres RoseroApplied Psychology and Autonomous Systems Lab, Department of Psychology, College of Humanities and Social Sciences, George Mason University, Fairfax, VA, United States.
Elizabeth DulaApplied Psychology and Autonomous Systems Lab, Department of Psychology, College of Humanities and Social Sciences, George Mason University, Fairfax, VA, United States.
Harris KellyApplied Psychology and Autonomous Systems Lab, Department of Psychology, College of Humanities and Social Sciences, George Mason University, Fairfax, VA, United States.
Bertram F MalleSocial Cognitive Science Research Lab, Department of Cognitive and Psychological Sciences, Brown University, Providence, RI, United States.
Elizabeth K PhillipsApplied Psychology and Autonomous Systems Lab, Department of Psychology, College of Humanities and Social Sciences, George Mason University, Fairfax, VA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Robots are being introduced into increasingly social environments. As these robots become more ingrained in social spaces, they will have to abide by the social norms that guide human interactions. At times, however, robots will violate norms and perhaps even deceive their human interaction partners. This study provides some of the first evidence for how people perceive and evaluate robot deception, especially three types of deception behaviors theorized in the technology ethics literature: External state deception (cues that intentionally misrepresent or omit details from the external world: e.g., lying), Hidden state deception (cues designed to conceal or obscure the presence of a capacity or internal state the robot possesses), and Superficial state deception (cues that suggest a robot has some capacity or internal state that it lacks). Methods: Participants (N = 498) were assigned to read one of three vignettes, each corresponding to one of the deceptive behavior types. Participants provided responses to qualitative and quantitative measures, which examined to what degree people approved of the behaviors, perceived them to be deceptive, found them to be justified, and believed that other agents were involved in the robots' deceptive behavior. Results: Participants rated hidden state deception as the most deceptive and approved of it the least among the three deception types. They considered external state and superficial state deception behaviors to be comparably deceptive; but while external state deception was generally approved, superficial state deception was not. Participants in the hidden state condition often implicated agents other than the robot in the deception. Conclusion: This study provides some of the first evidence for how people perceive and evaluate the deceptiveness of robot deception behavior types. This study found that people people distinguish among the three types of deception behaviors and see them as differently deceptive and approve of them differently. They also see at least the hidden state deception as stemming more from the designers than the robot itself.

Indexed as

deceptiondeceptive anthropomorphismhuman-robot interactionjustificationsrobots

Identifiers

PMID39301050
PMCPMC11411098

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.