short-paper

Looks Can Permit Deceiving: How Reward or Punishment Decisions are Influenced by Robot Embodiment

Authors:

Kantwon Rogers,

Ayanna HowardAuthors Info & Claims

HRI '21 Companion: Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction

Pages 57 - 61

https://doi.org/10.1145/3434074.3447128

Published: 08 March 2021 Publication History

Abstract

As robots and artificially intelligent systems are given more cognitive capabilities and become more prevalent in our societies, the relationships they share with humans have become more nuanced. This paper aims to investigate the influences that embodiment has on a person's decision to reward or punish an honest or deceptive intelligent agent. We cast this exploration within a financial advisement scenario. Our results suggest that people are more likely to choose to reward a physically embodied intelligent agent over a virtual one irrespective of whether the agent has been deceptive or honest and even if this deception or honesty resulted in the individual gaining or losing money. Additionally, our results show that people are more averse to punishing intelligent agents, irrespective of the embodiment, which matches prior research in relation to human-human interaction. These results suggest that embodiment choices can have meaningful effects on the permissibility of deception conducted by intelligent agents.

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Cited By

Candon KZhou HGillet SVázquez MCastellano GRiek LCakmak MLeite I(2023)Verbally Soliciting Human Feedback in Continuous Human-Robot CollaborationProceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3568162.3576980(290-300)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3568162.3576980

Index Terms

Looks Can Permit Deceiving: How Reward or Punishment Decisions are Influenced by Robot Embodiment
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

HRI '21 Companion: Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction

March 2021

756 pages

ISBN:9781450382908

DOI:10.1145/3434074

General Chairs:
Cindy Bethel
Mississippi State University, USA
,
Ana Paiva
INESC-ID, IST, University of Lisbon, Portugal & Radcliffe Institute for Advanced Study, Harvard University, USA
,
Program Chairs:
Elizabeth Broadbent
University of Auckland, New Zealand
,
David Feil-Seifer
University of Nevada Reno, USA
,
Daniel Szafir
University of Colorado Boulder, USA

Copyright © 2021 ACM.

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Published: 08 March 2021

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HRI '21: ACM/IEEE International Conference on Human-Robot Interaction

March 8 - 11, 2021

CO, Boulder, USA

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Cited By

Candon KZhou HGillet SVázquez MCastellano GRiek LCakmak MLeite I(2023)Verbally Soliciting Human Feedback in Continuous Human-Robot CollaborationProceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3568162.3576980(290-300)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3568162.3576980

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