학술논문
Looks Can Permit Deceiving: How Reward or Punishment Decisions are Influenced by Robot Embodiment
Document Type
Conference
Author
Source
Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction. :57-61
Subject
Language
English
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.