Is It Personal? The Impact of Personally Relevant Robotic Failures (PeRFs) on Humans' Trust, Likeability, and Willingness to Use the Robot

Romi Gideoni, Shanee Honig, Tal Oron-Gilad

Research output: Contribution to journalArticlepeer-review

Abstract

In three laboratory experiments, we examine the impact of personally relevant failures (PeRFs) on users’ perceptions of a collaborative robot. PeR is determined by how much a specific issue applies to a particular person, i.e., it affects one's own goals and values. We hypothesized that PeRFs would reduce trust in the robot and the robot's Likeability and Willingness to Use (LWtU) more than failures that are not personal to participants. To achieve PeR in human–robot interaction, we utilized three different manipulation mechanisms: (A) damage to property, (B) financial loss, and (C) first-person versus third-person failure scenarios. In total, 132 participants engaged with a robot in person during a collaborative task of laundry sorting. All three experiments took place in the same experimental environment, carefully designed to simulate a realistic laundry sorting scenario. Results indicate that the impact of PeRFs on perceptions of the robot varied across the studies. In experiments A and B, the encounters with PeRFs reduced trust significantly relative to a no failure session. But not entirely for LWtU. In experiment C, the PeR manipulation had no impact. The work highlights challenges and adjustments needed for studying robotic failures in laboratory settings. We show that PeR manipulations affect how users perceive a failing robot. The results bring about new questions regarding failure types and their perceived severity on users' perception of the robot. Putting PeR aside, we observed differences in the way users perceive interaction failures compared (experiment C) to how they perceive technical ones (A and B).

Original languageAmerican English
Pages (from-to)1049-1067
Number of pages19
JournalInternational Journal of Social Robotics
Volume16
Issue number6
DOIs
StatePublished - 1 Jun 2024

Keywords

  • Bystanders
  • Financial loss
  • Personal relevance
  • Property damage
  • Robot failures
  • Trust

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Philosophy
  • Social Psychology
  • Human-Computer Interaction
  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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