Expectation management in child-robot interaction

Mike Ligthart, O. Blanson Henkemans, Koen Hindriks, Mark Neerincx

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

9 Citations (Scopus)

Abstract

Children are eager to anthropomorphize (ascribe human attributes to) social robots. As a consequence they expect a more unconstrained, substantive and useful interaction with the robot than is possible with the current state-of-the art. In this paper we reflect on several of our user studies and investigate the form and role of expectations in child-robot interaction. We have found that the effectiveness of the social assistance of the robot is negatively influenced by misaligned expectations. We propose three strategies that have to be worked out for the management of expectations in child-robot interaction: 1) be aware of and analyze children's expectations, 2) educate children, and 3) acknowledge robots are (perceived as) a new kind of `living' entity besides humans and animals that we need to make responsible for managing expectations.
Original languageEnglish
Title of host publication26th IEEE International Symposium on Robot and Human Interactive Communication, IEEE RO-MAN 2017
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages916-921
Number of pages6
ISBN (Electronic)978-1-5386-3518-6
ISBN (Print)978-1-5386-3519-3
DOIs
Publication statusPublished - Aug 2017
EventIEEE RO-MAN 2017: 26th IEEE International Symposium on Robot and Human Interactive Communication - Human-Robot Collaboration and Human Assistance for an Improved Quality of Life - Lisbon, Portugal
Duration: 28 Aug 20171 Sept 2017
Conference number: 26

Conference

ConferenceIEEE RO-MAN 2017
Country/TerritoryPortugal
CityLisbon
Period28/08/171/09/17

Keywords

  • Robots
  • Diabetes
  • Pediatrics
  • Avatars
  • Human-robot interaction
  • Hospitals
  • Interviews

Fingerprint

Dive into the research topics of 'Expectation management in child-robot interaction'. Together they form a unique fingerprint.

Cite this