Individual differences that predict interactions in mixed-initiative teams

Bianca M. Zongrone, Douglas C. Derrick, Gina Scott Ligon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


Humans and machines are collaborating in new ways and organizations are increasingly leveraging mixed-initiative teams. We examine the effect that an individual's personality has on his or her willingness to: (1) seek assistance from and/or (2) accept the recommendations of an automated teammate. We use a game of pure strategy with a perfectly accurate decision-assisting automated agent to examine how personality predicts these interactions. Forty-nine participants played 3 rounds of a decision game called 'Pirate Island.' Each participant made 27 total decisions (9 decisions per round over 3 rounds) and had the option to solicit assistance from an automated agent for each decision. Participants were not told that the agent was 100% accurate, only that it could help them. We found that people low on extroversion and high on agreeableness were highly correlated to soliciting recommendations from an agent. However, only those high on agreeableness actually accepted recommendations.

Original languageEnglish (US)
Title of host publicationProceedings of the 48th Annual Hawaii International Conference on System Sciences, HICSS 2015
EditorsTung X. Bui, Ralph H. Sprague
PublisherIEEE Computer Society
Number of pages9
ISBN (Electronic)9781479973675
StatePublished - Mar 26 2015
Event48th Annual Hawaii International Conference on System Sciences, HICSS 2015 - Kauai, United States
Duration: Jan 5 2015Jan 8 2015

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Print)1530-1605


Other48th Annual Hawaii International Conference on System Sciences, HICSS 2015
Country/TerritoryUnited States


  • Automated agents
  • Decision making
  • Personality

ASJC Scopus subject areas

  • Engineering(all)

Cite this