Modeling human-robot trust in emergencies

Paul Robinette, Alan R. Wagner, Ayanna M. Howard

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

4 Scopus citations

Abstract

Modeling human trust decisions is a notoriously difficult problem. We focus on decisions where a victim must decide whether to trust a robot in an emergency situation and outline the necessary inputs to model this decision. These inputs can each be represented as an outcome matrix and combined using a weighted sum. Calibrating these weights can be accomplished through the use of internet surveys.

Original languageEnglish (US)
Title of host publicationThe Intersection of Robust Intelligence and Trust in Autonomous Systems - Papers from the AAAI Spring Symposium, Technical Report
PublisherAI Access Foundation
Pages62-63
Number of pages2
ISBN (Print)9781577356448
StatePublished - Jan 1 2014
Event2014 AAAI Spring Symposium - Palo Alto, CA, United States
Duration: Mar 24 2014Mar 26 2014

Publication series

NameAAAI Spring Symposium - Technical Report
VolumeSS-14-04

Other

Other2014 AAAI Spring Symposium
CountryUnited States
CityPalo Alto, CA
Period3/24/143/26/14

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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  • Cite this

    Robinette, P., Wagner, A. R., & Howard, A. M. (2014). Modeling human-robot trust in emergencies. In The Intersection of Robust Intelligence and Trust in Autonomous Systems - Papers from the AAAI Spring Symposium, Technical Report (pp. 62-63). (AAAI Spring Symposium - Technical Report; Vol. SS-14-04). AI Access Foundation.