Designing Trust in Highly Automated Virtual Assistants: A Taxonomy of Levels of Autonomy

Fernando Galdon, Ashley Hall, Stephen Jia Wang

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

Abstract

This paper presents a guiding framework and a multi-level taxonomy of automation levels specially adapted to Virtual Assistants in the context of Human-Human-Interaction. This trust-based framework incorporates interaction phases, trust-affecting design principles and design techniques. It also introduces a taxonomy of levels of autonomy explaining each level from a trust perspective. To test the proposed Levels a survey was conducted addressing different contexts. Participants preferred to have total control of the system. Level 1 is the preferred option on average. Levels 2 and 3, account for 40.50% of the participants preference to be in control of the autonomous system. If we combine levels 1, 2, and 3; This presents an average of 68.75% of participants demanding the initiative. The neutral level (level 4) is preferred by 15.75% of the participants on average. On Levels where the initiative resides on the system (levels 5, 6, and 7), only 14.75% of participants would decentralise their decision. Based on the research findings, the author recommends designers to combine a holistic perspective on trust with contextual awareness, to be able to integrate the impact of contexts on interactions. Trust formation is a dynamic process that starts before a user’s first contact with the system and continues long thereafter. Furthermore, as autonomous systems continuously evolve, factors-affecting trust change during user interactions with the system and over time; thus, Human-Human-Interaction concepts need to be able to adapt. Future work will be dedicated to further understanding other areas such as reparation and accountability.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Science and Business Media Deutschland GmbH
Pages199-211
Number of pages13
DOIs
Publication statusPublished - 28 Feb 2021
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume928
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

ASJC Scopus subject areas

  • Artificial Intelligence

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