Exploring the Impact of Explainability on Trust and Acceptance of Conversational Agents – A Wizard of Oz Study

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Abstract

With advancements in natural language processing and understanding, conversational agents (CAs) have become one of the fundamental modes of human-computer interaction. However, the black-box problem of AI algorithms often results in reduced acceptance of such systems. This calls for transparency and justification or rationale for the provided output from the users’ perspective. Explainable artificial intelligence (XAI) provides insights into the algorithms and elucidates outputs to the users, thus gaining more importance in various applications as a significant contributor to user acceptance and trust in artificial intelligence (AI) systems. This paper presents a Wizard of Oz user study with a between-subjects design comparing two versions of a vacation planning chatbot (low and high explainability) with 60 participants. The study explored the impact of explainability on users’ understanding, trust and acceptance. The results indicated that explanations (between-subject factor) significantly influence users’ understanding, trust and acceptance. According to our results, high explainability leads to increased trust and acceptance of the chatbot.

Original languageEnglish
Title of host publicationArtificial Intelligence in HCI - 5th International Conference, AI-HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Proceedings
EditorsHelmut Degen, Stavroula Ntoa
PublisherSpringer Science and Business Media Deutschland GmbH
Pages199-218
Number of pages20
ISBN (Print)9783031606052
DOIs
StatePublished - 2024
Event5th International Conference on Artificial Intelligence in HCI, AI-HCI 2024, held as part of the 26th HCI International Conference, HCII 2024 - Washington, United States
Duration: 29 Jun 20244 Jul 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14734 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Artificial Intelligence in HCI, AI-HCI 2024, held as part of the 26th HCI International Conference, HCII 2024
Country/TerritoryUnited States
CityWashington
Period29/06/244/07/24

Keywords

  • Chatbots
  • Conversational Agents
  • Explainable AI
  • Human-AI Interaction
  • Human-Centered Explainable AI

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