"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction

Sunnie S.Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong, Andrés Monroy-Hernández

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

16 Scopus citations

Abstract

Despite the proliferation of explainable AI (XAI) methods, little is understood about end-users' explainability needs and behaviors around XAI explanations. To address this gap and contribute to understanding how explainability can support human-AI interaction, we conducted a mixed-methods study with 20 end-users of a real-world AI application, the Merlin bird identification app, and inquired about their XAI needs, uses, and perceptions. We found that participants desire practically useful information that can improve their collaboration with the AI, more so than technical system details. Relatedly, participants intended to use XAI explanations for various purposes beyond understanding the AI's outputs: calibrating trust, improving their task skills, changing their behavior to supply better inputs to the AI, and giving constructive feedback to developers. Finally, among existing XAI approaches, participants preferred part-based explanations that resemble human reasoning and explanations. We discuss the implications of our findings and provide recommendations for future XAI design.

Original languageEnglish (US)
Title of host publicationCHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450394215
DOIs
StatePublished - Apr 19 2023
Event2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 - Hamburg, Germany
Duration: Apr 23 2023Apr 28 2023

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2023 CHI Conference on Human Factors in Computing Systems, CHI 2023
Country/TerritoryGermany
CityHamburg
Period4/23/234/28/23

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Keywords

  • Explainable AI (XAI)
  • Human-AI Collaboration
  • Human-AI Interaction
  • Human-Centered XAI
  • Interpretability
  • Local Explanations
  • XAI for Computer Vision

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