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A Study on the Benefits and Drawbacks of Adaptivity in AI-generated Explanations

Published: 22 December 2023 Publication History

Abstract

It is commonly assumed that explanations should be tailored to the addressee in order to yield higher understanding. Consequently, much work on explainable intelligent agents has been directed to user-adapted explanations. However, recent studies show ambiguous results with regard to the efficiency of adaptive and non-adaptive explanations. This raises the question whether an explanation, generated by a socially interactive agent, should be adapted. In this paper, we present a general approach to adaptive explanation generation as a non-stationary decision process, and we study the benefits and pitfalls of adapting explanations in an ongoing interaction with a user. Specifically, we report results from a between-subject online evaluation in a game explanation domain with three conditions (non-interactive, interactive but non-adaptive, adaptive). Results show that the decision for or against adaptivity depends on the goal of the explanation, the complexity of the domain and external constraints. Based on the collected data we discuss challenges that arise from the individuality of adaptive dialogues, such as comparability and the tendency to produce results with a large variance.

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Cited By

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  • (2024)A Study on Integrating Representational Gestures into Automatically Generated Embodied ExplanationsProceedings of the 24th ACM International Conference on Intelligent Virtual Agents10.1145/3652988.3673919(1-5)Online publication date: 16-Sep-2024
  • (2024)Towards Balancing Preference and Performance through Adaptive Personalized ExplainabilityProceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610977.3635000(658-668)Online publication date: 11-Mar-2024
  • (2024)Personalization through Adaptivity or Adaptability? A Meta-analysis on Simulation-based Learning in Higher EducationEducational Research Review10.1016/j.edurev.2024.100662(100662)Online publication date: Dec-2024

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cover image ACM Conferences
IVA '23: Proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents
September 2023
376 pages
ISBN:9781450399944
DOI:10.1145/3570945
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 22 December 2023
Accepted: 22 June 2023
Received: 25 April 2023

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Author Tags

  1. Adaptivity
  2. Dynamic Planning
  3. Efficiency
  4. Explainability
  5. User Study
  6. XAI

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Cited By

View all
  • (2024)A Study on Integrating Representational Gestures into Automatically Generated Embodied ExplanationsProceedings of the 24th ACM International Conference on Intelligent Virtual Agents10.1145/3652988.3673919(1-5)Online publication date: 16-Sep-2024
  • (2024)Towards Balancing Preference and Performance through Adaptive Personalized ExplainabilityProceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610977.3635000(658-668)Online publication date: 11-Mar-2024
  • (2024)Personalization through Adaptivity or Adaptability? A Meta-analysis on Simulation-based Learning in Higher EducationEducational Research Review10.1016/j.edurev.2024.100662(100662)Online publication date: Dec-2024

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