Which biases and reasoning pitfalls do explanations trigger? Decomposing communication processes in human-AI interaction

Caterina Moruzzi, Mennatallah El-Assady*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Collaborative human–AI problem-solving and decision making rely on effective communications between both agents. Such communication processes comprise explanations and interactions between a sender and a receiver. Investigating these dynamics is crucial to avoid miscommunication problems. Hence, in this article, we propose a communication dynamics model, examining the impact of the sender’s explanation intention and strategy on the receiver’s perception of explanation effects. We further present potential biases and reasoning pitfalls with the aim of contributing to the design of hybrid intelligence systems. Finally, we propose six desiderata for human-centered explainable AI and discuss future research opportunities.
Original languageEnglish
Pages (from-to)11-23
Number of pages13
JournalIEEE Computer Graphics and Applications
Volume42
Issue number6
Early online date12 Sept 2022
DOIs
Publication statusPublished - 13 Dec 2022

Keywords / Materials (for Non-textual outputs)

  • adaptation models
  • Artificial Intelligence
  • receivers
  • knowledge representation
  • cognition
  • decision-making
  • problem solving

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