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Frontiers in Computer Science
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
DBLP
Article . 2025
Data sources: DBLP
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Forgiveness in human-machine interaction

Authors: Inbal Holtzman; Galit Nimrod;

Forgiveness in human-machine interaction

Abstract

Forgiveness has been extensively studied across various academic fields, but not in relation to Human-Machine Interaction (HMI). The work presented in this article aims to answer two interrelated questions: what is forgiveness in HMI, and how do we forgive an erring technology? Relying on a literature review of both forgiveness and HMI studies, the article offers a holistic definition of the concept, according to which forgiveness in HMI is a shift in the users’ feelings, from negative to positive, that prevents the users from abandoning the erring technology and allows them to keep using it without resentment. Based on a pioneering focus groups study with a convenience sample of 27 young adults, four forgiveness mechanisms are illustrated: (1) evaluating the cost of the error against the benefits of using the technology; (2) transferring responsibility for technology errors to humans (either those “behind the technology” or the users); (3) communicating with or about the technology; and (4) accepting the technology’s faults. The results suggest that users undergo complex cognitive and emotional processes when faced with a technological error. As forgiveness is one of the most critical aspects of every relationship, the conceptualization and preliminary study presented here may serve as a starting point for a new area of research and as a springboard for an essential scholarly discussion.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average