The (Im)perfect Automation Schema: Who Is Trusted More, Automated or Human Decision Support?
decision making
expert systems
expert-novice differences
human-automation interaction
trust in automation
Journal
Human factors
ISSN: 1547-8181
Titre abrégé: Hum Factors
Pays: United States
ID NLM: 0374660
Informations de publication
Date de publication:
26 Aug 2023
26 Aug 2023
Historique:
medline:
27
8
2023
pubmed:
27
8
2023
entrez:
26
8
2023
Statut:
aheadofprint
Résumé
This study's purpose was to better understand the dynamics of trust attitude and behavior in human-agent interaction. Whereas past research provided evidence for a perfect automation schema, more recent research has provided contradictory evidence. To disentangle these conflicting findings, we conducted an online experiment using a simulated medical X-ray task. We manipulated the framing of support agents (i.e., artificial intelligence (AI) versus expert versus novice) between-subjects and failure experience (i.e., perfect support, imperfect support, back-to-perfect support) within subjects. Trust attitude and behavior as well as perceived reliability served as dependent variables. Trust attitude and perceived reliability were higher for the human expert than for the AI than for the human novice. Moreover, the results showed the typical pattern of trust formation, dissolution, and restoration for trust attitude and behavior as well as perceived reliability. Forgiveness after failure experience did not differ between agents. The results strongly imply the existence of an imperfect automation schema. This illustrates the need to consider agent expertise for human-agent interaction. When replacing human experts with AI as support agents, the challenge of lower trust attitude towards the novel agent might arise.
Sections du résumé
OBJECTIVE
OBJECTIVE
This study's purpose was to better understand the dynamics of trust attitude and behavior in human-agent interaction.
BACKGROUND
BACKGROUND
Whereas past research provided evidence for a perfect automation schema, more recent research has provided contradictory evidence.
METHOD
METHODS
To disentangle these conflicting findings, we conducted an online experiment using a simulated medical X-ray task. We manipulated the framing of support agents (i.e., artificial intelligence (AI) versus expert versus novice) between-subjects and failure experience (i.e., perfect support, imperfect support, back-to-perfect support) within subjects. Trust attitude and behavior as well as perceived reliability served as dependent variables.
RESULTS
RESULTS
Trust attitude and perceived reliability were higher for the human expert than for the AI than for the human novice. Moreover, the results showed the typical pattern of trust formation, dissolution, and restoration for trust attitude and behavior as well as perceived reliability. Forgiveness after failure experience did not differ between agents.
CONCLUSION
CONCLUSIONS
The results strongly imply the existence of an imperfect automation schema. This illustrates the need to consider agent expertise for human-agent interaction.
APPLICATION
CONCLUSIONS
When replacing human experts with AI as support agents, the challenge of lower trust attitude towards the novel agent might arise.
Identifiants
pubmed: 37632728
doi: 10.1177/00187208231197347
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM