The Relationship Between Performance and Trust in AI in E-Finance.
artificial intelligence
finance simulation
hidden Markov model
robo-advisor
trust
Journal
Frontiers in artificial intelligence
ISSN: 2624-8212
Titre abrégé: Front Artif Intell
Pays: Switzerland
ID NLM: 101770551
Informations de publication
Date de publication:
2022
2022
Historique:
received:
07
03
2022
accepted:
30
05
2022
entrez:
8
7
2022
pubmed:
9
7
2022
medline:
9
7
2022
Statut:
epublish
Résumé
Artificial intelligence (AI) is fundamentally changing how people work in nearly every field, including online finance. However, our ability to interact with AI is moderated by factors such as performance, complexity, and trust. The work presented in this study analyzes the effect of performance on trust in a robo-advisor (AI which assists in managing investments) through an empirical investment simulation. Results show that for applications where humans and AI have comparable capabilities, the difference in performance (between the human and AI) is a moderate indicator of change in trust; however, human or AI performance individually were weak indicators. Additionally, results indicate that biases typically seen in human-human interactions may also occur in human-AI interactions when AI transparency is low.
Identifiants
pubmed: 35800065
doi: 10.3389/frai.2022.891529
pmc: PMC9253559
doi:
Types de publication
Journal Article
Langues
eng
Pagination
891529Informations de copyright
Copyright © 2022 Maier, Menold and McComb.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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