Trust by Design: How Glass Box AI Shapes User Acceptance through Explainability

dc.contributor.authorDa Silvia, Danilo Riberio
dc.contributor.mentorKarg, Jona
dc.contributor.mentorMisyura, Ilya
dc.contributor.partnerHochschule für Wirtschaft FHNW
dc.date.accessioned2025-12-15T13:38:51Z
dc.date.issued2025
dc.description.abstractAI is increasingly used in high-stakes domains such as healthcare, yet decision processes are often opaque. This study asks whether explainability improves user trust and acceptance. Building on Karg’s Path Model of Trust in AI, it focuses on process-level explainability as a core design element.
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/54824
dc.language.isoen
dc.publisherHochschule für Wirtschaft FHNW
dc.spatialBasel
dc.subject.ddc330 - Wirtschaft
dc.titleTrust by Design: How Glass Box AI Shapes User Acceptance through Explainability
dc.type11 - Studentische Arbeit
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.StudentsWorkTypeBachelor
fhnw.affiliation.hochschuleHochschule für Wirtschaft FHNWde_CH
fhnw.affiliation.institutBachelor of Sciencede_CH
relation.isMentorOfPublication38efec10-d5b0-4462-ac9d-31ab8d3b4910
relation.isMentorOfPublicationbedd2787-e3c5-48e9-a8a8-3e26e125f76b
relation.isMentorOfPublication.latestForDiscovery38efec10-d5b0-4462-ac9d-31ab8d3b4910
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