Towards a Model for Building Trust and Acceptance of Artificial Intelligence Aided Medical Assessment Systems

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

This study aims to identify determinants for the emergence of trust in AI-based medical assessment systems consisting of chatbots and telemedicine. Existing studies have been failing to create a holistic understanding due to focusing on single trust antecedents. Our study closes this research gap by conducting semi-structured interviews and standardized questionnaires to identify relevant variables and their relationship to each other. Participants (n = 40) take part in a laboratory experiment interacting with a chatbot (vs. chatbot + human agent) for initial medical assessment. The first results indicate the importance of the chatbot’s purpose and the transparency of underlying data base. Furthermore, communication patterns conveying uncertainty reduction are found to be more important than chatbot’s social skills. The additional human expert complements the chatbot due to the possibility of more specific and detailed questioning and patients’ wish of having a responsible person.
OriginalspracheEnglisch
TitelProceedings of the 49th EMAC 2020 Annual Conference, Budapest, May 26-29, 2020
Anzahl der Seiten10
ErscheinungsortBrüssel
VerlagEuropean Marketing Academy
Datum27.05.2020
Aufsatznummer64418
PublikationsstatusErschienen - 27.05.2020
Veranstaltung49th Annual of the European Marketing Academy - EMAC 2020 - Corvinus University of Budapest, Budapest , Ungarn
Dauer: 26.05.202029.05.2020
Konferenznummer: 49
http://emac-budapest2020.org/

Dokumente

Links