Towards a Model for Building Trust and Acceptance of Artificial Intelligence Aided Medical Assessment Systems
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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.
Original language | English |
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Title of host publication | Proceedings of the 49th EMAC 2020 Annual Conference, Budapest, May 26-29, 2020 |
Number of pages | 10 |
Place of Publication | Brüssel |
Publisher | European Marketing Academy |
Publication date | 27.05.2020 |
Article number | 64418 |
Publication status | Published - 27.05.2020 |
Event | 49th Annual of the European Marketing Academy - EMAC 2020 - Corvinus University of Budapest, Budapest , Hungary Duration: 26.05.2020 → 29.05.2020 Conference number: 49 http://emac-budapest2020.org/ |
- Management studies