Abstract
"Artifcial intelligence (AI) refers to technologies which support the execution of tasks normally requiring human intelligence (e.g., visual perception, speech recognition, or decision-making). Examples for AI systems are chatbots,
robots, or autonomous vehicles, all of which have become an important phenomenon in the economy and society. Determining which AI system to trust and which not to trust is critical, because such systems carry out tasks autonomously and infuence human decision making. This growing
importance of trust in AI systems has paralleled another trend: the increasing understanding that user personality is related to trust, thereby afecting the acceptance and adoption of AI systems. We developed a framework of user personality and trust in AI systems which distinguishes
universal personality traits (e.g., Big Five), specifc personality traits (e.g., propensity to trust), general behavioral tendencies (e.g., trust in a specifc AI system), and specifc behaviors (e.g., adherence to the recommendation of an AI system in a decision-making context).
Based on this framework, we reviewed the scientifc literature. We analyzed N=58 empirical studies published in various scientifc disciplines and developed a “big picture” view, revealing signifcant relationships between personality traits and trust in AI systems. However,
our review also shows several unexplored research areas. In particular, it was found that prescriptive knowledge about how to design trustworthy AI systems as a function of user personality lags far behind descriptive knowledge about the use and trust efects of AI systems.
Based on these fndings, we discuss possible directions for future research, including adaptive systems as focus of future design science research.
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 2021-2051 |
| Seitenumfang | 31 |
| Fachzeitschrift | Electronic Markets |
| Volume | 32 |
| Ausgabenummer | 4 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - Dez. 2022 |
Wissenschaftszweige
- 303026 Public Health
- 305909 Stressforschung
- 102 Informatik
- 102006 Computer Supported Cooperative Work (CSCW)
- 102015 Informationssysteme
- 102016 IT-Sicherheit
- 502007 E-Commerce
- 502014 Innovationsforschung
- 502030 Projektmanagement
- 509026 Digitalisierungsforschung
- 501016 Pädagogische Psychologie
- 602036 Neurolinguistik
- 501030 Kognitionswissenschaft
- 502032 Qualitätsmanagement
- 502043 Unternehmensberatung
- 502044 Unternehmensführung
- 502050 Wirtschaftsinformatik
- 502058 Digitale Transformation
- 503008 E-Learning
- 509004 Evaluationsforschung
- 301407 Neurophysiologie
- 301401 Hirnforschung
JKU-Schwerpunkte
- Digital Transformation
Dieses zitieren
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver