Propensity matters. An empirical analysis on the importance of trust for the intention to use artificial intelligence

Proceedings of the 15th International Conference on Human Interaction & Emerging Technologies (IHIET 2025) August 25-27, 2025 University of Vienna, Austria

Themenheft

DOI der Originalpublikation

https://doi.org/10.54941/ahfe1006710

URI

https://irf.fhnw.ch/handle/11654/53306
https://doi.org/10.26041/fhnw-13997

Link

Reihe / Serie

AHFE International

Reihennummer

197

Jahrgang / Band

Ausgabe / Nummer

Seiten / Dauer

171-181

Patentnummer

Verlag / Herausgebende Institution

AHFE Open Access

Verlagsort / Veranstaltungsort

New York

Auflage

Version

Programmiersprache

Abtretungsempfänger:in

Praxispartner:in/Auftraggeber:in

Zusammenfassung

There is a growing need for scientific knowledge about the extent to which the results of artificial intelligence (AI) and the effects of its use can be considered trustworthy. Accordingly, user experience can lead to trust in AI being too low or too high, which could result in its misuse. Especially as trust is considered subjective and could be seen as a heuristic, which in turn would speak in favor of the importance of trust in AI, as the underlying algorithm is not transparent to the user in so-called black-box models. In this context, the call to enhance the transparency of such models to increase trust seems contradictory. There is no common theory, but Lee and See's (2004) model of trust in automation is often used as a basis for research, since automation can be seen as the foundation of AI. However, it remains unclear whether this model can be adapted to AI. Therefore, this study investigates which factors influence trust in AI in the context of ChatGPT and how this affects the intention to use. On this basis, a conceptual path model was derived and tested using path analysis. Data were collected from 105 students using validated questionnaires. The empirical path model shows the expected positive influences, with one exception. In addition, the results emphasize that the role of the propensity to trust is central. Furthermore, the significant influence of trust on intention to use is weaker than supposed. While the results largely align with existing assumptions, they simultaneously introduce new insights.

Schlagwörter

Fachgebiet (DDC)

330 - Wirtschaft

Projekt

Veranstaltung

Human Interaction and Emerging Technologies (IHIET 2025)

Startdatum der Ausstellung

Enddatum der Ausstellung

Startdatum der Konferenz

25.08.2025

Enddatum der Konferenz

27.08.2025

Datum der letzten Prüfung

ISBN

978-1-964867-73-1

ISSN

Sprache

Englisch

Während FHNW Zugehörigkeit erstellt

Ja

Zukunftsfelder FHNW

Publikationsstatus

Veröffentlicht

Begutachtung

Peer-Review der ganzen Publikation

Open Access-Status

Gold

Lizenz

Zitation

Karg, J., Ritz, F., & Asprion, P. (2025). Propensity matters. An empirical analysis on the importance of trust for the intention to use artificial intelligence. In T. Z. Ahram & R. Motschnig (Eds.), Proceedings of the 15th International Conference on Human Interaction & Emerging Technologies (IHIET 2025) August 25-27, 2025 University of Vienna, Austria (pp. 171–181). AHFE Open Access. https://doi.org/10.54941/ahfe1006710

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