The Influence of Different Types of Trust, Perceived Objectivity, and Perceived Risk on the Preferred Involvement of AI for Subjective and Objective Tasks
ABSTRACT Artificial intelligence (AI) is increasingly involved in decision‐making. While many consumers currently use AI for minor tasks such as music recommendations or for improving writing, it can also be used for more consequential decisions such as medical diagnoses or financial recommendations. A declaration of AI content is not common, and consumers may not always be aware that AI is involved in the decision‐making. Therefore, it is important to understand their perception of AI for different tasks and how different kinds of trust influence the degree to which AI involvement is accepted. The psychometric paradigm was adapted to analyze participants’ acceptance, perceived objectivity, and perceived risks in the event of errors for a list of different tasks. To analyze the role of trust, measures for general confidence, general trust, and social trust, as well as AI‐trust and AI‐distrust were collected. The online survey was completed by 923 Swiss participants. The results show that participants’ preferred levels of AI involvement were influenced positively by the degree of subjectivity and negatively by the perceived risk associated with the task. Preferred AI involvement was highest for “Searching for information,” “Making a weather forecast,” and “Programming software” but lowest for “Delivering a court judgment,” “Selecting a candidate for a job,” and “Driving a car.” General confidence, general trust, and social trust indirectly influenced acceptance of AI through AI‐trust, but not AI‐distrust. The findings indicate that although specific AI‐trust has the largest influence on acceptance of AI, general types of trust are also important for evaluating AI in decision‐making.
Authors
- Michael Siegrist (ORCID: https://orcid.org/0000-0002-6139-7190)
- Fabienne Michel (ORCID: https://orcid.org/0000-0003-3105-6747)
Institutions
- ETH Zurich (CH)
- Institute for Biomedical Engineering (CH)
Publication Details
- Journal
- Risk Analysis
- Published
- 2026-09-15
- DOI
- https://doi.org/10.1111/risa.70349
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00