KIVerfahrensStudy

KIVerfahrensStudy is a research initiative that examines human interactions with artificial intelligence systems. Conducted across multiple institutions, the project seeks to understand how users experience AI in real-world tasks, how explanations and interfaces affect perception, trust, and decision-making, and how design choices influence adoption and outcomes.

Originating in the German-speaking research community, the study brings together computer science, psychology, and human-computer interaction to address questions of usability, safety, and ethics in AI-enabled applications.

Methods: The study uses a mixed-methods approach, combining large-scale surveys, controlled experiments, and qualitative interviews. Data are anonymized and stored in accordance with ethical guidelines. The design includes cross-sector samples—consumer apps, enterprise tools, and public services—to capture diverse user experiences. Longitudinal elements track changes over time.

Scope: Core topics include transparency and explainability, trust and reliance, user control, task performance, privacy, and bias mitigation. The study also documents user preferences for feedback mechanisms and safety features.

Findings: Early results indicate that transparent explanations improve perceived usefulness and trust in straightforward tasks, whereas complex tasks may require adaptive explanations to avoid cognitive overload. UI patterns, customization options, and user education significantly affect satisfaction and continued use. Privacy concerns and data-sharing expectations vary by context.

Impact: KIVerfahrensStudy contributes to best practices for evaluating AI systems from a user-centric perspective and informs guidelines for explainable AI, risk assessment, and governance. Findings aim to support designers, policymakers, and researchers in creating more usable and trustworthy AI applications.