59 citations · 122 across the 7 of their papers we have counts for
9 papers
Let Me Clarify: Interactive Modeling of Soft Attributes
Steffen Holter, Rita Sevastjanova, Michaela Benk +1
People commonly express preferences through soft attributes such as is interesting,'' which are difficult to operationalize for computational preference modeling. Latent representa…
Trust Hinders Bidirectional Human-AI Alignment
Michaela Benk, Kacper Sokol
Trust calibration remains the dominant framing of AI-assisted decision making: the goal is to close the gap between perceived and actual trustworthiness of AI systems so that users…
Ranking Companion: A Visual Analytics Approach to Item-Based Ranking with Hybrid Item Selection
Aman Kumar, Maximilian Tornow, Michaela Benk +2
Personalizing item ranking creation is a challenging task, especially when users lack knowledge of data attributes or the ability to express and formalize their attribute preferenc…
Same Performance, Hidden Bias: Evaluating Hypothesis- and Recommendation-Driven AI
Michaela Benk, Tim Miller
The HCI community commonly evaluates decision support systems based on whether they improve task performance or promote appropriate user reliance. In this work, we look beyond deci…
Twenty-Four Years of Empirical Research on Trust in AI: A Bibliometric Review of Trends, Overlooked Issues, and Future Directions
Michaela Benk, Sophie Kerstan, Florian v. Wangenheim +1
Trust is widely regarded as a critical component to building artificial intelligence (AI) systems that people will use and safely rely upon. As research in this area continues to e…
Certification Labels for Trustworthy AI: Insights From an Empirical Mixed-Method Study
Nicolas Scharowski, Michaela Benk, Swen J. Kühne +2
Auditing plays a pivotal role in the development of trustworthy AI. However, current research primarily focuses on creating auditable AI documentation, which is intended for regula…
"Is It My Turn?" Assessing Teamwork and Taskwork in Collaborative Immersive Analytics
Michaela Benk, Raphael Weibel, Stefan Feuerriegel +1
Immersive analytics has the potential to promote collaboration in machine learning (ML). This is desired due to the specific characteristics of ML modeling in practice, namely the…
Creative Uses of AI Systems and their Explanations: A Case Study from Insurance
Michaela Benk, Raphael Weibel, Andrea Ferrario
Recent works have recognized the need for human-centered perspectives when designing and evaluating human-AI interactions and explainable AI methods. Yet, current approaches fall s…
The Value of Measuring Trust in AI - A Socio-Technical System Perspective
Michaela Benk, Suzanne Tolmeijer, Florian von Wangenheim +1
Building trust in AI-based systems is deemed critical for their adoption and appropriate use. Recent research has thus attempted to evaluate how various attributes of these systems…