activity
20212024
most citedInterpretability is in the eye of the beholder: Human versus artificial classification of image segments generated by humans versus XAI

12 citations · 32 across the 7 of their papers we have counts for

collaborators

7 papers

cs.HC2024★ 1 cited

Adapt/Exchange decisions or generic choices: Does framing influence how people integrate qualitatively different risks?

Romy Müller, Alexander Blunk

In complex systems, decision makers often have to consider qualitatively different risks when choosing between options. Do their strategies of integrating these risks depend on the…

cs.HC2024★ 1 cited

Adapt/Exchange decisions depend on structural and surface features: Effects of solution costs and presentation format

Romy Müller

Problem solvers often need to choose between adapting a current solution and exchanging it for a new one. How do such decisions depend on structural and surface features of the tas…

cs.HC2023★ 1 cited

Information acquisition in Adapt/Exchange decisions: When do people check alternative solution principles?

Romy Müller, Maria Pohl

Many problems can be solved in two ways: either by adapting an existing solution, or by exchanging it for a new one. To investigate under what conditions people consider new soluti…

cs.HC2023★ 8 cited

The benefits and costs of explainable artificial intelligence in visual quality control: Evidence from fault detection performance and eye movements

Romy Müller, David F. Reindel, Yannick D. Stadtfeld

Visual inspection tasks often require humans to cooperate with AI-based image classifiers. To enhance this cooperation, explainable artificial intelligence (XAI) can highlight thos…

cs.HC2023★ 12 cited

Interpretability is in the eye of the beholder: Human versus artificial classification of image segments generated by humans versus XAI

Romy Müller, Marius Thoß, Julian Ullrich +2

The evaluation of explainable artificial intelligence is challenging, because automated and human-centred metrics of explanation quality may diverge. To clarify their relationship,…

cs.CV2023★ 8 cited

Do humans and Convolutional Neural Networks attend to similar areas during scene classification: Effects of task and image type

Romy Müller, Marcel Dürschmidt, Julian Ullrich +3

Deep Learning models like Convolutional Neural Networks (CNN) are powerful image classifiers, but what factors determine whether they attend to similar image areas as humans do? Wh…

cs.HC2021★ 1 cited

Data in context: How digital transformation can support human reasoning in cyber-physical production systems

Romy Müller, Franziska Kessler, David W. Humphrey +1

In traditional production plants, current technologies do not provide sufficient context to support information integration and interpretation. Digital transformation technologies…