426 citations · 627 across the 19 of their papers we have counts for
5 papers · 1 filter
Designing Visual Explanations and Learner Controls to Engage Adolescents in AI-Supported Exercise Selection
Jeroen Ooge, Arno Vanneste, Maxwell Szymanski +1
E-learning platforms that personalise content selection with AI are often criticised for lacking transparency and controllability. Researchers have therefore proposed solutions suc…
Representation Debiasing of Generated Data Involving Domain Experts
Aditya Bhattacharya, Simone Stumpf, Katrien Verbert
Biases in Artificial Intelligence (AI) or Machine Learning (ML) systems due to skewed datasets problematise the application of prediction models in practice. Representation bias is…
Petal-X: Human-Centered Visual Explanations to Improve Cardiovascular Risk Communication
Diego Rojo, Houda Lamqaddam, Lucija Gosak +1
Cardiovascular diseases (CVDs), the leading cause of death worldwide, can be prevented in most cases through behavioral interventions. Therefore, effective communication of CVD ris…
An Explanatory Model Steering System for Collaboration between Domain Experts and AI
Aditya Bhattacharya, Simone Stumpf, Katrien Verbert
With the increasing adoption of Artificial Intelligence (AI) systems in high-stake domains, such as healthcare, effective collaboration between domain experts and AI is imperative.…
EXMOS: Explanatory Model Steering Through Multifaceted Explanations and Data Configurations
Aditya Bhattacharya, Simone Stumpf, Lucija Gosak +2
Explanations in interactive machine-learning systems facilitate debugging and improving prediction models. However, the effectiveness of various global model-centric and data-centr…