19 papers
Algorithmic Gender Prediction Is Illegitimate, But Gender Imputation Can Yield Valid Measurements
Evan Dong, Angelina Wang
Machine learning ethics researchers and critical HCI scholars have argued that algorithmically predicting gender is wrong. At the same time, other researchers rely on predicted gen…
Designing Social Robots for Inclusive Child Wellbeing Assessment: Insights from Communities Supporting Developmental Language Disorder and Forced Migration
Fethiye Irmak Dogan, Yue Lou, Alva Markelius +8
Assessing children's wellbeing and mental health can be particularly challenging for children experiencing communication barriers, such as children with Developmental Language Diso…
StARS: Socially Appropriate Robot Actions via a Recommender System-Driven Approach
Erencem Ozbey, Fethiye Irmak Dogan, Jin Huang +1
Social appropriateness in human-robot interaction (HRI) is not universal: different people can judge the same robot action differently in the same situation. To capture this inter-…
Toward Personalized Social Robots for Child Well-being: Data Requirement Principles from a Recommender-System Perspective
Jin Huang, Eric Nichols, Fethiye Irmak Dogan +1
Social robots are increasingly deployed in clinical settings to support the well-being of children, where effective support must be personalized to each child. Personalization, cho…
Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions
Saleh Afroogh, Syed Ishtiaque Ahmed, Petra Ahrweiler +46
This study provides a cross-disciplinary examination of Explainable Artificial Intelligence (XAI) approaches-focusing on deep neural networks (DNNs) and large language models (LLMs…
MM-Conv: A Multimodal Dataset and Benchmark for Context-Aware Grounding in 3D Dialogue
Anna Deichler, Jim O'Regan, Fethiye Irmak Dogan +4
Grounding language in the physical world requires AI systems to interpret references that emerge dynamically during conversation. While current vision-language models (VLMs) excel…