13 papers
FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment
Sophie Chiang, Tom Brennan, Fethiye Irmak Dogan +2
In recent years, the integration of multimodal machine learning in wellbeing assessment has offered transformative potential for monitoring mental health. However, with the rapid a…
Investigating Associational Biases in Inter-Model Communication of Large Generative Models
Fethiye Irmak Dogan, Yuval Weiss, Kajal Patel +2
Social bias in generative AI can manifest not only as performance disparities but also as associational bias, whereby models learn and reproduce stereotypical associations between…
Some Optimizers are More Equal: Understanding the Role of Optimizers in Group Fairness
Mojtaba Kolahdouzi, Hatice Gunes, Ali Etemad
We study whether and how the choice of optimization algorithm can impact group fairness in deep neural networks. Through stochastic differential equation analysis of optimization d…
Who Owns The Robot?: Four Ethical and Socio-technical Questions about Wellbeing Robots in the Real World through Community Engagement
Minja Axelsson, Jiaee Cheong, Rune Nyrup +1
Recent studies indicate that robotic coaches can play a crucial role in promoting wellbeing. However, the real-world deployment of wellbeing robots raises numerous ethical and soci…
FAIRWELL: Fair Multimodal Self-Supervised Learning for Wellbeing Prediction
Jiaee Cheong, Abtin Mogharabin, Paul Liang +2
Early efforts on leveraging self-supervised learning (SSL) to improve machine learning (ML) fairness has proven promising. However, such an approach has yet to be explored within a…
Automatic Depression Assessment using Machine Learning: A Comprehensive Survey
Siyang Song, Yupeng Huo, Shiqing Tang +4
Depression is a common mental illness across current human society. Traditional depression assessment relying on inventories and interviews with psychologists frequently suffer fro…