4 papers
First-See-Then-Design: A Multi-Stakeholder View for Optimal Performance-Fairness Trade-Offs
Kavya Gupta, Nektarios Kalampalikis, Christoph Heitz +1
Fairness in algorithmic decision-making is often defined in the predictive space, where predictive performance - used as a proxy for decision-maker (DM) utility - is traded off aga…
Towards Reasonable Concept Bottleneck Models
Nektarios Kalampalikis, Kavya Gupta, Georgi Vitanov +1
We propose a novel, flexible, and efficient framework for designing Concept Bottleneck Models (CBMs) that enables practitioners to explicitly encode and extend their prior knowledg…
A Causal Framework to Measure and Mitigate Non-binary Treatment Discrimination
Ayan Majumdar, Deborah D. Kanubala, Kavya Gupta +1
Fairness studies of algorithmic decision-making systems often simplify complex decision processes, such as bail or loan approvals, into binary classification tasks. However, these…
Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches
Israel Abebe Azime, Deborah D. Kanubala, Tejumade Afonja +4
Large Language Models (LLMs) are increasingly employed in high-stakes decision-making tasks, such as loan approvals. While their applications expand across domains, LLMs struggle t…