Data Model for Computer Vision Explainability, Fairness, and Robustness

Maxplain – Value-based Evaluation of Explainable AI Techniques

Clearing the Air: An Exploration of Pulmonologists' Needs and Intents in XAI Solutions for Respiratory Medicine

Exploring Hybrid Intelligence for Topic Interpretation in Colorectal Cancer Research: A Comparative Study of GPT-3.5 and Human Expertise

A System for Model Diagnosis centered around Human Computation

Natural Language Processing and Reinforcement Learning to Generate Morally Aligned Text: Comparing a moral agent to an optimally playing agent

Value-sensitive Evaluation of Hybrid Human-AI Chatbots in Customer Services

A Human-In-the-Loop Framework to Assess Multimodal Machine Learning Models

Evaluating the Effect of Data Drift on Model Performance

Value-Sensitive Rejection of Machine Learning Predictions for Hate Speech Detection

LoveBERT: Leveraging Language Models to Improve Matchmaking at Breeze

Towards a Safer and More Reliable Selective Classifier: With Human Knowledge and Value Incorporated

CHIME: Causal Human-In-the-Loop Model Explanations

Debugging Machine Learning on Time-series Data

Declarative Image Generation

Characterizing the knowns and unknowns of text simplification models

Toward Fine-grained Causality Reasoning and Question Answering

Closer or even farther from fairness: An assessment of whether fairness toolkits constrain practitioners with regards to algorithmic harms

Who Cares About Fairness: How Background Influences the Way Practitioners Consider Machine Learning Harms

Effectiveness of Automatic and Semi-Automatic Methods to Collect Common Sense Knowledge