10 papers
Be Fair! Can Machine Learning Engineering Agents Adhere to Fairness Constraints?
Anna Richter, Julia Stoyanovich, Sebastian Schelter
Machine learning engineering (MLE) agents promise to automate end-to-end ML pipeline development from raw data and natural language instructions, potentially making ML accessible t…
"Would You Want an AI Tutor?" Understanding Stakeholder Perceptions of LLM-based Systems in the Classroom
Caterina Fuligni, Daniel Dominguez Figaredo, Armanda Lewis +1
Large Language Models (LLMs) have gained traction in educational settings, often framed as virtual tutors or teaching assistants. Following early skepticism and bans, many schools…
SafeTutors: Benchmarking Pedagogical Safety in AI Tutoring Systems
Rima Hazra, Bikram Ghuku, Ilona Marchenko +5
Large language models are rapidly being deployed as AI tutors, yet current evaluation paradigms assess problem-solving accuracy and generic safety in isolation, failing to capture…
Memory Undone: Between Knowing and Not Knowing in Data Systems
Viktoriia Makovska, George Fletcher, Julia Stoyanovich +1
Machine learning and data systems increasingly function as infrastructures of memory: they ingest, store, and operationalize traces of personal, political, and cultural life. Yet c…
Explanation Multiplicity in SHAP: Characterization and Assessment
Hyunseung Hwang, Seungeun Lee, Lucas Rosenblatt +2
Post-hoc explanations are widely used to justify, contest, and review automated decisions in high-stakes domains such as lending, employment, and healthcare. Among these methods, S…
ONION: A Multi-Layered Framework for Participatory ER Design
Viktoriia Makovska, George Fletcher, Julia Stoyanovich
We present ONION, a multi-layered framework for participatory Entity-Relationship (ER) modeling that integrates insights from design justice, participatory AI, and conceptual model…