5 papers
Between Suppression and Collapse: Evaluating Narrative Unlearning with LENS
Viktoriia Makovska, George Fletcher
Large language models (LLMs) can reproduce disinformation-aligned narrative frames as plausible explanations, raising the question of whether existing machine-unlearning algorithms…
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…
Seasoning Data Modeling Education with GARLIC: A Participatory Co-Design Framework
Viktoriia Makovska, Ihor Michurin, Mariia Tokhtamysh +2
Entity-Relationship (ER) modeling is commonly taught as a primarily technical activity, despite its central role in shaping how data systems represent people, processes, and instit…
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…
CREDAL: Close Reading of Data Models
George Fletcher, Olha Nahurna, Matvii Prytula +1
Data models are necessary for the birth of data and of any data-driven system. Indeed, every algorithm, every machine learning model, every statistical model, and every database ha…