2 citations · 2 across the 4 of their papers we have counts for
5 papers
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…
We Are AI: Taking Control of Technology
Julia Stoyanovich, Armanda Lewis, Eric Corbett +3
Responsible AI (RAI) is the science and practice of ensuring the design, development, use, and oversight of AI are socially sustainable--benefiting diverse stakeholders while contr…
Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data
Shlomi Hod, Lucas Rosenblatt, Julia Stoyanovich
Differentially private (DP) machine learning often relies on the availability of public data for tasks like privacy-utility trade-off estimation, hyperparameter tuning, and pretrai…
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…