21 citations · 25 across the 5 of their papers we have counts for
4 papers
Bias-Aware Mislabeling Detection via Decoupled Confident Learning
Yunyi Li, Maria De-Arteaga, Maytal Saar-Tsechansky
Reliable data is a cornerstone of modern organizational systems. A notable data integrity challenge stems from label bias, which refers to systematic errors in a label, a covariate…
Should you use LLMs to simulate opinions? Quality checks for early-stage deliberation
Terrence Neumann, Maria De-Arteaga, Sina Fazelpour
The emergent capabilities of large language models (LLMs) have prompted interest in using them as surrogates for human subjects in opinion surveys. However, prior evaluations of LL…
Using Machine Bias To Measure Human Bias
Wanxue Dong, Maria De-Arteaga, Maytal Saar-Tsechansky
Biased human decisions have consequential impacts across various domains, yielding unfair treatment of individuals and resulting in suboptimal outcomes for organizations and societ…
Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential Harms
Terrence Neumann, Maria De-Arteaga, Sina Fazelpour
Faced with the scale and surge of misinformation on social media, many platforms and fact-checking organizations have turned to algorithms for automating key parts of misinformatio…