3 citations · 3 across the 2 of their papers we have counts for
3 papers
Diverse, but Divisive: LLMs Can Exaggerate Gender Differences in Opinion Related to Harms of Misinformation
Terrence Neumann, Sooyong Lee, Maria De-Arteaga +2
The pervasive spread of misinformation and disinformation poses a significant threat to society. Professional fact-checkers play a key role in addressing this threat, but the vast…
Homophily and Incentive Effects in Use of Algorithms
Riccardo Fogliato, Sina Fazelpour, Shantanu Gupta +2
As algorithmic tools increasingly aid experts in making consequential decisions, the need to understand the precise factors that mediate their influence has grown commensurately. I…
Fair Machine Learning Under Partial Compliance
Jessica Dai, Sina Fazelpour, Zachary C. Lipton
Typically, fair machine learning research focuses on a single decisionmaker and assumes that the underlying population is stationary. However, many of the critical domains motivati…