Search Results for author:
Found 4 papers, 3 papers with code
Will Large-scale Generative Models Corrupt Future Datasets?
These trends lead us to a research question: "\textbf{will such generated images impact the quality of future datasets and the performance of computer vision models positively or negatively?}"
Trustworthy Human Computation: A Survey
Human computation is an approach to solving problems that prove difficult using AI only, and involves the cooperation of many humans.
Characterizing the risk of fairwashing
In particular, we show that fairwashed explanation models can generalize beyond the suing group (i. e., data points that are being explained), meaning that a fairwashed explainer can be used to rationalize subsequent unfair decisions of a black-box model.
Fairwashing: the risk of rationalization
Black-box explanation is the problem of explaining how a machine learning model -- whose internal logic is hidden to the auditor and generally complex -- produces its outcomes.
