Seema Nagar

TL;DR: A new open source Python toolkit for algorithmic fairness, AI Fairness 360 (AIF360), released under an Apache v2.0 license to help facilitate the transition of fairness research algorithms to use in an industrial setting and to provide a common framework for fairness researchers to share and evaluate algorithms.

TL;DR: A new open-source Python toolkit for algorithmic fairness, AI Fairness 360 (AIF360), released under an Apache v2.0 license, to help facilitate the transition of fairness research algorithms for use in an industrial setting and to provide a common framework for fairness researchers to share and evaluate algorithms.

TL;DR: This work proposes a methodology for auto-generation of test inputs, for the task of detecting individual discrimination, which combines two well-established techniques - symbolic execution and local explainability for effective test case generation.

TL;DR: Initial findings reported herein suggest that social media sites like Twitter constitute a promising source for extracting user context that can be exploited by novel social networking applications.

TL;DR: The authors proposed a novel mechanism for enriching the feature vector, with cognitive features extracted from eye-movement patterns of human readers, for sarcasm detection, with the cognitive features obtained from readers eye movement data.