Tag: Black Box Algorithms
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Chris Olah on What the Hell is Going on Inside Neural Networks
Author: Robert Wiblin, Keiran Harris, Chris Olah; Publisher: 80,000 Hours; Publication Year: 2021. The following podcast episode features Chris Olah, a researcher at Google focused on data interpretability, specifically as it relates to neural networks…
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fairmodels: a Flexible Tool for Bias Detection, Visualization, and Mitigation in Binary Classification Models
Author: Jakub Wisniewski, Przemyslaw Biecek; Publisher: The R Journal; Publication Year: 2022. The following article discusses how as more sophisticated machine learning methods become more ubiquitous, a culture of classifying between “explainable” and “unexplainable” models…
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Manipulating SHAP via Adversarial Data Perturbations (Student Abstract)
Author: Hubert Baniecki, Przemyslaw Biecek; Publisher: Proceedings of the AAAI Conference on Artificial Intelligence; Publication Year: 2022. The following article discusses how Shapley Additive Explanations (SHAP) values are a popular metric for identifying variable importance…
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What is “Data Ethics”, and Why is it Important
Author: Dennis Hirsch; Publisher: Centre for Information Policy Leadership; Publication Year: 2021. The following article discuses what exactly is data ethics. Dennis Hirsch, a lawyer from Ohio State, asks this question in a study conducted…
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The Alignment Problem: Machine Learning and Human Values
Author: Brian Christian; Publisher: W. W. Norton & Company; Publication Year: 2020. The following book focuses on word2vec, an algorithm from 2013 that allows for vector computation of words. That is, word2vec allows for computations…