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  • Dealing with Bias and Fairness in Building Data Science/ML/AI Systems
  • Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned
  • A Visual Tour of Bias Mitigation Techniques for Word Representations
  • Fairness in Machine Learning
  • The Trouble with Bias
  • Socially Responsible NLP
  • Tutorial: Bias and Fairness in Natural Language Processing
  • How to test the fairness of ML models? The 80% rule to measure the disparate impact
  • Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints
  • Mitigating Gender Bias Amplification in Distribution by Posterior Regularization
  • Gendered Ambiguous Pronoun (GAP) Shared Task at the Gender Bias in NLP Workshop 2019 - jussa, Marta R. and Hardmeier, Christian and Radford, Will, 2019
  • Proceedings of the First Workshop on Gender Bias in Natural Language Processing - juss{\`a}, Marta R. and Hardmeier, Christian and Radford, Will and Webster, Kellie, 2019
  • Proceedings of the Second Workshop on Gender Bias in Natural Language Proceedings - juss{\`a}, Marta R. and Hardmeier, Christian and Radford, Will and Webster, Kellie, 2020
  • Team Kermit-the-frog at SemEval-2019 Task 4: Bias Detection Through Sentiment Analysis and Simple Linguistic Features
  • Fairness and machine learning
  • Ethics in NLP
  • Team Kermit-the-frog at SemEval-2019 Task 4: Bias Detection Through Sentiment Analysis and Simple Linguistic Features
  • Socially Responsible NLP
  • Gendered Ambiguous Pronoun (GAP) Shared Task at the Gender Bias in NLP Workshop 2019 - jussa, Marta R. and Hardmeier, Christian and Radford, Will, 2019
  • Proceedings of the First Workshop on Gender Bias in Natural Language Processing - juss{\`a}, Marta R. and Hardmeier, Christian and Radford, Will and Webster, Kellie, 2019
  • Proceedings of the Second Workshop on Gender Bias in Natural Language Proceedings - juss{\`a}, Marta R. and Hardmeier, Christian and Radford, Will and Webster, Kellie, 2020