Responsible AI

You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual Settings ACL 2022 A Crash Course on Ethics for Natural Language Processing NAACL 2021 Algorithms for Fairness in Sequential Decision Making AISTATS 2021 Alibi Explain: Algorithms for Explaining Machine Learning Models JMLR 2021 Aligning AI With Shared Human Values ICLR 2021 All That’s ‘Human’ Is Not Gold: Evaluating Human Evaluation of Generated Text ACL 2021 Annotating and Modeling Fine-grained Factuality in Summarization NAACL 2021 An Overview of Fairness in Data – Illuminating the Bias in Data Pipeline EACL 2021 A Study of Automatic Metrics for the Evaluation of Natural Language Explanations EACL 2021 Auditing Robot Learning for Safety and Compliance during Deployment CoRL 2021 Beyond Fair Pay: Ethical Implications of NLP Crowdsourcing NAACL 2021 Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering ICCV 2021 Bias-tolerant Fair Classification ACML 2021 Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics ALT 2021 Can We Improve Model Robustness through Secondary Attribute Counterfactuals? EMNLP 2021 Case Study: Deontological Ethics in NLP NAACL 2021 Challenges in Detoxifying Language Models EMNLP 2021 Characterizing Fairness Over the Set of Good Models Under Selective Labels ICML 2021 Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation EMNLP 2021 dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python JMLR 2021 Dataset Inference: Ownership Resolution in Machine Learning ICLR 2021 Decision Making with Differential Privacy under a Fairness Lens IJCAI 2021 Detect and Perturb: Neutral Rewriting of Biased and Sensitive Text via Gradient-based Decoding EMNLP 2021 Differentially Private Learning Needs Better Features (or Much More Data) ICLR 2021 Does Explainable Artificial Intelligence Improve Human Decision-Making? AAAI 2021