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Fairness in NLP Teaching Materials

These materials are designed to teach students about the topic of fairness in machine learning. The materials are described in more detail in the SIGCSE paper: Towards Machine Learning Fairness Education in a Natural Language Processing Course, with a discussion on what went well and what can be improved in the future.

Lecture: Bias in NLP. pptx file

Activity 1 Exploring Vectors Representations for Words and Texts and their Similarities. Details are in the ipynb file.

Activity 2 Measuring Bias in BERT Contextualized Embeddings. Details are in the ipynb file.

Activity 3 Measuring Disability Bias in BERT. Details are in the ipynb file

Final Project: Details are in the ipynb file.

Related work: Teaching Accessibility in AI Courses

Team

Samantha Dobesh

Tyler Miller

Pax Newman

Dr. Yudong Liu

Dr. Yasmine Elglaly

Acknowledgement

Parts of this work are supported by the SIGCSE Special Projects Grant award 56004A.

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