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Exploring Gender Bias in Word Embeddings

Shlomi Hod

Audience level:
Novice

Brief Summary

Through hands-on interaction with word-embedding, a widespread building block of many machine learning models working with human languages, we will explore the issues of bias and fairness in machine learning.

Outline

  1. Introduction and setup

  2. Intro to Natural Language Processing (NLP)

  3. How to represent a language in computing?

  4. Intro to word embeddings

  5. Gender bias in word embeddings

  6. Bias mitigation

  7. Critical review

  8. Hands-on exercises

  9. Wrap-up: Takeaways and resources