Covers: theory of Bias
Estimated time needed to finish: 30 minutes
Questions this item addresses:
  • What are type of biases and algorithmic bias?
Author(s) / creator(s) / reference(s)
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Algorithmic bias and fairness in Natural Language Processing

Collaborators
Total time needed: ~3 hours
Objectives
Introduction to bias and fairness in Natural language processing
Potential Use Cases
It is very important to learn and understand harms in machine learning model to develop responsible and fair models.
Who is this for ?
INTERMEDIATENLP Data scientist from all audience levels
Click on each of the following annotated items to see details.
ARTICLE 1. AI Ethics Primer
  • What is AI ethics ?
30 minutes
ARTICLE 2. Bias in Machine learning models
  • What is bias and sources of bias in ML models?
10 minutes
ARTICLE 3. Fairness definitions
  • What is fairness and various fairness definitions?
30 minutes
OTHER 4. Type of biases and evaluating fairness in Natural Language Processing (NLP)
  • What is bias and fairness in Natural language processing?
  • What are the type of harms in NLP model?
  • How bias is generated in NLP?
30 minutes
ARTICLE 5. Algorithmic Bias in Natural language processing models
  • What are type of biases and algorithmic bias?
30 minutes

Concepts Covered

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