Building an Ethical Data Science Practice

Building an Ethical Data Science Practice

Open Data Science via YouTube Direct link

segregation between population

14 of 16

14 of 16

segregation between population

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Building an Ethical Data Science Practice

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  1. 1 Introduction
  2. 2 What is Ethical Data Science
  3. 3 Examples of AI gone wrong
  4. 4 Data complexity
  5. 5 Sentiment analysis
  6. 6 The virtuous cycle
  7. 7 Diversity in data science
  8. 8 Open invitation
  9. 9 Connect with Cal
  10. 10 How can data science have an active role in combating inequity
  11. 11 How are other organizations responding to ethical challenges
  12. 12 How can we prevent models from becoming biased
  13. 13 How would you systematically test for biases
  14. 14 segregation between population
  15. 15 trading complexity for accuracy
  16. 16 outro

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