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Introduction
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Classroom Contents
Social Implications of Bias in Machine Learning
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- 1 Introduction
- 2 Social Bias
- 3 Prejudice
- 4 Statistical Bias
- 5 The Human Condition
- 6 What is Machine Learning
- 7 Overview
- 8 Garbage in Garbage out
- 9 Open Data Institute Canvas
- 10 Summary
- 11 Orchestras
- 12 Protected Attributes
- 13 Reducing Data
- 14 Adding Missing Data
- 15 Raising Machines
- 16 Google Translate
- 17 algorithmic justice league
- 18 the stem
- 19 diversity
- 20 The Forgotten
- 21 People Plus AI Research
- 22 Google
- 23 The Black Box
- 24 The Right to an Explanation
- 25 Open the Black Box
- 26 Simplifying Algorithms
- 27 Fixed Bugs
- 28 Lime
- 29 Tree Frog
- 30 What If
- 31 Feedback loops
- 32 Facebook
- 33 Compass
- 34 Silver Lining
- 35 Governance Usage
- 36 Amazon
- 37 Whos responsible
- 38 Pharmaceutical example
- 39 OpenAI example
- 40 We can quickly patch
- 41 We can demand better products
- 42 We can create updates very quickly
- 43 We realized that data is biased
- 44 We have the power
- 45 We want to go
- 46 Lets learn
- 47 We have an immense power
- 48 Change and shape society
