From 9d0bf96f04a04dafa9cad7a48270befec4f2da7b Mon Sep 17 00:00:00 2001 From: softchris Date: Wed, 16 Jun 2021 21:32:02 +0100 Subject: [PATCH] fix --- 1-Introduction/3-fairness/README.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/1-Introduction/3-fairness/README.md b/1-Introduction/3-fairness/README.md index 0984036a..8aa48ccd 100644 --- a/1-Introduction/3-fairness/README.md +++ b/1-Introduction/3-fairness/README.md @@ -13,7 +13,7 @@ Imagine what can happen when the data you are using to build these models lacks In this lesson, you will: -- Raise your awareness of importance of fairness in machine learning. +- Raise your awareness of the importance of fairness in machine learning. - Learn about fairness-related harms. - Learn about unfairness assessment and mitigation. @@ -40,9 +40,9 @@ What do you mean by unfairness? "Unfairness" encompasses negative impacts, or "h The main fairness-related harms can be classified as: -- **Allocation**, if a gender or ethnicity for example is favoured over another. -- **Quality of service**. If you train the data one type of data and reality is much more complex, it leads to a poor performing service. -- **Stereotyping**, that a certain gender is associated with a certain profession for example. +- **Allocation**, if a gender or ethnicity for example is favored over another. +- **Quality of service**. If you train the data for one specific scenario but reality is much more complex, it leads to a poor performing service. +- **Stereotyping**. Associating a given group with pre-assigned attributes. - **Denigration**. To unfairly criticize and label something or someone. - **Over- or under- representation**. The idea is that a certain group is not seen in a certain profession, and any service or function that keeps promoting that is contributing to harm. @@ -113,11 +113,11 @@ Let’s use the loan selection example to isolate the case to figure out each fa ## Assessment methods -1. **Identify harms (and benefits)**. The first step is to identify the harms and benefits. Think about how this affects both potential customers of a business but a business itself for example. +1. **Identify harms (and benefits)**. The first step is to identify harms and benefits. Think about how actions and decisions can affect both potential customers and a business itself. -1. **Identify the affected groups**. Once you understand what kind of harms or benefits that can occur, identify the groups that may be affected. Are these groups defined by gender, ethnicity, social group? +1. **Identify the affected groups**. Once you understand what kind of harms or benefits that can occur, identify the groups that may be affected. Are these groups defined by gender, ethnicity, or social group? -1. **Define fairness metrics**. Finally define a metric so you have something to measure against in your work to improve the situation. +1. **Define fairness metrics**. Finally, define a metric so you have something to measure against in your work to improve the situation. ### Identify harms (and benefits)