Learn about protected attributes like race, age, sex, and ethnicity and why they should be excluded from AI models used in recruiting to ensure fairness and avoid discrimination.
Table of Contents
Question
Maria is on a team creating an AI model to help recruit engineers. Maria wants to ensure that the data set does not include specific attributes such as race, age, sex at birth, and ethnicity.
What type of attributes are these examples of?
A. Private attributes
B. Privileged attributes
C. Confidential attributes
D. Protected attributes
Answer
D. Protected attributes
Explanation
Attributes that separate the population into groups that could introduce disparity or inequity are called protected attributes. While there isn’t a defined set of protected attributes, some generally protected attributes include race, age, sex at birth, gender identity, and ethnicity.
The attributes that Maria wants to ensure are not included in the data set—such as race, age, sex at birth, and ethnicity—are examples of protected attributes.
Protected attributes are personal characteristics that are legally protected against discrimination under various regulations. In the context of AI and hiring, it’s important to avoid these attributes to prevent biases and ensure fairness in the recruitment process.
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