How Machine Learning is Influencing Diversity & Inclusion

Our society is in a technological paradox. Life events for many people are increasingly influenced

To understand social bias, it is essential to define diversity and inclusion. Diversity is an appreciation of the traits that make a group of people unique, while inclusion behaviors and norms make people from these groups feel welcome to participate in a given organization.

Social biases occur through two key processes when developing programmatic software or processes initiated from algorithm decisions. One source is the fragility inherent in machine learning classification methods. Models classify training data either through statistical clustering of observations or For more information on bias in AI and ML, read these articles:

AI Ethics: Where to Start

How IT Pros Can Lead the Fight for Data Ethics

AI Machine Learning: An Enterprise Guide