Day: 30 May 2020

One of the most common misperceptions in the world of Machine Learning about bias is “If I don’t use age, gender or race, or similar factors in my model, it’s not biased.” Well, that’s not true. Even though the same people holding this opinion know that Artificial Intelligence can ‘learn’ and compute relationships between data, they don’t understand that there are proxies to biased data types in other features that are captured. These proxies are called confounding variables and, as the term indicates, unintended variables can confuse the model into…