Ethics, Fairness, and Bias in AI - KDnuggets

Today, AI is getting adopted in everyday life, and now it is more important to ensure that decisions that have been taken using AI are not reflecting discriminatory behaviour towards a set of populations. It is important to take fairness into consideration while consuming the output from AI. Discrimination towards a sub-population can be created unintentionally and unknowingly, but during the deployment of any AI solution, a check on bias is imperative. Example 1: Machine learned human biases that result in a model with racial disparity. In the United States, amongst the population sent to lock-up include blacks in disproportionate number. For centuries, the key decisions in the legal process are governed by human instincts and biases.