Biases Introduced by the Algorithm Itself

Abstract

In the discussion so far, you have experienced algorithms as neutral and fact-driven and actively pursuing the goal of debiasing decision-making. The types of algorithmic biases reviewed all originated outside of the algorithm, such as in real-world biases or inadequate data. In this chapter, we will dive deeper in how an algorithm works and discover situations in which an algorithm "randomly" introduces new biases in the sense of prejudice against specific profiles of instances. Much of this can be considered noise, but every once in a while, such an algorithmic bias can be magnified, reinforced, or even whipped up by the context of how the algorithm is used, in which case the effect of such an algorithmic bias might grow out of proportion.