Biased AI, a Look Under the Hood. What exactly is going on in AI systems…

In order to gain a better understanding of the background to this problem, let us first introduce some fundamental knowledge about machine learning. Compared with traditional programming, one major difference is that the reasoning behind the algorithm's decision-making is not defined by hard-coded rules which were explicitly programmed by a human, but it is rather learned by example data: thousands, sometimes millions of parameters get optimised without human intervention to finally capture a generalised pattern of the data. The resulting model allows to make predictions on new, unseen data with high accuracy. To illustrate the concept, let's consider a sample scenario about fraud detection in insurance claims. Verifying the legitimacy of an insurance claim is essential to prevent abuse.