Artificial intelligence (AI) permeates our everyday lives, and with software being introduced that is increasingly more sophisticated, being able to understand how machines make decisions is vital. In banking, this is all the more important, as artificial intelligence is often implemented to streamline processes but experts still need to understand how a computer has arrived at its decision.
This kind of artificial intelligence is known as ‘explainable’ AI, or XAI. It’s this specialty that Prof. Jacques Klein, head of the TruX research group at SnT is applying to one of his current projects with BGL BNP Paribas, as they develop explainability for financial machine learning algorithms.
In this article with Paperjam, Prof. Klein discusses what the work has involved, as well as why this type of AI is implemented over other kinds. Read the full article here.