By Dr. David Bray and R “Ray” Wang
Over the last ten years, organizations have begun to rely on an ever-growing number of algorithms to assist in making a wide range of business decisions, including delivery logistics, airline route planning, financial fraud detection, image recognition etc. As we’re currently experiencing the end of the second wave of artificial intelligence (AI), a specific subset of AI, called deep learning, will play an even more critical role in the nearest future. Moving into the next stage, the key question for organizations will be how to embrace deep learning for driving better business decisions while at the same time avoiding biases and potentially bad outcomes. In this article, PCI Executive Director Dr. David Bray and R “Ray” Wang share determined patterns that can help companies reduce error rates when implementing deep learning initiatives.