Published on 06/10/2020
By Alexei Markovits, AI Team Manager, Element AI
The world around us is constantly changing due to ground-breaking advances in artificial intelligence (AI). AI systems are being used to buy and sell millions of financial instruments, assessing insurance claims, assigning credit scores and optimising investment portfolios. Along with these advancements, we also need a framework for understanding how AI arrives at its findings and suggestions, in order to build trust to use them to their full potential.
The processes behind how modern AI works isn’t always obvious. Many of today’s advanced machine learning algorithms that power AI systems are inspired by the processes of the human brain, but are limited by their lack of human ability to explain actions or reasoning.
With this in mind, an entire research field is now working towards describing the rationale behind AI decision-making: Explainable AI (XAI). While modern AI systems demonstrate performance and capabilities far beyond previous technologies, practicality and legal compliance present hurdles to successful implementation.