explainability-can-address-every-industrys-ai-problem-the-lack-of-transparency

In its nascent stages, AI may have been able to rest on the laurels of newness. It was okay for machine learning to learn slowly and maintain an opaque process where the AI's calculation is impossible for the average consumer to penetrate. As more industries such as healthcare, finance and the criminal justice system begin to leverage AI in ways that can have real impact on peoples' lives, more people want to know how the algorithms are being used, how the data is being sourced, and just how accurate its capabilities are. If companies want to stay at the forefront of innovation in their markets, they need to rely on AI that their audience will trust. AI explainability is the key ingredient to deepen that relationship. AI explainability differs from standard AI procedures because it offers people a way to understand how the machine learning algorithms create output.