Insurance is moving toward a world in which carriers will not be allowed to make decisions that affect customers based on black-box AI. Artificial intelligence (AI) holds a lot of promise for the insurance industry, particularly for reducing premium leakage, accelerating claims and making underwriting more accurate. AI can identify patterns and indicators of risk that would otherwise go unnoticed by human eyes. Unfortunately, AI has often been a black box: Data goes in, results come out and no one -- not even the creators of the AI -- has any idea how the AI came to its conclusions. That's because pure machine learning (ML) analyzes the data in an iterative fashion to develop a model, and that process is simply not available or understandable.

In my first post in this series, I wrote that one definition of artificial intelligence (AI) is a machine that thinks. Several people with technical backgrounds in the AI field reached out to me after reading that post. One comment I received that I found striking is that AI is neither A nor I. Instead, it is just computer code. Nothing is thinking; a computer is just following directions. And AI is just inputs to outputs for a goal.