Explainable AI and the Rebirth of Rules
Summary
But if you want to use artificial intelligence in a regulated industry, you better be able to explain how the machine predicted a fraud or criminal suspect, a bad credit risk, or a good candidate for drug trials. Enter the “knowledge engineers.” Rainbird’s customers like Taylor Wessing find people who have a penchant for learning the domain and the technology. This is easier in fields such as reading medical images, where there might be tens of millions of examples of relevant MRI’s or CAT scans. Rainbird’s technology provides an example of the explainability advantage of rule engines: it offers an “evidence tree” that describes how a particular decision was made. Carla O’Dell is the chairman of APQC, a non-profit business research institute focused on benchmarking, best practices, process improvement and knowledge management for a global corporations and consulting firms.