Building trust in machine learning and AI

Many machine learning and artificial intelligence (AI) systems lack the ability to explain how they work and make decisions--and this is a major trust inhibitor. They can find patterns in data that elude us, patterns that might reveal important relationships that improve the accuracy of the algorithm. They can recover patterns and relationships that we as human beings want to ignore. But they can just as easily fail to discover important relationships and produce bad recommendations, even dangerous ones. A well-known example of the latter involved research to see whether machine learning could guide the treatment of pneumonia patients.