When company leaders talk about democratizing artificial intelligence (AI), it’s easy to imagine what they have in mind. The more people with access to the raw materials of the knowledge, tools, and data required to build an AI system, the more innovations are bound to emerge. Efficiency improves and engagement increases. Faced with a shortage of technical talent? Microsoft, Amazon, and Google have all released premade drag-and-drop or no-code AI tools that allow people to integrate AI into applications without needing to know how to build machine learning (ML) models.
But as companies move toward democratization, a cautionary tale is emerging. Even the most sophisticated AI systems, designed by highly qualified engineers, can fall victim to bias and can be difficult to explain. An AI system that was built by someone without proper training or that is operated without appropriate controls could create something outright dangerous, introducing discrimination or serious