How can Machine Learning improve user experience?

With a quick look around Medium and enterprise's blogs, it becomes clear that intelligent automation is boosting the unfolding reality that digital labour is flexible, lean, and cost-efficient for business software applications-- for both their clients and their independent contractors. You can have a brief overview simply by checking existing APIs like Amazon intelligence API, Google Cloud AI Products, Microsoft Cognitive services and IBM Watson Products to have an idea about the kinds of inputs and logic are being used to train those models. Nevertheless, it was a section on how to design intelligent systems in the SAP Fiori design guidelines that caught my attention to the role of design when creating seamless ML-based software experiences. As Reiss writes: "to allow users to feel that they're contributing to the AI insights, by indicating how useful the guidance was -- allowing the system to learn about which guidance was followed and which not, and hence improve future guidance". This comes hand in hand with our beloved Jakob Nielsen's #1 general heuristic for interaction design, the visibility of system status.