Can Users Control and Understand a UI Driven by Machine Learning?

We live in a world flooded by information. It's harder and harder for us to keep track of it or to manually curate it for others; luckily, modern data science can sort through the vast amounts of information and surface those items that are relevant to us. Machine-learning algorithms rely on user knowledge and patterns observed in the data to make inferences and suggestions about what we may like or be interested in. With machine-learning technologies becoming more and more accessible to developers, there's a push for companies to take advantage of these algorithms to improve their products and their users' experience. Unfortunately, these algorithms are usually not transparent to the end users. People are not sure which of their actions are taken into account by these algorithms, and their outputs are not always easy to make sense of.