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

From Nielson Norman Group: https://www.nngroup.com/articles/machine-learning-ux

Summary: In a study of people interacting with systems built on machine-learning algorithms, users had weak mental models and difficulties making the UI do what they want.



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.

Typical uses of such artificial-intelligence (AI) technologies for UX purposes include:

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