- Machine learning algorithms used in recommendation systems must be made more transparent to users. Users currently do not understand how the systems work and feel they have no control over the recommendations. - Interviews with users revealed fears about data privacy and a lack of understanding of how user interactions influence recommendations. Users have not formed clear mental models of how recommendation systems track and use their data. - User experience designers need to help users build better mental models of recommendation systems and deconstruct the "black box" feeling. Designers must also encourage users to provide feedback and give them more control over their data and recommendations.