Abstract
With the recent advancement in data science, Predictive Analytics (PA) functions have been built into many commercial products, which affects several "non-functional" goals, including usability, performance, and transparency of the software, as well as privacy and well-being of the user. The direct and indirect consequences are yet to be understood better before the service providers take any further actions in response. In this work, a survey was conducted with a sample set of 153 respondents from U.S., on their acceptance of applications with PA. The result shows that many consumers recognize the benefit of PA features, but they are not without concerns about transparency, privacy, and personal well-being. Once users are highly concerned, they may choose not to use these features or even give up the products altogether. Based on the survey result, we have discussed how requirements engineering can help the stakeholders make better decisions related to PA adoption and design, and how RE tools can help address user concerns related to PA.