Inc. shut down a project it had been developing for four years, a recruitment tool driven by machine learning. The concept was a simple and appealing one: at its core, the project aimed to develop an algorithm that would sort incoming job applications to isolate the short list for managers to use in making their final selections. Anyone who has been involved in such a process knows that isolating the top five or ten resumés from dozens of applicants is a time-consuming job. Any process that brings logic and speed to this stage of the recruitment chain can only be a good thing. But algorithms are only as good as the data used to drive them, and in the Amazon case the machine "learning" was based on patterns in applications submitted to the firm in the previous ten years.