Can theartificial intelligence optimize the process selection of talent?

Abstract

Hiring processes are intended to recruit and retain ideal candidates; those who would generate competitive value in an organization. In an increasingly global context, the challenge is often costly, inefficient, and complex. Even though artificial intelligence already solves specific tasks with greater speed, precision, and efficiency in various fields, and in different companies, in the area of human resources the desirability of the use of data science continues to be debated. By reviewing cases and research, in which the integration of artificial intelligence applications in the selection processes was tested, measuring and socializing impacts, I contribute to the current discussion aimed at overcoming the mistrust that exists by default, and that is associated with the ethical challenges and risks t assumed to solve a human problem through technology. I conclude that it is possible to turn artificial intelligence into a collaborative and augmented intelligence, through its interaction with human cognition, which manages to reduce time and costs; increase employee satisfaction; and manage cognitive biases, to make better decisions in the hiring process.