NSF Award
2403479
This project explores the development and implementation of Automated Hiring Platforms that use complex mathematical formulas and artificial intelligence when making choices about whom to hire for a job. This is an important issue because Automated Hiring Platforms have sometimes been found to be biased in their selection of employees from particular social groups and because they often lack transparency regarding the factors that go into their decisions. This project aims to understand the social and ethical dimensions of how Automated Hiring Platforms are created and how they function within the job market. This will be accomplished through surveying companies that use Automated Hiring Platforms about how they use them, observing how Automated Hiring Platforms are designed, and through interviews with those who design and develop them and with human resources professionals and job applicants. The project will also result in the creation of a new code of ethics for the design and use of Automated Hiring Platforms.<br/><br/>Automated Hiring Platforms are among the most visible and consequential forms of artificial intelligence because of their importance for hiring decisions, because they can be systematically biased in their selection criteria, and because they often operate as 'black boxes' the design and inner workings of which are unknown. This project would advance recent research in Science and Technology Studies that has begun to consider the social and ethical implications of artificial intelligence for human-computer interaction, social stratification, and the future of work. The main goals of this project are: 1) To provide better social scientific understanding of the human-computer interactions involved in using Automated Hiring Platforms and how they are designed; 2) To educate the public and organizations about the technical capabilities, limitations, and ethical issues arising from algorithmic hiring tools; and 3) To facilitate the development of ethical codes of conducts for designers, developers and consumers of algorithmic hiring tools. This will be accomplished via a mixed-methods research design involving surveys, interviews, observations, and documentary content analysis.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
