Job Search 2.0: Artificial Intelligence Impact in Candidate Pre-Screening
Professor Huiling Ding teaches technical communication at North Carolina State University. She is the Director of the MS in Technical Communication program and a University Faculty Scholar. Her research focuses on intercultural professional communication, technical communication, risk communication, and epidemic communication. Her recent projects have been exploring the connections between artificial intelligence, communication technologies, risk communication, and social justice. As the principal investigator of a large multidisciplinary NSF C Accel grant, she has been leading her team to examine how AI tools have been transforming the job market and job screening processes in the U.S.
In this episode of Room 42 we discuss the impact of AI on job application materials and strategies.
The socio-technological landscape of work has been radically and permanently changed. Ever increasing demands for recruiters to present the exact ideal candidates for job openings has created more reliance on Artificial Intelligence (AI) for pre-screening and matching volumes of candidates against defined criteria.
To understand the impacts of emerging AI-augmented pre-hire assessment tools, this talk will examine assessment tools such as applicant tracking systems, resume screeners, and on-demand video interviews. We will also examine assumptions about pre-hire screening criteria and procedures used by technology and the impact of such tools on job application materials and strategies.
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