Challenges and Opportunities of NLP for HR Applications: A Discussion Paper
Jochen L. Leidner, Mark Stevenson
TL;DR
This paper examines how natural language processing can support human resources throughout the employment lifecycle, mapping opportunities and risks arising from recent NLP advances. It adopts an employment lifecycle framework to identify concrete applications, from resume extraction and job posting generation to candidate matching and onboarding, while analyzing ethical, fairness, privacy, and equity concerns. The authors synthesize related work, highlight practical design considerations such as workflow transparency and user-centric chatbots, and discuss mechanisms like fair matching and multilingual support. The work aims to guide researchers and practitioners toward responsible, impactful, and inclusive NLP-enabled HR systems, and calls for regulatory measures where appropriate to protect workers.
Abstract
Over the course of the recent decade, tremendous progress has been made in the areas of machine learning and natural language processing, which opened up vast areas of potential application use cases, including hiring and human resource management. We review the use cases for text analytics in the realm of human resources/personnel management, including actually realized as well as potential but not yet implemented ones, and we analyze the opportunities and risks of these.