A challenge-based survey of e-recruitment recommendation systems
E-recruitment recommendation systems recommend jobs to job seekers and job seekers to
recruiters. The recommendations are generated based on the suitability of job seekers for …
recruiters. The recommendations are generated based on the suitability of job seekers for …
Policy advice and best practices on bias and fairness in AI
JM Alvarez, AB Colmenarejo, A Elobaid… - Ethics and Information …, 2024 - Springer
The literature addressing bias and fairness in AI models (fair-AI) is growing at a fast pace,
making it difficult for novel researchers and practitioners to have a bird's-eye view picture of …
making it difficult for novel researchers and practitioners to have a bird's-eye view picture of …
Fairness, AI & recruitment
C Rigotti, E Fosch-Villaronga - Computer Law & Security Review, 2024 - Elsevier
The ever-increasing adoption of AI technologies in the hiring landscape to enhance human
resources efficiency raises questions about algorithmic decision-making's implications in …
resources efficiency raises questions about algorithmic decision-making's implications in …
Challenges and Opportunities of NLP for HR Applications: A Discussion Paper
JL Leidner, M Stevenson - arXiv preprint arXiv:2405.07766, 2024 - arxiv.org
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 …
machine learning and natural language processing, which opened up vast areas of potential …
Towards Positive Outcomes in the AI Economy: Mitigating Algorithmic Collusion and Enabling Fair Recourse
E Mibuari - 2024 - dash.harvard.edu
The rise of Artificial Intelligence (AI) promises to solve many important problems in the world.
At the same time, awareness has been increasing about its potential and real harms. How …
At the same time, awareness has been increasing about its potential and real harms. How …