Summary of Challenges and Opportunities Of Nlp For Hr Applications: a Discussion Paper, by Jochen L. Leidner and Mark Stevenson
Challenges and Opportunities of NLP for HR Applications: A Discussion Paper
by Jochen L. Leidner, Mark Stevenson
First submitted to arxiv on: 13 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper reviews the applications of machine learning (ML) and natural language processing (NLP) in hiring and human resource management. Specifically, it explores the use cases for text analytics in HR/personnel management, including both realized and potential but not yet implemented ones. The authors analyze the opportunities and risks of these applications. The study leverages recent progress in ML/NLP to identify areas where text analytics can enhance HR processes, such as job posting analysis, candidate screening, and employee feedback evaluation. By examining existing and potential use cases, this research aims to shed light on the potential benefits and challenges of integrating ML/NLP into HR management. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine using artificial intelligence (AI) to help with hiring and managing employees. This paper looks at how AI can be used in human resources (HR). It explores different ways AI can be applied, such as analyzing job postings or screening candidates. The authors also discuss the benefits and challenges of using AI in HR. They want to help people understand how AI can make HR processes more efficient and effective. |
Keywords
» Artificial intelligence » Machine learning » Natural language processing » Nlp
