Big City Bias: Evaluating the Impact of Metropolitan Size on Computational Job Market Abilities of Language Models

arXiv:2403.08046v1 Announce Type: new
Abstract: Large language models (LLMs) have emerged as a useful technology for job matching, for both candidates and employers. Job matching is often based on a particular geographic location, such as a city or region. However, LLMs have known biases, commonly derived from their training data. In this work, we aim to quantify the metropolitan size bias encoded within large language models, evaluating zero-shot salary, employer presence, and commute duration predictions in 384 of the United …

abstract arxiv bias big city computational cs.cl employers however impact job job market language language models large language large language models llms location market technology type