Fair and Ethical Resume Screening: Enhancing ATS with JustScreen the ResumeScreeningApp
DOI:
https://doi.org/10.70715/jitcai.2024.v2.i1.001Abstract
Abstract— In today's fast-paced job market, the efficiency and
fairness of the resume screening process are paramount.
"JustScreen" emerges as a cutting-edge solution leveraging
advanced Natural Language Processing (NLP) to automate
resume evaluation, thus eliminating biases and promoting merit-
based candidate selection. This thesis explores JustScreen's
innovative approach to integrating NLP and machine learning
algorithms to enhance the recruitment workflow, ensuring a more
streamlined, unbiased, and efficient candidate assessment process.
The methodology involves several key components: data
preprocessing, NLP information extraction, fairness metrics
calculation, bias mitigation, and interpretability techniques. By
utilizing frameworks such as spaCy for NLP tasks, JustScreen
aims to overcome the challenges of traditional manual screening
processes, improving both accuracy and fairness. This thesis
explores the transition from developing a full Application
Tracking System (ATS) to creating a powerful enhancement for
existing ATS systems. The ResumeScreeningApp/ JustScreen
integrates generative AI to provide comprehensive resume
analysis, adding significant value to traditional ATS
functionalities. Initial evaluations indicate a significant
advancement in talent acquisition practices, promoting equal
opportunities and reducing the impact of potentially
discriminatory factors. This research signifies a transformative
shift in recruitment, setting new standards for ethical and efficient
hiring practices using Generative AI.
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Copyright (c) 2025 Gloribeth Navarro (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
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