Ethicruit: A Framework for Designing Ethical AI Systems in Employment and Recruitment Processes

Artificial Intelligence use in recruitment has enhanced efficiency but also created ethical issues regarding bias, fairness, and transparency. The conventional AI recruitment systems tend to perpetuate existing human prejudices, which result in gender, race, or socioeconomic-based discrimination. With this problem, we suggest Ethicruit, a novel framework for AI that will promote fair and ethical hiring. It applies debiasing algorithms to preprocess the data and uses fairness-aware machine learning algorithms to make more informed decisions. The system incorporates an explainability module that provides transparent reasons for every recommendation and eliminates the "black box" issue. Experiments demonstrate that Ethicruit is less biased while maintaining accuracy and efficiency in candidate ranking. This research enables Responsible AI by encouraging fairness, diversity, and inclusion in the workplace.

Artificial Intelligence(AI), Ethical Recruitment, Bias Mitigation, Fairness-Aware Machine Learning, Explainable AI(XAI), Responsible AI, Diversity and Inclusion

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