AI-Driven Emotional Intelligence and Behavioral Profiling for Smart Recruitment Systems

In organizational development, recruitment is a crucial phase and the selection of appropriate candidates plays a vital role in shaping the productivity, culture, and growth of the organization in the long run. The traditional methods of recruitment mainly depend on Resumes, Aptitude Test, and manual interviews which are less effective in measuring the emotional intelligence, behavioural traits, communication skills and psychological fitness of the candidates. Artificial Intelligence (AI) has been proving to be a viable solution to automate recruitment processes and enhance the efficiency of decision-making in recent years. But current AI driven recruitment systems primarily use keyword matching, facial expression or single behavioral factors, which suffer from several drawbacks like bias, lack of explainability, lack of adaptability and privacy issues.

This paper proposes a problem statement and conceptual framework that is reviewed to develop an AI-based emotional and behavioral assessment system for recruitment. The framework proposed incorporates multiple modalities like facial expressions, speech patterns, text responses, and behavioral interactions to better assess the suitability of candidates. The framework is built on principles of machine learning, deep learning, natural language processing, and explainable AI, to promote fairness, transparency, and reliability of decisions. The study reveals the key research gaps in current recruitment systems and the significance of intelligent and adaptive recruitment models that are emotion-aware and privacy preserving. The proposed solution is to help the recruiters to make an accurate, unbiased and data-driven decision during the hiring process.