Ai Based Techniques to Detect and Prevent Dark Personality Traits In Organizational Settings

Haripriya Nagasubramanian, T. S. Saranya () and Sandeep Kumar Gupta
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Haripriya Nagasubramanian: Independent Researcher
T. S. Saranya: Head of the Institute, AIBHAS, Amity University Bengaluru
Sandeep Kumar Gupta: Mohan Babu University

A chapter in Proceedings of the International Conference on Artificial Intelligence in Management for Business and Industrial Growth (AIMBIG 2025), 2025, pp 227-246 from Springer

Abstract: Abstract This review paper analyses the role of HCI (Human Computer Interface) and AI (Artificial Intelligence) techniques in detecting dark personalities within organizational settings, focusing on personality screening and prediction. In this review, the effectiveness of AI, notably deep learning (DL) algorithms, in boosting the prediction diagnostic precision of personalities, minimizing false positives, and improving operational efficiency is showcased. Various DL and ML frameworks show great promise in supporting human resources personnel by enhancing both sensitivity and specificity in identifying personalities. Nevertheless, challenges such as algorithmic bias, implementation difficulties, need for training the data and the necessity for varied data sets impede widespread organizational implementation. Regardless, the results highlight that incorporating AI and HCI algorithms into organizational routines can transform dark triad of personality in workplace settings, facilitating earlier detection and optimizing resources. The analysis stresses the need for additional validation and training for human resource professionals to guarantee the smooth integration of AI technology into organizational practices.

Keywords: “AI in personality detection”; “dark triad traits detection using AI”; “Deep Learning (DL) in personality detection”; “Convolutional Neural Networks (CNN) in detecting personality”; “HCI and AI integration in the workplace”; “HCI in detecting personality”; “Ethics of AI in employee monitoring” (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-898-1_18

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DOI: 10.2991/978-94-6463-898-1_18

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