Exploring the role of Artificial Intelligence in assessing soft skills

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Abstract

Recent research has underscored the pivotal role of soft skills in navigating the complexities of today's workplace dynamics. Soft skills encompass a broad spectrum of attributes, such as effective communication, adept collaboration, nimble adaptability, and profound emotional intelligence, all of which are integral to fostering productive team environments and driving organizational success. Despite their acknowledged importance, quantifying and evaluating soft skills has traditionally been hindered by their inherently subjective nature. However, the emergence of artificial intelligence (AI) technologies has revolutionized the landscape of skill assessment, presenting novel opportunities to address these longstanding challenges. By leveraging AI-powered algorithms, organizations can now analyze vast datasets encompassing various facets of human interaction, enabling a more nuanced and objective evaluation of individuals' soft skill proficiencies. Moreover, AI-driven assessments offer scalability, allowing for the efficient evaluation of large cohorts of employees or candidates. Nonetheless, this intersection of AI and soft skills measurement is not without its obstacles. Ethical considerations surrounding data privacy, algorithmic bias, and the potential for automation-induced job displacement necessitate careful scrutiny and regulation. Furthermore, the dynamic nature of soft skills presents a continuous challenge, as individuals must continually adapt and refine their abilities to meet evolving workplace demands. Despite these challenges, the synergistic relationship between AI and soft skills measurement holds immense promise for the future of talent assessment and development. By embracing AI-driven approaches, organizations can cultivate a workforce equipped with the diverse skill set necessary to thrive in an ever-changing professional landscape.

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APA

Ciaschi, M., & Barone, M. (2024). Exploring the role of Artificial Intelligence in assessing soft skills. In Annals of Computer Science and Information Systems (pp. 573–578). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.15439/2024F2063

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