Objectivity by design: The impact of AI-driven approach on employees' soft skills evaluation

Ruti Gafni, Itzhak Aviv, Boris Kantsepolsky, Sofia Sherman, Havana Rika, Yariv Itzkovich, Artem Barger

Research output: Contribution to journalArticlepeer-review

Abstract

Engineers’ team collaboration skills are among software development's most important success factors. Existing Artificial Intelligence practices for the engineers' soft skills assessment mainly rely on evaluations of subjective data gathered through surveys, interviews, or observations. As a result, the insights gained by these methods are biased because of the subjective data people report. To overcome the challenge of subjectivity, we offer a novel objectivity-by-design approach for continuous AI-driven team collaboration skills analytics. The method analyzes the data from workstreams gathered from data repositories like Jira. Based on the study results, we conclude that this approach enables a continuous assessment of employees' team collaboration skills, provides more accurate insights, eliminates subjective biases, and helps uncover trends and deficits on individual and team levels. Understanding and recognizing employees' strengths and weaknesses can foster an organizational culture of growth and development. An improved organizational climate is expected to result in work satisfaction, engagement, and motivation, thus positively impacting employees, businesses, and society.

Original languageEnglish
Article number107430
JournalInformation and Software Technology
Volume170
DOIs
StatePublished - Jun 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024

Keywords

  • Artificial intelligence
  • Data Science
  • Employees analytics
  • Machine learning
  • Soft skills assessment

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Science Applications

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