Abstract
This research delves into the transformative influence of Generative Artificial Intelligence (GenAI) on the self-evaluation processes of employees within contemporary organizations. In an era marked by rapid technological advancements, the integration of AI into various facets of the workplace is reshaping traditional paradigms. We use Self-Evaluation Maintenance (SEM) Model, which is our theoretical lens, and combining with the concept of Core Self-Evaluation (CSE) to conduct our research model. This study seeks to elucidate whether the usage of GenAI, specifically in the context of performance compares to GenAI, and then the impact on CSE, which we plan to use in this research, has discernible effects on how employees perceive and evaluate their own contributions. In addition, we adapt various reliable scales to assess the constructs in our research model. This research employs surveys and content analysis of questionnaire data to investigate the perceptions of employees in organizations that have introduced GenAI-driven tools for performance appraisal. The objective is to determine whether these tools, by providing real-time feedback, personalized recommendations, and novel evaluation metrics, result in changed self-perceptions and attitudes towards one's work.
Recommended Citation
Chou, Chih-Yuan and Lee, Chen-Wei, "How Employee Use of Generative Artificial Intelligence Affects Self-Evaluation: Investigating Implications for Job Insecurity and Career Commitment" (2023). Digit 2023 Proceedings. 4.
https://aisel.aisnet.org/digit2023/4
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