Jamie stared at the notification on her screen: "Your quarterly performance review is scheduled for tomorrow. AI-assisted insights are available for preview." As an employee at TechFusion, she had seen the company revise its approach to performance management over the past year. The old system of annual reviews had been replaced with quarterly conversations supported by an artificial intelligence (AI) platform that analyzed work patterns, communication, and project outcomes throughout the quarter.
Some employees embraced the change, appreciating the continuous feedback and data-driven insights. Others worried about privacy, algorithm bias, and whether complex human performance could truly be captured by AI. When Jamie clicked the notification, she found not just metrics but suggestions for discussion points, personalized development resources, and patterns in her work that she had not noticed herself. The AI had identified her strongest collaborations and projects where she appeared to struggle and even suggested some potential growth opportunities based on her skill profile. As she prepared for tomorrow's conversation with her manager, Jamie wondered about the implications of this new approach.
Please read this article: Boundaries of Generative AI: When to Hold Back?
Then, discuss the following with your fellow classmates:
- What makes performance appraisal meetings valuable?
- What are some ethical ways AI can be used to improve individual performance?
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