Recency Bias
A cognitive bias where recent events are weighted more heavily than earlier ones when making evaluations. In performance reviews, recency bias causes managers to base ratings primarily on the last 2-4 weeks rather than the full review period—resulting in inaccurate assessments that miss sustained contributions and penalize employees whose strongest work happened months ago. AI agents counter recency bias by tracking achievements throughout the review period and surfacing a balanced, time-distributed evidence set.
Written by Max Zeshut
Founder at Agentmelt · Last updated Oct 26, 2026
Frequently asked questions
- How do AI agents specifically counter recency bias?
- By continuously logging achievements from project management tools, code repositories, CRM, and peer feedback throughout the review period. When generating review drafts, the agent pulls examples from each quarter or month evenly, flagging when a manager's draft relies too heavily on recent events. Studies show this awareness alone reduces recency bias by 30-40% in subsequent review cycles.