Abstract: This article discusses how AI and machine learning can help make feedback processes more effective by overcoming innate psychological biases that hinder people's ability to openly receive and learn from criticism. It explores research on common barriers like self-affirmation bias, highlights how AI can aggregate data to remove recency and attribution biases, and provides examples of companies leveraging AI-powered feedback through tools like automated video analysis and virtual teaching assistants. The abstract concludes that when guided by training and ethics, AI shows promise in enhancing feedback culture by objectively surfacing improvement areas and delivering suggestions in a depersonalized, non-threatening manner that respects privacy.
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