---
id: 1239
title: "AI Bias: Consequences and Mitigation"
source_domain: hackerone.com
source_url: "https://www.hackerone.com/blog/ai-bias-consequences-and-mitigation"
published_at: "2025-04-18 17:23"
tags: ["ai-security", "ai-safety", "machine-learning", "healthcare", "ethics", "ai-bias", "training-data"]
phying_url: "https://phying.com/item/1239"
lang: en
---

# AI Bias: Consequences and Mitigation

## Summary

A HackerOne researcher invokes Galton's wisdom-of-the-crowd to argue that diverse training data is essential for unbiased AI, citing racial bias in Optum's patient-care algorithm as a concrete harm.

## Intelligence Metadata

- **Sources:** hackerone.com
- **Published:** 2025-04-18 17:23
- **Original:** https://www.hackerone.com/blog/ai-bias-consequences-and-mitigation
- **Phying News:** https://phying.com/item/1239