The inconvenient truth about AI ethics in observability

This post argues that AI ethics is simply a practical data quality issue. It explains how messy, biased, and insecure observability data leads to untrustworthy AI that can amplify existing problems. The solution requires actionable steps, like stripping sensitive PII and validating data in real-time. The key is a well-managed telemetry pipeline that gives teams the control to clean, understand, and secure their data before it’s used for training.