Originally published at https://blog.akshatuniyal.com . A plain-language guide to Responsible AI — and why it matters more than most people realise Picture a loan application. A person applies, gets rejected, and asks why. The bank says the model decided. The model’s vendor says it just built the tool — how the bank configured it is on them. The bank’s data team says the training data came from a third party. The third party says they only supplied the data, not the logic. Everyone touched the system. Nobody owns the outcome. This is not a hypothetical. It’s Tuesday. The word nobody can agree on “Responsible AI” has been on enough conference slides and annual reports that it’s started to sound like wallpaper. Which is a problem — because underneath the corporate gloss, it’s pointing at something real and increasingly urgent. At its core, Responsible AI is the practice of building and deploying AI systems that are fair, transparent, safe, and accountable. Not just to the engineers who built them.…