RESPONSIBLE AI
Responsible AI is designed into the work. We define appropriate data use, access, human oversight, evaluation, escalation, traceability and ownership according to the use case and its risk profile.
WHY UP FRONT
When boundaries get written after the solution already works, they become a review layer that slows the work down and that people learn to route around. Defined up front, they’re part of how it’s built: the system can’t do what it has no permission to do.
Not every case needs the same thing. An assistant drafting an internal memo and an agent acting on a production system carry different risk profiles, and therefore different controls. What doesn’t change is that they’re decided and written down before anything gets built.
WHAT GETS DEFINED IN EVERY CASE
01
What information goes in, where it comes from, who can see it and what for. Defined before building, not once it’s already running.
02
Handling of personal and sensitive data, encryption, retention and isolation to fit each company’s environment.
03
What counts as an acceptable answer and how that gets checked. Without a threshold, “it works well” is an opinion.
04
Where a person reviews, approves or corrects before anything takes effect. The higher the risk, the closer that point sits to the end.
05
What happens to the cases that don’t fit: who they reach, how fast, and with what context.
06
What gets recorded about each assisted decision, so it’s possible to reconstruct afterwards why what happened happened.
07
Who answers for the operation and who for the business result. A control with no owner is a document.
08
How often behavior gets reviewed, who reviews it, and what triggers a change.
ACCOUNTABILITY ISN’T DELEGATED TO THE SYSTEM
Tell us the case and its risk profile. We’ll tell you which controls it needs before a line of code gets written.