What is responsible AI?
Responsible AI is the design and use of AI systems in a safe, transparent way, aligned with the organization's rules and values.
Principles and practice
Responsible AI defines the "what": that systems are safe, transparent, explainable and respectful of the organization's rules and values. AI governance provides the "how": the rules, controls and responsibilities that turn those principles into something verifiable. One does not work without the other.
How it is made effective
It is not a statement of intent but a series of design decisions: traceability of every result, human-in-the-loop control at the decision points and clear rules over data and permissions. Built in from the start, it lets the organization trust its systems and be accountable for them.
How we approach it at Codara
Responsibility is built into our method: we design systems with human oversight, traceability and control over data from the start, so your organization uses AI safely and can be accountable for every decision.
Preguntas frecuentes
How does it differ from AI governance?
Responsible AI is the principles —safety, transparency, alignment with rules and values—; AI governance is the set of rules, controls and responsibilities that make them effective in practice.
How is it applied in practice?
With traceability of every result, human oversight at the decision points and clear controls over data and permissions, built into the system from the design stage rather than added at the end.