Algorithmic Accountability

Algorithmic accountability refers to the obligation of organizations that develop or deploy AI systems to take responsibility for the outcomes those systems produce — and to be able to demonstrate that responsibility to regulators, affected individuals, and the public. It encompasses transparency about how systems work, mechanisms for challenging or appealing AI-driven decisions, audit trails that allow outcomes to be traced and explained, and governance structures that ensure ongoing oversight. Accountability is not achieved by having a policy: it is demonstrated through evidence. Eticas.ai helps organizations build the evidence base — through independent evaluation and continuous monitoring — that makes accountability demonstrable rather than merely claimed.