algorithmic accountability

Algorithmic accountability is the governance practice of assigning responsibility for the outcomes of automated systems to the organizations and individuals that design, deploy, and operate those systems. It operates through three parameters: (1) traceability of algorithmic decisions back to human actors, (2) enforceable consequences when harm occurs, and (3) mechanisms for affected parties to seek redress. Its persistence mechanism is institutional — embedded in regulatory frameworks, organizational policies, and legal liability structures that outlive individual systems. Algorithmic accountability is not a property of the technology itself but a social arrangement imposed on its lifecycle. See also: algorithmic transparency, due diligence, audit trail. This definition carves the concept by specifying its parameters and persistence mechanism as required by Law 4.