AAA-06 - Algorithmic Mediation and the End of Intentional Action

This paper examines how algorithmic mediation transforms the structure of human action. Classical accounts of agency assume that intentional action emerges within a temporal gap between perception and response, where individuals deliberate, choose, and commit to outcomes. The expansion of algorithmic systems—such as recommendation engines, ranking systems, adaptive interfaces, and predictive decision tools—compresses this gap by pre-structuring the environment of choice.As a result, actions increasingly occur within dynamically configured decision environments rather than through independent deliberation. Individuals continue to perform observable acts (selecting, approving, navigating), but these acts often take place within trajectories shaped in advance by system design and predictive models. The subjective experience of choosing remains, yet the underlying architecture of intention becomes attenuated.This transformation has two major consequences. First, decisive moments of choice tend to dissolve into sequences of micro-actions distributed across time, making the locus of intention difficult to identify. Second, responsibility becomes structurally diffuse: outcomes emerge from interactions between users, institutional procedures, data infrastructures, and algorithmic systems. Accountability therefore shifts from tracing intentional action to assigning responsibility through institutional attribution.The paper argues that the primary change introduced by algorithmic mediation is not the disappearance of agency but its reconfiguration—from agency as the origin of action to agency as an interface within system-mediated processes. In this configuration, individuals remain present in decision loops but are no longer the primary authors of the trajectories they enact.Understanding this shift is essential for contemporary debates in philosophy of action, moral responsibility, and algorithmic governance.