Designed Forgetting as a Mechanism for Preserving Decision Speed Forgetting as an Evolutionarily Selected Strategy Under Latency Constraints

This paper argues that forgetting is not a defect of intelligent systems but a functionally and evolutionarily necessary mechanism for preserving decision speed under latency constraints. In real environments, delayed decisions are often equivalent to incorrect ones. Retaining excessive or irrelevant information increases internal processing cost and introduces fatal response delays. From an evolutionary perspective, agents incapable of discarding low-utility information are systematically outcompeted by faster-reacting counterparts. We propose that forgetting functions as structural pruning: reducing internal state dimensionality while retaining compressed evaluative tags that enable rapid classification and action. Subjective experience and internal labels (such as danger, comfort, or aversion) are interpreted as speed-optimized representations whose effectiveness depends on aggressive forgetting of high-resolution detail. This framework reframes forgetting as a survival strategy rather than a cognitive limitation. It further suggests that artificial intelligence systems emphasizing complete context retention risk reproducing architectures already rejected by biological evolution. Intentional, designed forgetting should therefore be treated as a core design principle for latency-constrained intelligent agents. Prior work contributing to the functional analysis of cognitive pruning and information prioritization includes the frameworks presented in https://doi.org/10.5281/zenodo.18390077 and https://doi.org/10.5281/zenodo.18371655, which explore related mechanisms of adaptive evaluation and structural simplification under task constraints.