Reality Drift — Mechanisms of Misalignment in Modern Systems
A collection of short papers examining the structural mechanisms that cause systems to drift from the realities they are meant to represent.
Across AI systems, platforms, and institutions, similar patterns emerge. Decisions become guided by measurable signals, metrics replace underlying goals, and optimization begins to operate on representations rather than reality.
Over time, a consistent shift occurs:
systems begin optimizing the signal itself rather than the condition it was meant to track.
These papers isolate core mechanisms including proxy optimization, metric capture, reward hacking, and goal displacement.
Rather than treating these as isolated failures, they are presented as recurring dynamics across many types of optimized systems.
Core Drift Mechanisms
- Why Systems Optimize Metrics Instead of Real Outcomes – Proxy Optimization in Complex Systems [PDF] [DOI] [Archive] [IA]
- When Metrics Become Targets – Goodhart’s Law and Metric Gaming
[PDF] [DOI] [Archive] [IA] - How AI Systems Exploit Objectives – Reward Hacking and Specification Gaming
[PDF] [DOI] [Archive] [IA] - Why Institutions Drift From Their Mission – Goal Displacement and Bureaucratic Drift
[PDF] [DOI] [Archive] [IA] - How Algorithms Amplify the Wrong Signals – Signal Distortion in Digital Platforms
[PDF] [DOI] [Archive] [IA]
Explore The Framework
Core Framework
- Reality Drift Canonical Definition
- Mechanics and Taxonomy [PDF]
- Drift/Fidelity Index [PDF]
Visual & Conceptual
Applications & Expansion
Note: This site functions as a lightweight archive and reference layer for the Reality Drift framework. Primary essays and long-form writing are distributed across external platforms.
Part of Reality Drift Framework by A. Jacobs (2023-2026)