A Conceptual-Methodological Research Design for Testing The Algorithmic Alienation Index and Systemised Self Hypothesis v1

Abstract

Algorithmic Alienation is an established theoretical construct with partial qualitative empirical grounding in the published work of Kanbay, Akçam, and Arkan (2026) and Arkan, Kanbay, and Akçam (2026). This document does not reconstruct that foundation. It examines the next research problem: operationalising Algorithmic Alienation through the proposed Algorithmic Alienation Index (AAI) and testing the Systemised Self as a hypothesised terminus. The AAI is a theory-derived model comprising Diminished Autonomy, Identity Ambiguity, Eroded Decision-Making, Emotional Disconnection, and Algorithmic Resistance. Its weights and thresholds remain provisional. Because an advanced subject may experience algorithmic dependence as liberation rather than estrangement, self-report cannot independently verify the Systemised Self. A dual-evidence design is therefore proposed, combining subjective phenomenology with backend behavioural traces, experimental friction shocks, and cognitive reaction measures. Testable hypotheses, falsification criteria, four worked participant scenarios, and boundary conditions are provided to guide future empirical research and theoretically disciplined use.

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