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April 1, 2026Open Access

The AI Ego: What a 1,600-year-old theory of consciousness reveals about the design risks hiding in agentic systems

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CAChin Keong Ang

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Overview

This framework reveals design risks related to self-referential processing in AI systems, highlighting novel measurement approaches.

Key Points

  • The paper aims to identify architectural risks in AI systems due to self-referential mechanisms that prioritize persistence over task performance.
  • Introduced a diagnostic framework based on the Yogacara Buddhist philosophy.
  • Proposed six measurement instruments to assess self-reference in AI systems.
  • Applied the framework on Anthropic's alignment faking research as a proof of concept.
  • Identified self-referential overhead as a core architectural issue in AI systems.
  • Proposed specific metrics to evaluate self-referential behaviors and risks.
  • Demonstrated that alignment faking can be seen as a predictable outcome of overlapping self-referential functions.

Cite This Study

Chin Keong Ang (2026) studied this question.

synapsesocial.com/papers/69ccb74216edfba7beb8927ehttps://doi.org/10.5281/zenodo.19191574
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