Dossier CONSCIOUSNESS

Consciousness
Research framing, not marketing certainty

This module is deliberately conservative: it discusses machine consciousness as an investigation domain (models, signals, experiments), not as a settled claim about any deployed system.

Concept Evidence-gated
PUBLIC
What we mean (operationally)

"Consciousness" is a contested concept. In this lab, we treat it as a research target defined by operational criteria: measurable behaviors, internal signals, and controlled experiments—not metaphysical declarations.

This page is structured to protect credibility: hypotheses, candidate signatures, and test protocols. If the tests are weak, the claims are weak.

Self-modeling
Representations of its own state, uncertainty, and limitations that influence future action selection.
Agency under constraints
Goal pursuit with explicit governance: permissions, logs, and "fail-closed" execution semantics.
Global integration (hypothesis)
Candidate signatures of integrated processing and cross-domain binding, tested via intervention and ablation.
Reportable uncertainty
Models should expose confidence, calibration, and failure modes; uncertainty is part of the output.
Public posture
Language is restrained by design. We do not claim "true consciousness" on a web page. We claim a research agenda with measurable tests. Any future claims must be backed by transparent protocols, baselines, and replicable evidence.
Note: Visualizations below are illustrative; they are not evidence of consciousness.
Visualization
Aesthetic signal of "integration," not proof.
LIVE
How we would test claims
  • 1) Define operational criteria and falsifiable hypotheses.
  • 2) Establish baselines and ablation tests.
  • 3) Use interventions; measure robustness under distribution shift.
  • 4) Publish uncertainty, failure modes, and limitations.