Algorithmic-Necessity-of-Agency

In the paper's words

This treatise presents a comprehensive theoretical synthesis resolving the dialectic between the subjective experience of free will and the objective reality of a superdeterministic universe. By integrating the foundational principles of quantum mechanics—specifically the violation of statistical independence in Bell’s Theorem—with the functional neuroanatomy of the left-hemisphere interpreter, we propose that the “illusion of choice” is not a metaphysical error, but a mandatory biological heuristic. We demonstrate that the human brain, constrained by strict thermodynamic limits (E ≥ kT ln 2), utilizes the concept of agency as a lossless data-compression algorithm to process the infinite causal variables of a deterministic environment.

The abstract, verbatim, and its opening sentence is the claim. Every line below is quoted from the text.

Numbers it reports

1. The human brain consumes roughly 20 watts of power, placing a strict thermodynamic limit defined by Landauer’s principle, $E \ge kT \ln 2$, on the amount of information it can erase or process.

   from Chapter 1: The

2. Evolution did not equip the human brain with the sensory bandwidth to measure these micro-variables, as the bit-rate of conscious processing is limited to approximately 50 bits per second.

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3. Evolution engineered this abstraction because the conscious mind possesses a strictly limited bandwidth, typically measured at around 50 bits per second, and would instantly crash if forced to process the raw, uncompressed data of physical reality.

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4. However, relying on fundamental randomness provides no evolutionary advantage; a predictive system requires $P(future|past) \gt 0.5$ to justify the caloric cost of neural computation.

   from Chapter 1: The

5. 3: The Computational Cost of Causal Processing 3.1 Infinite Causal Variables The concept of infinite causal variables describes the boundless web of physical interactions required to produce even the simplest macroscopic event.

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6. 3.6 The Fatal Cost of Raw Determinism The fatal metabolic cost of raw determinism refers to the catastrophic biological failure that would occur if the human brain attempted to process the universe without the illusion of choice.

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How it is done

1. By integrating the foundational principles of quantum mechanics—specifically the violation of statistical independence in Bell’s Theorem—with the functional neuroanatomy of the left-hemisphere interpreter, we propose that the “illusion of choice” is not a metaphysical error, but a mandatory biological heuristic.

   from ABSTRACT

2. Superdeterminism; Left-Hemisphere Interpreter; Quantum Entanglement; Bell’s Theorem; Evolutionary Game Theory; Neuroplasticity; Data Compression Heuristics; Agency Bypass; Deterministic Ethics; Systemic Entropy; Nash Equilibrium; Cognitive Dissonance.

   from KEYWORDS

3. 1.2 Bell’s Theorem and the Local Hidden Variable Loophole Bell’s Theorem stands as one of the most profound mathematical proofs in the history of physics, establishing a strict inequality for any theory relying on local hidden variables.

   from Chapter 1: The

4. Observing these adaptations provides undeniable proof that the subjective feeling of a unified will is merely the result of high-speed data transfer, not a metaphysical soul.

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What would falsify it

1. If a hominid believed $P(survival) = 1$ or $0$ regardless of effort, the dopamine reward prediction error signal $\delta = r + \gamma V(s_{t+1}) - V(s_t)$ would collapse.

   from Chapter 1: The

2. If the brain didn’t feel ownership, it wouldn’t expend energy on prediction.

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3. Evolution demanded this high level of internal consistency because an organism that cannot predict its own future behavior based on a stable past cannot survive in a complex environment.

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Where the claim stops

1. However, relying on fundamental randomness provides no evolutionary advantage; a predictive system requires $P(future|past) \gt 0.5$ to justify the caloric cost of neural computation.

   from Chapter 1: The

2. If the universe were truly random at its core, the brain’s predictive coding algorithms, which minimize variational free energy $F = -\ln P(o|m) + D_{KL}[Q(s)||P(s|o,m)]$, would ultimately fail.

   from Chapter 1: The

3. Processing environments with high degrees of uncertainty requires massive amounts of caloric energy to maintain multiple predictive models simultaneously.

   from Chapter 1: The

Where to read

1. A45,951 words · 200 min