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arxiv: 2606.18288 · v2 · pith:RY4TEZJHnew · submitted 2026-06-12 · 💰 econ.GN · cs.AI· econ.TH· q-fin.EC

A Knowledge Theory of Capital:The Value of Natural and Artificial Intelligence, Volume 1

Jeffrey Gardiner This is my paper

Pith reviewed 2026-06-30 10:36 UTC · model grok-4.3

classification 💰 econ.GN cs.AIecon.THq-fin.EC
keywords knowledge capitaleconomic theoryartificial intelligencecapital accumulationknowledge governanceAdam Smithproductivityepistemic infrastructure
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The pith

Modern wealth depends not only on capital accumulation but on how productive knowledge is governed.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper extends Adam Smith's theory of labour, stock, and specialization to economies where productive capacity resides in software, data, models, routines, expertise, platforms, organizations, commons, and public epistemic infrastructure. It treats knowledge as becoming stock-like, mobile across forms, scalable, governable, recombinable, and imperfectly visible in accounting. The analysis centers on knowledge-bearing stock and tracks how it is generated, converted into governable form, deployed, improved through feedback, enclosed or shared, measured, impaired, and used as future input. It distinguishes embodied, disembodied, institutionalized, commons, and public knowledge forms while introducing concepts such as first conversion, cognitive enclosure, feedback capture, dark capital, and expected knowledge loss. The core claim is conditional and testable: outcomes for wealth turn on the specific governance of this knowledge stock.

Core claim

The paper claims that knowledge-bearing stock is the central object in modern economies, and that wealth depends not only on capital accumulation but on how productive knowledge is governed through its generation, conversion, deployment, feedback improvement, enclosure or sharing, measurement, impairment, and reuse as input.

What carries the argument

Knowledge-bearing stock, the productive capacity in software, data, models, routines, expertise, platforms, organizations, commons, and public epistemic infrastructure that can be converted, governed, and recombined.

If this is right

  • Governance choices on whether knowledge remains commons or becomes enclosed will directly shape the rate at which productive capacity expands.
  • Systems that fail to measure or capture feedback from knowledge use will systematically understate or impair future output.
  • Distinctions among knowledge forms make it possible to analyze why some knowledge scales while other knowledge remains embodied or localized.
  • Impairment through expected knowledge loss becomes a measurable drag on wealth comparable to physical depreciation.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The framework suggests testable metrics for how open versus proprietary AI models affect aggregate productivity when capital stocks are held constant.
  • It connects directly to questions of how public epistemic infrastructure alters the returns to private knowledge investment.
  • One extension would be to derive accounting adjustments that make knowledge-bearing stock visible in national accounts and test whether those adjustments improve growth forecasts.

Load-bearing premise

Knowledge can be usefully treated as stock-like, mobile across forms, scalable, governable, recombinable, and imperfectly visible in accounting, allowing distinctions between embodied, disembodied, institutionalized, commons, and public forms to structure analysis.

What would settle it

An empirical comparison of economies or sectors with matched physical capital stocks but measurably different knowledge governance regimes (for example, differing rates of cognitive enclosure or feedback capture) that shows no corresponding difference in productivity growth or wealth would falsify the central claim.

Figures

Figures reproduced from arXiv: 2606.18288 by Jeffrey Gardiner.

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read the original abstract

This volume develops a knowledge theory of capital for economies in which productive capacity increasingly resides in software, data, models, routines, expertise, platforms, organizations, commons, and public epistemic infrastructure. Beginning from Adam Smith's theory of labour, stock, specialization, and market extent, it asks what changes when knowledge becomes stock-like, mobile across forms, scalable, governable, recombinable, and imperfectly visible in accounting. The book introduces knowledge-bearing stock as the central object and analyses how it is generated, converted into governable form, deployed, improved through feedback, enclosed or shared, measured, impaired, and used as input to future production. It distinguishes embodied, disembodied, institutionalized, commons, and public knowledge forms and develops concepts such as first conversion, cognitive enclosure, feedback capture, dark capital, and expected knowledge loss. The argument is conditional and testable: modern wealth depends not only on capital accumulation, but on how productive knowledge is governed.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 1 minor

Summary. The manuscript develops a knowledge theory of capital by extending Adam Smith's concepts of labour, stock, specialization, and market extent to modern economies where productive capacity resides in software, data, models, routines, expertise, platforms, organizations, commons, and public epistemic infrastructure. It posits knowledge-bearing stock as the central object and examines its generation, conversion into governable form, deployment, improvement through feedback, enclosure or sharing, measurement, impairment, and use as input to future production. The work distinguishes embodied, disembodied, institutionalized, commons, and public knowledge forms while introducing concepts such as first conversion, cognitive enclosure, feedback capture, dark capital, and expected knowledge loss. The central claim is framed as conditional and testable: modern wealth depends not only on capital accumulation but on how productive knowledge is governed.

Significance. If the distinctions among knowledge forms and the associated processes can be shown to be non-circular and to yield operational, falsifiable implications, the framework could provide a coherent extension of classical capital theory to contemporary issues of AI, data governance, and epistemic infrastructure. The explicit conditional framing and positioning as preparatory for later testing are strengths that facilitate future empirical work.

major comments (1)
  1. [Abstract] Abstract: The definition of knowledge-bearing stock relies on the properties 'stock-like, mobile across forms, scalable, governable, recombinable, and imperfectly visible in accounting,' which are then used to structure the analysis of how such stock 'is generated, converted into governable form, deployed, improved through feedback, enclosed or shared, measured, impaired, and used as input.' This risks circularity, as the distinctions (embodied/disembodied/etc.) and processes presuppose the very mobility, governability, and recombinability they are intended to explain.
minor comments (1)
  1. [Abstract] Abstract: Several novel terms (first conversion, cognitive enclosure, feedback capture, dark capital, expected knowledge loss) are introduced without even brief parenthetical characterizations, which reduces immediate accessibility.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the careful reading and constructive feedback. The concern about potential circularity in the abstract is noted, and we address it directly below. The manuscript's conditional framing remains unchanged.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The definition of knowledge-bearing stock relies on the properties 'stock-like, mobile across forms, scalable, governable, recombinable, and imperfectly visible in accounting,' which are then used to structure the analysis of how such stock 'is generated, converted into governable form, deployed, improved through feedback, enclosed or shared, measured, impaired, and used as input.' This risks circularity, as the distinctions (embodied/disembodied/etc.) and processes presuppose the very mobility, governability, and recombinability they are intended to explain.

    Authors: We agree the abstract phrasing risks suggesting circularity. The properties are intended as empirically observed characteristics of knowledge assets in contemporary economies (extending Smith's stock concept), which then motivate analysis of governance processes. To remove any appearance of circular reasoning, we will revise the abstract to first characterize knowledge-bearing stock via its stock-like and mobile properties, then separately describe the processes these properties enable. The distinctions among forms will be presented as derived from these properties rather than presupposed. This change will be made in the revised manuscript. revision: yes

Circularity Check

0 steps flagged

No significant circularity; framework is definitional but conditional and non-derivational

full rationale

The manuscript is a conceptual extension of Smith's framework to knowledge-bearing stock, introducing distinctions and processes as analytical tools rather than deriving predictions from equations or fitted parameters. The central claim is explicitly conditional and positioned as preparatory for testing, with no load-bearing steps that reduce by construction to self-defined inputs, self-citations, or renamed empirical patterns. The abstract and description contain no equations, uniqueness theorems, or ansatzes that presuppose the target results. This is the normal case of a self-contained conceptual analysis without the enumerated circularity patterns.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 6 invented entities

The paper rests on domain assumptions about the nature of knowledge and introduces multiple new entities without independent evidence or formal derivations; counts here measure what is postulated rather than derived.

axioms (1)
  • domain assumption Knowledge becomes stock-like, mobile across forms, scalable, governable, recombinable, and imperfectly visible in accounting when productive capacity resides in software, data, models, routines, expertise, platforms, organizations, commons, and public epistemic infrastructure.
    Foundational premise stated in the abstract that enables the entire analysis.
invented entities (6)
  • knowledge-bearing stock no independent evidence
    purpose: Central object of analysis for generation, conversion, deployment, improvement, enclosure, measurement, and impairment of knowledge
    New postulated entity introduced without external validation or falsifiable handle.
  • first conversion no independent evidence
    purpose: Process by which knowledge is generated or converted into governable form
    Invented term with no independent evidence provided.
  • cognitive enclosure no independent evidence
    purpose: Mechanism for enclosing or sharing knowledge
    Invented term with no independent evidence provided.
  • feedback capture no independent evidence
    purpose: Process of improving knowledge through feedback
    Invented term with no independent evidence provided.
  • dark capital no independent evidence
    purpose: Impaired or invisible knowledge capital
    Invented term with no independent evidence provided.
  • expected knowledge loss no independent evidence
    purpose: Measurement or expectation of knowledge impairment
    Invented term with no independent evidence provided.

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