Commodity Labor, Contributory Labor, and the Human as Orchestration
Context
The concept of 'salvific labor', a disctinct contribution of the Christian medieval tradition, is sourced in From Modes of Production to the Resurrection of the Body, a presentation of the
- PhD Thesis: Suriano, Benjamin, "From Modes of Production to the Resurrection of the Body: A Labor Theory of Revolutionary Subjectivity & Religious Ideas" (2016). Dissertations (1934 -). 628. [1]
I have elaborated this in a Substack article:
- "Why Human (Contributive) Labor remains the creative principle of human society" .
https://4thgenerationcivilization.substack.com/p/why-human-contributive-labor-remains?u
The piece focuses on the medieval Christian vision of human work as a spiritual activity and explores "the salvific and ex-tropic implications" of this idea.
In short, the salvific nature of human labor, was undermined by the shift towards 'commodity labor' for sale, but it returning through the contributory nature of work in peer production. But how does AI affect this, as it can potentially remove a substantial amount of human work. The answer may be in the concept of 'orchestration'.
Consider it as an exploratory idea, and here are some excerpts to illustrate it below.
Discussion
Michel Bauwens
AI as a Civilizational Mediator Between the Human and the Non-Human:
"The emergence of artificial intelligence introduces a new dimension to the evolution of translocal institutions. Unlike diasporas, phyles, network states, or commons magisteria, AI is not itself a human community or a governance institution. Its significance lies elsewhere: in its capacity to mediate complexity.
Two converging developments help explain why AI may become a crucial component of future civilizational architectures.
The first concerns knowledge. The information age has dramatically expanded humanity’s capacity to produce, store, and circulate information. Scientific research, technical documentation, cultural production, economic data, and social communication now grow at rates that exceed the capacity of any individual—or indeed any institution—to synthesize. Humanity possesses unprecedented amounts of knowledge, yet faces increasing difficulty in creating coherent representations of that knowledge.
In this context, AI can be understood as a universal synthetic machine. Its role is not merely to retrieve information but to generate integrated representations of increasingly fragmented knowledge domains. As the volume of available information continues to expand, AI may become an indispensable infrastructure for maintaining civilizational intelligibility. It offers the possibility of continuously producing synthetic understandings from the growing ocean of distributed human knowledge.
The second challenge concerns the relationship between human societies and the larger living systems upon which they depend. Ecological regeneration, biodiversity preservation, climate stabilization, watershed management, material throughput, and energy transitions all involve forms of complexity that exceed direct human perception. Modern societies increasingly confront systems whose dynamics unfold across scales that are difficult for human institutions to comprehend, monitor, and coordinate.
Here AI may play a second and potentially even more important role. It can function as a mediator between the human and non-human worlds, at all scales, from the hyperlocal through the bioregional and the national and the continental, all the way to the planetarity scale: it is indeed a ‘cosmo-local’ mediator!
The issue is not that AI speaks for nature, nor that it replaces human judgment. Rather, it can help render visible processes that would otherwise remain largely invisible to human perception. Ecological feedback loops, biodiversity indicators, material and energy flows, climate dynamics, soil health, watershed conditions, and planetary boundaries can all be translated into forms that become intelligible within human deliberative processes. You may recall that I did a first mapping of these new human capacities before AI was a generalized technology, in our report, P2P Accounting for Planetary Survival, while we surveilled the new capacity of p2p and commons technology to be a ‘neguentropic’ (anti-entropic) force in our earlier report, The Thermodynamics of Peer Production.
In this sense, AI may become a bridge between two forms of complexity: the complexity of human knowledge and the complexity of living systems. It can help synthesize what humanity knows, while simultaneously helping humanity perceive the conditions that sustain life itself.
This suggests a distinctive role for AI within an emerging commons-oriented civilization. Its primary function would not be sovereignty, governance, or representation. Rather, it would contribute a new layer of collective intelligence capable of enhancing humanity’s capacity for sense-making across scales. I’m anticipating this problematique in two tentative and speculative research essays which I will later adapt for publication in this Substack:
Historically, civilizations have developed institutions for power, exchange, and knowledge transmission. The contemporary challenge may require a new cognitive layer capable of integrating knowledge across domains while facilitating meaningful interaction between human societies and the larger ecological systems within which they are embedded.
From this perspective, AI appears less as an autonomous actor than as a civilizational mediator. It becomes part of the infrastructure through which human communities, translocal institutions, and ecological systems can become mutually intelligible. If Network States address questions of distributed governance and Commons Magisteria address questions of stewardship, AI may address a complementary challenge: the creation of shared intelligibility in a world of increasing informational and ecological complexity.
(https://4thgenerationcivilization.substack.com/p/the-historical-evolution-of-translocal)
The Human as Orchestrator
(for more context, see the article from which this is excerpted: Differential AI Orchestration as Governance Augmentation
ISPCR:
"What is the human's role in this configuration? In the documentary record, the human is repeatedly described as performing four functions. First, choosing which model to ask, in which order, with which framing — what one might call the curation function. Second, arbitrating contradictions, which requires both technical judgement and willingness to override individual model outputs. Third, setting boundaries — “What we will NOT touch” — which the documentary record treats as a substantive governance act, often more important than what the work plan does include. Fourth, preserving burn-rate discipline: deciding when to stop iterating, which model cycles to skip, and when a partial answer is sufficient to act on. This is a real shift in the texture of governance work. The human in this configuration is not the primary producer of strategic cognition. Strategic cognition is produced by the ensemble. The human is the operator who decides which strategic cognition to act on, and which to discard. This is, in Bauwens's terminology, closer to the role of a steward of a commons than to the role of a chief executive. It is also, in Beer's terminology, closer to the role of S5 (identity / policy) than to the role of S3 (operational management); the human sets the boundary conditions within which the AI ensemble does the operational management work."