A Systems Theory for Today

A living, forkable attempt to build a systems theory adequate to the present — by designed disagreement.

GLOSSARY

Version: 0.1 · Status: Living (definitions to be argued, not assumed) · Last updated: Session 1

The author flagged three words as themselves subjects for debate: “understanding,” “today,” and “systems theory.” This glossary holds working definitions — deliberately provisional. Each is a placeholder the panel will contest and sharpen. Where the panel has already split on a definition, both readings are kept.

The three contested terms

“Systems theory”

Working definition: a framework that identifies the entities, relationships (couplings), and dynamics (feedback, delay, emergence) of some domain, such that the behavior of the whole is explained by the structure of the interactions rather than by the parts in isolation. The contest:

  • Narrow (scientific) reading: the transdisciplinary formal science of systems as such — open systems, feedback, self-organization, complex adaptive systems (Bertalanffy → cybernetics → complexity science). Rigorous, but often silent on meaning and value.
  • Broad (philosophical) reading: any total explanatory framework integrating nature, society, mind, history, and meaning (the sense used in the history document). Ambitious, but risks the totalizing pathologies the postmodernists warned of.
  • This project’s stance (provisional): we want the rigor of the narrow reading applied at the scope of the broad reading — while holding the result as a “proto-synthesis,” never a closed totality. Whether that is coherent is itself an open question (Round 5).

“Today”

Working definition: the condition of globally-networked, high-technology, late-modern society in roughly the 2010s–2020s — the era of the smartphone, planetary-scale platforms, the climate emergency, post-2008 political realignment, and generative AI. The contest:

  • Is “today” a genuine rupture (something new under the sun — Luhmann’s fully differentiated society, Zuboff’s surveillance capitalism, the first AI systems) or the acceleration of a long trend (modernity, capitalism, or the technological Gestell running to their conclusion)?
  • Whose “today”? The condition is globally uneven; a systems theory of “today” must say whether it describes the networked core, the whole planet, or a dominant logic that shapes even those outside it.
  • This project’s stance (provisional): “today” = the period in which the pace and coupling of human-built systems first decisively exceeded human adaptive and sense-making capacity at planetary scale. That is a claim, not a date — and it is Candidate Theory A’s central variable.

“Understanding”

Working definition: a grasp of a system sufficient to explain its behavior, anticipate (conditionally) how it will respond to intervention, and act within it with less illusion. The contest:

  • Explanatory understanding (why it works) vs predictive understanding (what it will do) vs practical/participatory understanding (how to live and act within it). A theory can have one without the others.
  • Must understanding be held in a single mind to count? The project’s wager is no — that a whole can be understood distributively, across models, communities, and tools, in a way no individual fully holds. This redefinition is doing a lot of work and must be defended (Round 5).
  • Does understanding require meaning? The old totalities gave not just explanation but a sense of one’s place and purpose. Systems theory typically supplies the first and not the second. Is a theory that explains everything but means nothing actually understanding? (This is the panel’s sharpest definitional fault line.)

Working vocabulary (systems terms used throughout)

  • Stock — an accumulation (e.g. atmospheric CO₂, trust, elite aspirants). Changes only through flows.
  • Flow — a rate that fills or drains a stock (emissions, trust-erosion, elite production).
  • Feedback loop — a circle of causation. Reinforcing (R): amplifies change (vicious/virtuous cycles). Balancing (B): resists change, seeks a goal.
  • Delay — a lag between cause and effect; long delays make systems oscillate and overshoot (climate’s defining feature).
  • Emergence — properties of the whole not present in the parts (a market price, a mood, a traffic jam).
  • Self-organization — order arising without external design (Prigogine’s dissipative structures; markets; ecosystems).
  • Autopoiesis — a system that continuously produces itself and its own boundary (Maturana/Varela; Luhmann applied it to society-as-communication).
  • Functional differentiation (Luhmann) — modern society split into self-referential subsystems (economy, law, science, art, politics, media), each with its own binary code, none able to directly steer the others.
  • Leverage point (Meadows) — a place to intervene in a system; ranked from weak (adjusting parameters) to strong (changing goals and paradigms).
  • Overshoot — a system driven past a limit by momentum and delay, then forced to correct, often by collapse (Meadows; Limits to Growth).
  • Computational irreducibility — the property that some systems have no shortcut: the only way to know their outcome is to run them. A hard limit on prediction.
  • Reflexivity — a system whose participants react to beliefs about it, so that theories about the system change the system (acute in social and financial systems).
  • Supernormal stimulus — an exaggerated version of a natural cue that hijacks a drive more strongly than the real thing (Tinbergen); the engineering principle behind the dopamine economy.
  • Hyperobject (Morton) — an entity so massively distributed in time and space that it can’t be perceived as a whole (climate change, the internet), only encountered in fragments.

Project-coined terms (provisional, from the candidate theories)

  • The Adaptation Gap — the widening distance between the complexity-and-speed of human-built systems and the adaptive-and-meaning-making capacity of the humans and institutions inside them. Candidate Theory A’s master variable. (Working name; alternatives: Coherence Collapse, the Complexity–Comprehension Gap, the Overwhelm.)
  • The Optimization Ecology / Autopoietic Capture — the condition in which markets, media, and technical systems have become self-reproducing optimizers that capture human drives (attention, dopamine, outrage, status) as fuel, increasingly running without human ends. Candidate Theory B’s mechanism.
  • The Commons of Sense-Making / Distributed Coherence — the proposition that a livable systems theory for today must be held as a living, plural, computationally-augmented commons rather than authored as a monograph. Candidate Theory C — and this project’s own form.

(All three names are placeholders. Naming is a Round-7 decision and remains open; the panel and the community may rename.)