Prigogine recognized in Turing's morphogenesis the same principle he discovered in far-from-equilibrium thermodynamics: near bifurcation, fluctuations that would be negligible under normal conditions become the determining factors of macroscopic behavior. Far from the bifurcation, the system is robust — small perturbations produce small effects. Near the bifurcation, robustness fails. The energy barriers separating alternative states shrink. Molecular noise, thermal jitter, individual decisions — all can determine which branch the system enters.
The principle applies to sociotechnical systems at the AI threshold with documented fidelity. Consider the printing press. The technology itself was necessary but not sufficient for the transformation that followed. The transformation depended on fluctuations: a Mainz goldsmith's investment decision, a particular printer's choice of vernacular Bibles over Latin scholarly texts, Luther's decision to nail theses to a church door. Each was a small perturbation in a system already far from equilibrium, and each was amplified into consequences that reshaped European civilization.
Segal's account of the AI moment documents a system at maximum sensitivity. The teacher who begins grading questions rather than answers. The manager who maintains pre-AI role definitions. The parent who models curiosity rather than anxiety. Each introduces a perturbation into a system near bifurcation. In a near-equilibrium economy, the individual decision would be absorbed by restoring forces. In a far-from-equilibrium economy, where the rules of value creation are being rewritten, the same decision can become a template — not because other actors deliberately imitate it, but because the dynamics of a far-from-equilibrium system amplify successful strategies disproportionately.
The consequence extends beyond the individual to the institutional level. The company that invests in its workforce rather than reduces headcount. The government that funds retraining now rather than deferring. The fluctuations accumulate, the amplification continues, and the macroscopic pattern — which branch of the bifurcation prevails — is determined by the aggregate of small choices whose scale is grotesquely disproportionate to their consequences. The responsibility is substantial and, in a certain sense, unfair: no one asked for this amplifying power. The physics of far-from-equilibrium systems does not distribute sensitivity according to preparedness or desire. It distributes it according to proximity to the bifurcation point.
The mathematical analysis of fluctuations near bifurcation was developed by Prigogine and his collaborators in the 1970s, building on earlier work by Haken on laser physics and by Nicolis on chemical kinetics. The key result was that near a bifurcation, the system's response to perturbation shifts from linear (proportional, damped) to nonlinear (amplified, potentially decisive).
Turing's 1952 paper on morphogenesis had already demonstrated the principle in biological pattern formation. Prigogine's contribution was to generalize it to thermodynamic systems and demonstrate its applicability across chemistry, biology, and the sociotechnical domains explored in his later collaborative work.
Sensitivity is regime-dependent. Near equilibrium, perturbations are damped; near bifurcation, they are amplified.
Fluctuations determine patterns. In systems with multiple stable states, the specific outcome depends on events too small to predict or measure.
Quality of attention beats quantity of effort. A small, well-directed perturbation can tip the system; a large, poorly directed one can fail to produce any macroscopic effect.
The individual matters most at bifurcation. The thermodynamic leverage of individual actors is disproportionate precisely at moments when the system is poised between alternatives.
Amplifying power is not chosen. The builder operating near bifurcation carries responsibility she did not seek, distributed by proximity to the threshold rather than by preparedness.