From Transduction to Phase Transition: A Comparative Analysis of Procedural Ontologies in Gilbert Simondon and Paul Stillers

The twentieth century left philosophy a complex legacy. On one hand, there is Heidegger's critique of presence, and on the other, the tumultuous rise of the sciences of complexity. Their intersection has generated a demand for ontologies that could hold together becoming, nonlinearity, and openness to the future. A comparison of the two philosophers shows that while they both reject hylomorphism, their research focuses diverge. Simondon emphasizes transduction while maintaining connectivity, and individuation reveals itself as the immanent logic of the relationships between humans and their environment. Sillars, however, focuses on uncertainty. For him, a phase transition is the moment when any model inevitably misses something, and the consequences of such losses in a nonlinear world are impossible to predict in advance. The difference is particularly pronounced in the realm of neural networks. Simondon allows one to interpret machine learning as a concretization of technical essence. Sillars warns of the illusion of super-intelligence, pointing to the ontological emptiness of algorithmic models. Studying the ontologies of becoming in Simondon and Sillars cannot be done without a special tool. A methodological prism is needed that refuses the substantialist divide between subject and object. The foundation of the work is the unity of ontology, epistemology, and methodology, derived from the logic of processual thinking. Three complementary methods are employed. Conceptual analysis compares key concepts from Simondon's philosophy of individuation and Sillars's epistemology of complexity. Philosophical hermeneutics reconstructs the internal logic of their texts, converging in a critique of reductionism. Theoretical modeling allows for a comparison of both approaches and reveals their implications for understanding technical systems. The synthesis of transductive ontology and the epistemology of phase transitions opens the way for rethinking the philosophy of technology and modeling practices in the era of digital platforms and automated cognition. The former provides a language for describing the internal logic of the becoming of technical systems, their historicity, and their capacity for invention rooted in material-energy dynamics. The latter equips one with critical tools for analyzing boundaries, hierarchies, and incompressibility, reminding of the inevitable modesty of any knowledge about complex ensembles. Together, they form a normative ideal of an open model where technical knowledge does not suppress but articulates the metastability of being, transforming complexity from a threat into a resource for the joint individuation of humans, technology, and society.