Hybrid Evolution Preprint
Preprint and following book of Hybrid Evolution describe a relational model of the development of humans and technological systems, particularly artificial intelligence, as distinct yet interrelated systems.
At its core are the epistemic coprocessor, interaction architectures, feedback processes, and cultural future imaginaries that shape how cognitive, social, and technological structures co-evolve and influence one another.
Generative systems are not understood as autonomous agents or mere tools, but as epistemic co-processors: structuring instances that compute probabilities while humans assign meaning.
The approach deliberately distinguishes itself from:
- fusion-based and transhumanist models
- purely instrumental tool or assistance paradigms
- as well as classical augmentation approaches
Instead, Hybrid Evolution focuses on stable forms of interaction that preserve system boundaries without dissolving the distinct roles of human and system.
The term serves as a conceptual framework for research, essays, and book projects concerned with the long-term stability and design of human–AI interaction.
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DOI:
10.5281/zenodo.19257680
Zenodo:
to Zenodo-Site
Hybrid Evolution Research Series
The Hybrid Evolution Research Series is an ongoing interdisciplinary research program examining the evolving interaction between human cognition and increasingly capable artificial intelligence systems.
The series focuses on structural and dynamic aspects of human–AI interaction, including cognitive state dynamics, epistemic attribution, interaction stability, and the emergence of hybrid cognitive system in which human reasoning processes interact with probabilistic machine learning models.
Rather than approaching these phenomena from a single disciplinary perspective, the program integrates insights from cognitive science, human–computer interaction, philosophy of information, and systems theory. A central goal is to develop conceptual frameworks that help describe how human cognitive processes reorganize when they become tightly coupled with AI systems.
Publications within the series explore different aspects of this broader research agenda, including interaction drift in long dialogues, mode misclassification in extended human–AI collaboration, epistemic attribution in latent-space systems, and neurocognitive adaptation in hybrid intelligence contexts.
Current publications include the book Symbiotic Intelligence und Mensch-KI-Interaktion (companion page) as well as various papers and research works available on SSRN, Zenodo and the Open Science Framework (OSF).