Semiosis, Sense-Making and the Being of the Between: Reconciling Autopoietic Enactivism and Biosemiotics through Relational Biology

Matthew McTeigue

This talk will investigate the autopoietist’s theory of the continuity between life and mind under the auspices of a biosemiotic approach to enactivist philosophy of mind, with a view to resolve a deep-seated tension between the essence of life and mind (cognition). As proponents of the theory claim, where we find life, we find mind. Life and mind derive from the same set of organizational and functional properties, and those that define mind are an enriched version of those fundamental to life. In particular, it is those self-organizing features of mind which are enriched from those typifying life. The talk proceeds in a three-fold manner. Firstly, it queries the foundation of autopoietic theory to uncover the roots of the multi-varied criticisms levelled at the thesis. Secondly, it looks at the recent controversy between classical autopoietic theory and advocates of the free-energy principle and predictive processing theories, who contend autopoiesis fails to account for the anticipatory and future-oriented aspect of cognition. Thirdly, biosemiotic enactivism is shown to heal this disharmony by providing a more robust theory of autopoietic self-organization via Peirce and biosemiotics, not only more thoroughly grounded in the metaphysics of complex and self-organizing systems which underpin both the autopoietic and biosemiotics paradigm, but also through a demonstration of the sign as a unifying foundation of both autopoietic self-organization and meaning and anticipation. Finally, it will be argued that modelling biosemiosis under the auspices of autopoietic biology and anticipatory systems gives a far richer and nuanced picture of the dynamics of the sign simply unavailable to classical semioticians, and does justice to the prescience and insight of C.S Peirce. Ultimately, a biosemiotic contextualization of autopoiesis is touted as an attractive via media between enactivism and free-energy and predictive processing approaches.

[Slides from the lecture]