Open Questions about Time and Self-reference in Living Systems

TL;DR

This paper discusses the unique temporal and self-referential characteristics of living systems, proposing new theoretical frameworks to better model their self-modifying and creative nature across biological and cognitive sciences.

Contribution

It introduces the distinction between natural and representational time and suggests new modeling approaches for self-referential, self-modifying systems in living organisms.

Findings

Living systems operate with natural and representational time.

Self-reference enables memory, learning, and prediction.

New modeling directions include domain theory and self-modifying algorithms.

Abstract

Living systems exhibit a range of fundamental characteristics: they are active, self-referential, self-modifying systems. This paper explores how these characteristics create challenges for conventional scientific approaches and why they require new theoretical and formal frameworks. We introduce a distinction between 'natural time', the continuing present of physical processes, and 'representational time', with its framework of past, present and future that emerges with life itself. Representational time enables memory, learning and prediction, functions of living systems essential for their survival. Through examples from evolution, embryogenesis and metamorphosis we show how living systems navigate the apparent contradictions arising from self-reference as natural time unwinds self-referential loops into developmental spirals. Conventional mathematical and computational formalisms struggle to model self-referential and self-modifying systems without running into paradox. We identify promising new directions for modelling self-referential systems, including domain theory, co-algebra, genetic programming, and self-modifying algorithms. There are broad implications for biology, cognitive science and social sciences, because self-reference and self-modification are not problems to be avoided but core features of living systems that must be modelled to understand life's open-ended creativity.