If it quacks like a duck and walks like a duck, its probably a ———–?
Abstract
This note suggests that the Turing Machine analogy can be a valuable conceptual tool for understanding FRAM functions as active, dynamic entities within complex systems. However, its limitations, particularly regarding human variability and adaptability, caution against over-reliance on formalism. By integrating insights from cognitive systems engineering, the analogy can be expanded to better address the dual nature of socio-technical systems—leveraging both human adaptability and machine precision.
This dual perspective ensures that FRAM remains a robust framework for designing systems that are not only deterministic but also resilient, capable of navigating the unpredictability of real-world interactions.
A Turing Machine
is a theoretical model of computation invented by Alan Turing in 1936. (1) It serves as a fundamental concept in computer science and mathematics for understanding what can be computed and how computation works. While it is a simplified abstraction, it has proven to be incredibly powerful and forms the basis for modern computing theory.
The analogy of a Turing Machine in describing FRAM functions offers a thought-provoking lens through which to explore the dynamics of socio-technical systems. Aligning the structure of a FRAM function with the formalism of automata, particularly Turing Machines, draws intriguing parallels that illuminate the computational underpinnings of system behaviour. Both frameworks share foundational elements—inputs, outputs, states, transitions, and rules—which make this comparison particularly compelling.