On Reverse Engineering in the Cognitive and Brain Sciences

TL;DR

This paper critically examines the standard reverse engineering approach in cognitive and brain sciences, arguing that due to brain complexity, this method's core assumptions are flawed and should be reconsidered.

Contribution

It challenges the fundamental assumption that complex cognitive systems can be fully understood and duplicated through reverse engineering, proposing a need to rethink scientific methods in this field.

Findings

Reverse engineering's assumptions are questioned by recent findings.

The modeling relation by Robert Rosen is used to critique scientific analysis.

The paper suggests abandoning the idea that complex systems can be fully understood by reverse engineering.

Abstract

Various research initiatives try to utilize the operational principles of organisms and brains to develop alternative, biologically inspired computing paradigms and artificial cognitive systems. This paper reviews key features of the standard method applied to complexity in the cognitive and brain sciences, i.e. decompositional analysis or reverse engineering. The indisputable complexity of brain and mind raise the issue of whether they can be understood by applying the standard method. Actually, recent findings in the experimental and theoretical fields, question central assumptions and hypotheses made for reverse engineering. Using the modeling relation as analyzed by Robert Rosen, the scientific analysis method itself is made a subject of discussion. It is concluded that the fundamental assumption of cognitive science, i.e. complex cognitive systems can be analyzed, understood and duplicated by reverse engineering, must be abandoned. Implications for investigations of organisms and behavior as well as for engineering artificial cognitive systems are discussed.