The myth of optimality in human movement science

Abstract

The concept of optimality dominates contemporary human movement science, with researchers across biomechanics, motor control, and neuroscience routinely explaining observed behaviors as solutions that maximize or minimize objective functions. This paper critiques the pervasive application of optimality principles in human movement science. We argue that optimization frameworks mischaracterize biological systems for several reasons: (1) Evolution produces sufficient rather than optimal adaptations without foresight; (2) Biological systems serve multiple functions simultaneously with context-dependent prioritization; (3) Structure-function relationships co-evolve rather than optimize for fixed targets; (4) The fractal, multiscale nature of physiological signals makes traditional optimization mathematically meaningless—there are no well-defined minima or maxima in fractal landscapes; (5) Optimality models implicitly invoke a homunculus that selects optimization criteria; and (6) The concept is methodologically circular and unfalsifiable, as any behavior can be retroactively modeled as optimal for some function. Instead of this Cartesian illusion of optimality, we propose that human performance emerges as a dynamic, context-sensitive process across multiple scales. By breaking free from the optimization paradigm, movement science can develop more powerful explanatory frameworks that embrace the rich adaptive variability that defines true biological systems.