Cognition arises from the dynamic interaction between an embodied agent and its environment, according to enactivism, while new mechanism explains cognition by identifying the organized components that underlie cognitive abilities. Although mechanistic explanations often focus on localizable, decomposable neural mechanisms that seem to conflict with enactivist views, this paper argues they are compatible because mechanistic explanations need not be narrow or reductive and can incorporate ideas like emergence and downward causation. Enactivist ideas may also guide mechanistic investigations. However, the two approaches diverge in assumptions about cognition's constitutive boundaries.
The mechanistic model of scientific explanation describes explanations as uncovering multi-level, organized components that make up a target phenomenon. Sensorimotor enactivism offers an account of perceptual experience as a skillful, interactive relationship between perceiver and world, not as an internal representation. While these two approaches could complement each other—mechanism explaining subpersonal components of the skillful interaction that enactivism identifies—two challenges arise. The representation challenge arises because implementing sensorimotor interaction seems to require cognitive representations, conflicting with enactivism's nonrepresentational stance. The reconstitution challenge occurs when mechanistic explanation redefines perceptual experience so its components become entirely organism-bound. The paper explores these tensions and possible solutions, clarifying the compatibility and learning opportunities between the two frameworks.
Plants inspire soft robotics through their non-centralized, modular architecture and highly plastic phenotype. A holistic approach to plant bioinspiration, drawing on plant intelligence and behavior, supports an enactivist perspective that emphasizes embodiment and autonomy. Enactivist autonomy concerns the dynamics of self-producing systems like plants that create a distinction between themselves and their environment, contrasting with a diluted notion of independent operability. This distinction is relevant for evaluating limitations on existing growing robots ("growbots") that depend on external energy and material. Plant-inspired robots serve as a case study for an enactivist approach to intelligence, highlighting non-zoological forms of intelligence embodied in self-organizing, autonomous systems.