Whilst the usefulness of the computational metaphor in many areas of psychology and neuroscience is clear, it has not gone unchallenged and in this article I will review a group of philosophical arguments that suggest either such unequivocal optimism in computationalism is misplaced – computation is neither necessary nor sufficient for cognition – or panpsychism (the belief that the physical universe is fundamentally composed of elements each of which is conscious) is true. I conclude by highlighting an alternative metaphor for cognitive processes based on communication and interaction. Relevance: This paper argues against computational accounts of mind and cognition, discussing Searle, Bishop and Penrose and suggesting a new metaphor for cognition based on interactions and communication. The new metaphor is sympathetic to modern post-symbolic, anti-representationalist, embodied, enactive accounts of cognition.

“Strong computationalism” holds that any suitably programmed computer instantiates genuine conscious mental states purely in virtue of carrying out a specific series of computations. The argument presented herein is a simple development of that originally presented in Putnam’s “Representation & Reality”, which if correct, has important implications for Turing machine functionalism and the prospect of “conscious” machines. In the paper, instead of seeking to develop Putnam’s claim that, “everything implements every finite state automata”, I will try to establish the weaker result that “everything implements the specific machine Q on a particular input set (x)”. Then, equating Q (x) to any putative AI program, I will show that conceding the “strong AI” thesis for Q (crediting it with mental states and consciousness) opens the door to a vicious form of panpsychism whereby all open systems, (e.g., grass, rocks, etc.), must instantiate conscious experience and hence that disembodied minds lurk everywhere. Relevance: This paper critiques the computational accounts of mind and cognition using a construction borrowed from Putnam.

Open peer commentary on the article “Sensorimotor Direct Realism: How We Enact Our World” by Michael Beaton. Upshot: Sensorimotor direct realism is too promiscuous in its account of sensation.

Excerpt: ‘Sensorimotor Theory’ offers a new enactive approach to perception that emphasises the role of motor actions and their effect on sensory stimuli. The seminal publication that launched the field is the target paper co-authored by J. Kevin O’Regan and Alva Noë and published in Behavioral and Brain Sciences (BBS) for open peer commentary in 2001. In the central argument of their paper, O’Regan and Noë suggest radically shifting the nexus of research in visual perception away from analysis of the raw visual patterns of stimulation, to refocus on the law-like changes in visual stimulation brought about as a result of an agent’s actions in the [light-filled] world. A key consequence of this change is a new way of characterising objects by the unique set of ‘sensorimotor correspondences’ that define the characteristic changes in objective appearance brought about by the agent-object interactions [in the world]. These characteristic correspondences relating the movement of any object relative to the agent define its sensorimotor dependencies [qua world]; an agents practical knowledge of these sensorimotor dependencies constitutes its visual experience. Thus in O’Regan and Noë’s sensorimotor theory, perhaps for the first time, we have a rich, testable, psychological (and philosophically grounded) theory that accounts for why our conscious experience of the world appears as it does. This is a significant achievement and one that, in our opinion, goes a long way to answering at least some of the hard problems of consciousness.

Purpose: To present an account of cognition integrating second-order cybernetics (SOC) together with enactive perception and dynamic systems theory. Methodology – The paper presents a brief critique of classical models of cognition then outlines how integration of SOC, enactive perception and dynamic systems theory can overcome some weaknesses of the classical paradigm. Findings: Presents the critique of evolutionary robotics showing how the issues of teleology and autonomy are left unresolved by this paradigm although their solution fits within the proposed framework. Implications: The paper highlights the importance of genuine autonomy in the development of artificial cognitive systems. It sets out a framework within which the robotic research of cognitive systems could succeed. Practical implications: There are no immediate practical implications but see research implications. Originality/value – It joins the discussion on the fundamental nature of cognitive systems and emphasises the importance of autonomy and embodiment. Relevance: This paper draws explicit links between second order cybernetics, enactivism and dynamic systems accounts of cognition.

The Chinese Room Argument purports to show that ‘syntax is not sufficient for semantics’; an argument which led John Searle to conclude that ‘programs are not minds’ and hence that no computational device can ever exhibit true understanding. Yet, although this controversial argument has received a series of criticisms, it has withstood all attempts at decisive rebuttal so far. One of the classical responses to CRA has been based on equipping a purely computational device with a physical robot body. This response, although partially addressed in one of Searle’s original contra arguments – the ‘robot reply’ – more recently gained friction with the development of embodiment and enactivism, two novel approaches to cognitive science that have been exciting roboticists and philosophers alike. Furthermore, recent technological advances – blending biological beings with computational systems – have started to be developed which superficially suggest that mind may be instantiated in computing devices after all. This paper will argue that (a) embodiment alone does not provide any leverage for cognitive robotics wrt the CRA, when based on a weak form of embodiment and that (b) unless they take the body into account seriously, hybrid bio-computer devices will also share the fate of their disembodied or robotic predecessors in failing to escape from Searle’s Chinese room.

Key words: deep brain stimulation, functional connectivity, external world, cochlear implant, rubber hand.

An information-processing paradigm in the brain is proposed, instantiated in an artificial neural network using biologically motivated temporal encoding. The network will locate within the external world stimulus the target memory, defined by a specific pattern of micro-features. The proposed network is robust and efficient. Akin in operation to the Swarm Intelligence paradigm, Stochastic Diffusion Search, it will find the best-fit to the memory with linear time complexity. Information multiplexing enables neurons to process knowledge as “tokens” rather than “types.” The network illustrates the possible emergence of cognitive processing from low level interactions such as memory retrieval based on partial matching. Relevance: This paper outlines the implementation of a new metaphor for cognition; a metaphor grounded upon communication rather than computation.

Excerpt: This special issue contains a selection of the papers presented at the international symposium entitled ‘Foundations of Enactive Cognitive Science’, which was held in Windsor, UK, in February 2012. In organizing this symposium, our explicit goal was to create the space for researchers attracted to the concept of enaction to discuss the research agenda(s) for what could be described as an alternative or an extension to the orthodox paradigm(s) in cognitive science. About 70 researchers represented the five continents, and a dozen of academic disciplines. More extensive proceedings of the event can be found at

Upshot: Albeit mostly supportive of our work, the commentaries we received highlighted a few points that deserve additional explanation, with regard to the notion of learning in our model, the relationship between our model and the brain, as well as the notion of anticipation. This open discussion emphasizes the need for toy computer models, to fuel theoretical discussion and prevent business-as-usual from getting in the way of new ideas.

Context: Constructivist approaches to cognition have mostly been descriptive, and now face the challenge of specifying the mechanisms that may support the acquisition of knowledge. Departing from cognitivism, however, requires the development of a new functional framework that will support causal, powerful and goal-directed behavior in the context of the interaction between the organism and the environment. Problem: The properties affecting the computational power of this interaction are, however, unclear, and may include partial information from the environment, exploration, distributed processing and aggregation of information, emergence of knowledge and directedness towards relevant information. Method: We posit that one path towards such a framework may be grounded in these properties, supported by dynamical systems. To assess this hypothesis, we describe computational models inspired from swarm intelligence, which we use as a metaphor to explore the practical implications of the properties highlighted. Results: Our results demonstrate that these properties may serve as the basis for complex operations, yielding the elaboration of knowledge and goal-directed behavior. Implications: This work highlights aspects of interaction that we believe ought to be taken into account when characterizing the possible mechanisms underlying cognition. The scope of the models we describe cannot go beyond that of a metaphor, however, and future work, theoretical and experimental, is required for further insight into the functional role of interaction with the environment for the elaboration of complex behavior. Constructivist content: Inspiration for this work stems from the constructivist impetus to account for knowledge acquisition based on interaction.

Key words: Stochastic diffusion search, clustering, multi-agent system, cognitivism.