Xabier Barandiaran

The performance of complex motor and craft skills is a norm-governed process, reliant on an agent’s sensitivity to standards of correct and incorrect performance. Whilst norm-governed practical skills tend to be understood in terms of social norms, this paper proposes an alternative, pluralistic perspective, which recognises socially underdetermined normative dimensions in practical skills. Specifically, drawing on the enactive approach, we argue that sensorimotor norms, understood as situated patterns of sensorimotor organisation, constitute skill-guiding normative standards which are not fully captured by social rules and expectations. We demonstrate the value of this pluralistic perspective for the explanation of skill-related norms by showing how it delivers a better interpretation of a recent proposal about the skill-based evolution of social norms, namely Jonathan Birch’s ‘skill hypothesis’. Building on this discussion, we then elaborate on the explanatory benefits of our proposal for making sense of cases of norm change and innovation in the context of practical skills and highlight its potential to address challenges connected to the origins and development of social norms. We conclude that a pluralistic perspective which takes account of both sensorimotor and social norms is better suited to explain essential features of norm-governed motor and craft skills than a view which limits itself to the consideration of social norms.

The concept of autonomy, as the capacity of a system to govern itself according to its own normativity, is central to modernity. Its theoretical significance spans across various scientific and philosophical fields. Traditionally, however, autonomy has been conceived as arising within the boundaries attributed to the individual in an abstract, internalist and self-sufficient manner. During the last decades, this conception has been challenged at different scales and requires a revision that crosses the boundaries of the individual and takes into account the material embeddedness, open interactivity, and deep interdependency of natural and social phenomena. We propose that autonomous systems are better understood as emerging-from and depending-on different scales of interactivity, collectivity, extensionality, environmentality, and through the lenses of integrativity and sustainability. This updated approach we call Outonomy.

Traditionally, autonomy has been perceived through the lens of individualism and internalism, a view increasingly challenged by contemporary philosophical approaches, as well as by the context of global sustainability. Environmental challenges underline the need to shift from Earth-imposed limits to social-ecological limitations to achieve autonomy, democracy, and sustainability. In the realm of sustainability sciences, the concept of social-ecological systems has been developed to explore the interdependencies between humans and their environments. Despite the significance of autonomy in discussions around sustainability, its exploration within this field remains limited. This chapter aims to discuss the potential contribution of the concept of outonomy for social-ecological systems and the planetary scale and, conversely, to open up the concept of autonomy to planetary-ecological dependencies.

In this chapter, we briefly present different visions of the relationships between technology and autonomy. We accomplish this by a historical and (partly) dialectical exploration of three positions. We start with the modern thesis by which autonomous humans instrumentalize tools and techniques for their own benefit and self-determination. Next, we address the antithesis: the notion that technological systems have become autonomous, subordinating people to their own self-maintenance. Finally, we explore a synthetic position, which underlines that the only space for autonomy in a technologically mediated world is a technopolitical autonomy that takes the individual beyond itself, back to the ontotechnical constitution of its being, and forward into a personal and collective, ethical and political, participation in its becoming.

In this paper we argue that radically embodied approaches to cognition can be expanded to show that: (a) our sensorimotor engagements with technical objects can be normatively shaped in a direct manner (i.e. not necessarily involving symbolic processes), and that (b) this normativity is not only anchored in the agent but also partially supported by technical objects themselves. We depart from the enactive reinterpretation of Piagetian sensorimotor schemes and his theory of equilibration to establish how both agent-sided and environment-sided support structures (including artefacts) contribute to the autonomous self-maintenance of sensorimotor networks. We will then introduce technical behaviour as a regulatory transformation of the environment enacted to equilibrate certain sensorimotor structures. We will defend that technical objects, as products of technical behaviour, sediment these normative constraints in their material structure. Then, through the dynamics of assimilation and accommodation, we schematize how different scenarios give rise to canonical or alternative uses in the encounter of agents with artefacts. Finally, we will offer a complexification of the normative entanglement of objects and agents by introducing the sociohistorical notion of activity as developed within Activity Theory approaches as collectively articulating individual actions. Based on all of this, we will have offered a picture of technical objects as also radically embodying normative layers, without submitting to an overly-deterministic picture of artefacts as rigidly prescribing behaviour, or to the purely symbolic or culturalist interpretation of them.

This paper investigates the ontological characterization of Large Language Models (LLMs) like ChatGPT. Between inflationary and deflationary accounts, we pay special attention to their status as agents. This requires explaining in detail the architecture, processing, and training procedures that enable LLMs to display their capacities, and the extensions used to turn LLMs into agent-like systems. After a systematic analysis we conclude that a LLM fails to meet necessary and sufficient conditions for autonomous agency in the light of embodied theories of mind: the individuality condition (it is not the product of its own activity, it is not even directly affected by it), the normativity condition (it does not generate its own norms or goals), and, partially the interactional asymmetry condition (it is not the origin and sustained source of its interaction with the environment). If not agents, then… What are LLMs? We argue that ChatGPT should be characterized as an interlocutor or linguistic automaton, a library-that-talks, devoid of (autonomous) agency, but capable to engage performatively on non-purposeful yet purpose-structured and purpose-bounded tasks. When interacting with humans, a “ghostly” component of the human-machine interaction makes it possible to enact genuine conversational experiences with LLMs. Despite their lack of sensorimotor and biological embodiment, LLMs textual embodiment (the training corpus), digital extended interface embodiments, and resource-hungry computational embodiment, significantly transform existing forms of machine automatism and human agency. Beyond assisted and extended agency, the LLM-human coupling can produce midtended forms of agency, closer to the production of intentional agency than to the extended instrumentality of any previous technologies.

This paper critically analyses the “attention economy” within the framework of cognitive science and techno-political economics, as applied to both human and machine interactions. We explore how current business models, particularly in digital platform capitalism, harness user engagement by strategically shaping attentional patterns. These platforms utilize advanced AI and massive data analytics to enhance user engagement, creating a cycle of attention capture and data extraction. We review contemporary (neuro)cognitive theories of attention and platform engagement design techniques and criticize classical cognitivist and behaviourist theories for their inadequacies in addressing the potential harms of such engagement on user autonomy and wellbeing. 4E approaches to cognitive science, instead, emphasizing the embodied, extended, enactive, and ecological aspects of cognition, offer us an intrinsic normative standpoint and a more integrated understanding of how attentional patterns are actively constituted by adaptive digital environments. By examining the precarious nature of habit formation in digital contexts, we reveal the techno-economic underpinnings that threaten personal autonomy by disaggregating habits away from the individual, into an AI managed collection of behavioural patterns. Our current predicament suggests the necessity of a paradigm shift towards an ecology of attention. This shift aims to foster environments that respect and preserve human cognitive and social capacities, countering the exploitative tendencies of cognitive capitalism.

Teleosemantics explains meaning by appealing to the biological norms that make error possible, but most work in the field still anchors those norms in evolutionary “selected‐effect” functions. We develop an organismic alternative grounded in the self-maintenance of autonomous systems. Building on sensorimotor theory and enactivism, we reconceptualise goals as second-order constraints—attractors in a dynamic sensorimotor field—and show how they are nested into a heterarchy of means–end relations connecting global self‑maintenance of the sensorimotor organization and identity of system with the most basic sensorimotor coordinations. Drawing on this framework, we identify the minimal necessary requirements for genuine teleological behaviour: 1. Initiation that individuates an action in relation to a goal, 2. Modulatory execution that adaptively compensates perturbations or deploys alternative strategies in relation to the goal, and 3. Meaningful termination through successful acknowledgment and transition, goal-sensitive persistence, or coherent abandonment. We locate normativity and error in the dynamic presuppositions among sensorimotor schemes and goals: failure manifests as incoordination within, or across, goal branches. We finally illustrate our account with a detailed analysis of the well known A-not-B error in psychology, showing how infants meet our teleological criteria while revealing incoordination as tension breakdowns inside a heterarchy of goals and sensorimotor schemes. Teleological behaviour, therefore, is the management of tensions and dynamic presuppositions within the goal heterarchy, not a chain of mechanical causes, thus delivering a naturalised notion of purposiveness that opens up an alternative route to teleosemantics beyond evolutionary selection.

In this paper we argue that radically embodied approaches to cognition can be expanded to show that: a) our sensorimotor engagements with technical objects can be normatively shaped in a direct manner (i.e. not necessarily involving symbolic processes), and that b) this normativity is not only anchored in the agent but also partially supported by technical objects themselves. We depart from the enactive reinterpretation of Piagetian sensorimotor schemes and his theory of equilibration to establish how both agent-sided and environment-sided support structures (including artefacts) contribute to the autonomous self-maintenance of sensorimotor networks. We will then introduce technical behaviour as a regulatory transformation of the environment enacted to equilibrate certain sensorimotor structures. We will defend that technical objects, as products of technical behaviour, sediment these normative constraints in their material structure. Then, through the dynamics of assimilation and accommodation we schematize how different scenarios give rise to canonical or alternative uses in the encounter of agents with artefacts. Finally, we will offer a complexification of the normative entanglement of objects and agents by introducing the sociohistorical notion of activity as developed within Activity Theory approaches as collectively articulating individual actions. Based on all of this, we will have offered a picture of technical objects as also radically embodying normative layers, without submitting to an overly-deterministic picture of artefacts as rigidly prescribing behaviour, or to the purely symbolic or culturalist interpretation of them.

We suggest that the influence of biology in ‘biologically inspired robotics’ can be embraced at a deeper level than is typical, if we adopt an enactive approach that moves the focus of interest from how problems are solved to how problems emerge in the first place. In addition to being inspired by mechanisms found in natural systems or by evolutionary design principles directed at solving problems posited by the environment, we can take inspiration from the precarious, self-maintaining organization of living systems to investigate forms of cognition that are also precarious and self-maintaining and that thus also, like life, have their own problems that must be be addressed if they are to persist. In this vein, we use a simulation to explore precarious, self-reinforcing sensorimotor habits as a building block for a robot's behavior. Our simulations of simple robots controlled by an Iterative Deformable Sensorimotor Medium demonstrate the spontaneous emergence of different habits, their re-enactment and the organization of an ecology of habits within each agent. The form of the emergent habits is constrained by the sensory modality of the robot such that habits formed under one modality (vision) are more similar to each other than they are to habits formed under another (audition). We discuss these results in the wider context of: (a) enactive approaches to life and mind, (b) sensorimotor contingency theory, (c) adaptationist vs. structuralist explanations in biology, and (d) the limits of functionalist problem-solving approaches to (artificial) intelligence.

According to the traditional nomological-deductive methodology of physics and chemistry [Hempel and Oppenheim, 1948], explaining a phenomenon means subsuming it under a law. Logic becomes then the glue of explanation and laws the primary explainers. Thus, the scientific study of a system would consist in the development of a logically sound model of it, once the relevant observables (state variables) are identified and the general laws governing their change (expressed as differential equations, state transition rules, maximization/minimization principles,. . . ) are well determined, together with the initial or boundary conditions for each particular case. Often this also involves making a set of assumptions about the elementary components of the system (e.g., their structural and dynamic properties) and modes of local interaction. In this framework, predictability becomes the main goal and that is why research is carried out through the construction of accurate mathematical models. Thus, physics and chemistry have made most progress so far by focusing on systems that, either due to their intrinsic properties or to the conditions in which they are investigated, allow for very strong simplifying assumptions, under which, nevertheless, those highly idealized models of reality are deemed to be in good correspondence with reality itself. Despite the enormous success that this methodology has had, the study of living and cognitive phenomena had to follow a very different road, because these phenomena are produced by systems whose underlying material structure and organization do not permit such crude approximations. Seen from the perspective of physics or chemistry, biological and cognitive systems are made of an enormous number of parts or elements interacting in non-linear and selective ways, which makes very difficult their tractability through mathematical models. In addition, many of those interacting elements are hierarchically organized, in a way that the “macroscopic” (observable) parts behave according to rules that cannot be, in practice, derived from simple principles at the level of their “microscopic” dynamics..

The notion of malfunction is critical to biological explanation. It provides a test-bed for the normative character of functional attribution. Theories of biological functioning must permit traits to operate but, at the same time, be judged as malfunctioning (in some naturalized, non-arbitrary sense). Whereas malfunctioning has attracted most attention and discussion in evolutionary etiological approaches, systemic and organizational ones have been less discussed. The most influential of the organizational approaches (by Saborido, Moreno and Mossio) takes a dual-order approach to malfunctions, as a set of functions that fit first-order constitutive norms but fail to obey second-order regulatory ones. We argue that this conception is unnecessarily complicated (malfunctions do not need to arise as a result of two conflicting orders of norms) and too narrow (it excludes canonical cases of malfunctioning). We provide an alternative organizational account grounded on viability theory. The dynamics of the traits that constitute an organism define the normative field of its viability space: sugar must be replaced at certain rate, blood must be pumped at a certain pace, etc. A trait operates normatively when its effects on the viability space correlate positively with the normative field. Three senses of dysfunctionality might be distinguished: subfunctional operations are those that positively correlate with the normative field but quantitatively fail to match the required speed; malfunctional operations are those that do not positively correlate with the normative field; and, nonfunctional traits either don’t operate at all or operate with null effect on the normative field.

This paper introduces the concept of “generative midtended cognition”, that explores the integration of generative AI technologies with human cognitive processes. The term “generative” reflects AI’s ability to iteratively produce structured outputs, while “midtended” captures the potential hybrid (human-AI) nature of the process. It stands between traditional conceptions of _in_tended creation, understood as steered or directed from with_in_, and _ex_tended processes that bring exo-biological processes into the creative process. We examine the working of current generative technologies (based on multimodal transformer architectures typical of large language models like ChatGPT) to explain how they can transform human cognitive agency beyond what the conceptual resources of standard theories of extended cognition can capture. We suggest that the type of cognitive activity typical of the coupling between a human and generative technologies is closer (but not equivalent) to social cognition than to classical extended cognitive paradigms. Yet, it deserves a specific treatment. We provide an explicit definition of _generative midtended cognition_ in which we treat interventions by AI systems as constitutive of the agent’s intentional creative processes. Furthermore, we distinguish two dimensions of generative hybrid creativity: 1. Width: captures the sensitivity of the context of the generative process (from the single letter to the whole historical and surrounding data), 2. Depth: captures the granularity of iteration loops involved in the process. Generative midtended cognition stands in the middle depth between _conversational_ forms of cognition in which complete utterances or creative units are exchanged, and micro-cognitive (e.g. neural) subpersonal processes. Finally, the paper discusses the potential risks and benefits of widespread generative AI adoption, including the challenges of authenticity, generative power asymmetry, and creative boost or atrophy.

In recent years, (autonomy-centered) enactivism has been used to provide an integrative and relational account of mental conditions. A significant advancement lies in its naturalized and pluralistic treatment of normativity, which transcends traditional objectivist and normativist dichotomies. This article explores the varieties of normativity within this paradigm and their implications for understanding mental conditions. We address purported challenges associated with the integration of social normativity into the enactive naturalistic framework of cognition, particularly concerning mental conditions. Drawing upon the distinction between the constitution problem and the status problem, we conceptualize mental conditions as intersubjectively constituted with an intersubjectively negotiated status. Adopting a participatory sense-making perspective, we address three challenges posed by social movements: (1) Hermeneutical dilemmas related to the ontological openness of mental health categories. (2) The difficulties and urgency to mitigate epistemic injustices. (3) The complex attribution of (social) responsibility in psychological wellbeing. In conclusion, this perspective prompts a reevaluation of epistemological assumptions, advocating for a second-person and engaged perspective on mental conditions.

We offer a critical review of the concept of neural information, as received within mainstream neuroscience from Artificial Intelligence. This conception of information is constructed as a conditional probability of a stimulus given a certain neural activation, a correlation that cannot be accessed by the organism and fails to explain its causal organization. We reconstruct an alternative conception of neural information: a pattern of signals that is selected by the organism (as an autonomous system) to contribute to its self-maintenance in virtue of its correlation with external conditions, a correlation that might further be evaluated by the very system.

This Open Access book explains the philosophy, design principles, and community organization of Decidim and provides essential insights into how the platform works. Decidim is the world leading digital infrastructure for participatory democracy, built entirely and collaboratively as free software, and used by more than 500 institutions with over three million users worldwide. The platform allows any organization (government, association, university, NGO, neighbourhood, or cooperative) to support multitudinous processes of participatory democracy. In a context dominated by corporate-owned digital platforms, in the era of increasing social structuring via Artificial Intelligence, Decidim stands as a public or community owned platform for collective human intelligence. Yet, the project is much more than its technological features. Decidim is in itself a crossroad of the various dimensions of the networked society, a detailed practical map of its complexities and conflicts. Theauthors distinguish three general dimensions of the project: (1) the political - shedding light on the democratic model that Decidim promotes and its impact on public policies and organizations, (2) the technopolitical - explaining how this technology is democratically designed and managed to produce and protect certain political effects, and (3) the technical - presenting the conditions of production, operation, and success of the project. This book systematically covers those three levels in an academically sound, technologically consistent, and politically innovative manner. Serving as a useful resource and handbook for the use of Decidim, it will not only appeal to students and scholars interested in participatory and digital democracy but also to professionals, policy-makers, and a wider audience interested in learning more about the Decidim platform.

Learning to perceive is faced with a classical paradox: if understanding is required for perception, how can we learn to perceive something new, something we do not yet understand? According to the sensorimotor approach, perception involves mastery of regular sensorimotor co-variations that depend on the agent and the environment, also known as the “laws” of sensorimotor contingencies (SMCs). In this sense, perception involves enacting relevant sensorimotor skills in each situation. It is important for this proposal that such skills can be learned and refined with experience and yet up to this date, the sensorimotor approach has had no explicit theory of perceptual learning. The situation is made more complex if we acknowledge the open-ended nature of human learning. In this paper we propose Piaget’s theory of equilibration as a potential candidate to fulfill this role. This theory highlights the importance of intrinsic sensorimotor norms, in terms of the closure of sensorimotor schemes. It also explains how the equilibration of a sensorimotor organization faced with novelty or breakdowns proceeds by re-shaping pre-existing structures in coupling with dynamical regularities of the world. This way learning to perceive is guided by the equilibration of emerging forms of skillful coping with the world. We demonstrate the compatibility between Piaget’s theory and the sensorimotor approach by providing a dynamical formalization of equilibration to give an explicit micro-genetic account of sensorimotor learning and, by extension, of how we learn to perceive. This allows us to draw important lessons in the form of general principles for open-ended sensorimotor learning, including the need for an intrinsic normative evaluation by the agent itself. We also explore implications of our micro-genetic account at the personal level.

According to the sensorimotor approach, perception is a form of embodied know-how, constituted by lawful regularities in the sensorimotor flow or in sensorimotor contingencies (SMCs) in an active and situated agent. Despite the attention that this approach has attracted, there have been few attempts to define its core concepts formally. In this paper, we examine the idea of SMCs and argue that its use involves notions that need to be distinguished. We introduce four distinct kinds of SMCs, which we define operationally. These are the notions of sensorimotor environment (open-loop motor-induced sensory variations), sensorimotor habitat (closed-loop sensorimotor trajectories), sensorimotor coordination (reliable sensorimotor patterns playing a functional role), and sensorimotor strategy (normative organization of sensorimotor coordinations). We make use of a minimal dynamical model of visually guided categorization to test the explanatory value of the different kinds of SMCs. Finally, we discuss the impact of our definitions on the conceptual development and empirical as well as model-based testing of the claims of the sensorimotor approach.

The current disruption of ecosystems and climate systems can be likened to an increase in entropy within our planet. This concept is often linked to the second law of thermodynamics, which predicts a necessary rise in entropy resulting from all material and energy-related processes, including the intricate organisation of living systems. Consequently, discussions surrounding the ongoing crisis commonly carry an underlying sense of fatalism when referencing thermodynamic principles. In this study, we explore how the understanding of life has been harmonized with thermodynamics to show that entropy production is a consequence of heightened complexity in life rather than its breakdown. Furthermore, it is crucial to perform a thermodynamic analysis of the Earth system as a whole to dispel fatalistic assumptions. The extremum principles linked to thermodynamics do not foretell the precise evolution of complex organisations but rather set the thermodynamic boundaries associated with their development. Ultimately, treating the Earth system as an integrated autonomous entity in which life and human societies play pivotal roles is essential for charting a sustainable path forward for humanity. Understanding how to contribute to thermodynamic states that are more conducive to life, rather than hastening the journey towards chaotic states, is paramount for human survival and well-being in the Anthropocene era.

Many digital technologies, designed and controlled by intensive data-driven corporate platforms, have become ubiquitous for many of our daily activities. This has raised political and ethical concerns over how they might be threatening our personal autonomy. However, not much philosophical attention has been paid to the specific role that their hyper-designed (sensorimotor) interfaces play in this regard. In this paper, we aim to offer a novel framework that can ground personal autonomy on sensorimotor interaction and, from there, directly address how technological design affects personal autonomy. To do this, we will draw from enactive sensorimotor approaches to cognition, focusing on the central notion of habits, understood as sensorimotor schemes that, in networked relations, give rise to sensorimotor agency. Starting from sensorimotor agency as a basis for more complex forms of personal autonomy, our approach gives us grounds to analyse our relationship with technology (in general) and to distinguish between autonomy-enhancing and autonomy-diminishing technologies. We argue that, by favouring/obstructing the enactment of certain (networks of) habits over others, technologies can directly act upon our personal autonomy, locally and globally. With this in mind, we then discuss how current digital technologies are often being designed to be autonomy-diminishing (as is the case of “dark patterns” in design), and sketch some ideas on how to build more autonomy-enhancing digital technologies.

There are many different kinds of model and scientists do all kind of things with them. This diversity of model type and model use is a good thing for science. Indeed, it is crucial especially for the biological and cognitive sciences, which have to solve many different problems at many different scales, ranging from the most concrete of the structural details of a DNA molecule to the most abstract and generic principles of self-organization in networks. Getting a grip (or more likely many separate grips) on this range of topics calls for a teeming forest of techniques, including many different modeling techniques. Barbara Webb’s target article strikes us as a proposal for clear-cutting the forest. We think clear-cutting here would be as good for science as it is for non-metaphorical forests. Our argument for this is primarily a recitation of a few of the ways that diversity has been useful. Recently, looking at the actual practice of artificial life modelers, one of us distinguished four uses of simulation models classified in terms of the position the models take up between theory and data (see Figure 1). The classification is not exhaustive, and the barriers between kinds are not absolute. Rather, the purpose of the taxonomy is to open up the view for an epistemic ecology of modeling practices. First, and closest to the empirical domain, there are mechanistic models, in which there is an almost one-to-one correspondence between variables in the model and observables in the target system and its environment. Webb’s..

The first form of the inside-outside dichotomy appears as a self-encapsulated system with an active border. These systems are based on two complementary but asymmetric processes: constructive and interactive. The former physically constitute the system as a recursive network of component production, defining an inside. The maintenance of the constructive processes implies that the internal organization also constrains certain flows of matter and energy across the border of the system, generating interactive processes. These interactive processes ensure the maintenance of the constructive processes thus specifying a meaningful outside. Upon this basic form of identity formation, the evolutionary and historical domain is open for the emergence of a whole hierarchy and ecology of insides and outsides. These which mutually subsume and collaborate in the maintenance of the essential inside-outside dichotomy that defines the conditions of possibility of the subjects and the worlds they generate.

Both the irreducible complexity of biological phenomena and the aim of a universalized biology (life-as-it-could-be) have lead to a deep methodological shift in the study of life; represented by the appearance of ALife, with its claim that computational modelling is the main tool for studying the general principles of biological phenomenology. However this methodological shift implies important questions concerning the aesthetic, engineering and specially the epistemological status of computational models in scientific research: halfway between the well established categories of theory and experiment. ALife models become powerful epistemic artefacts allowing the simulation of emergent phenomena, the interaction between different levels of organization and the integration of different causal factors in the very same manipulable object. The use of computational models in ALife can be classified in four main categories depending on their position between theoretical and empirical practices: generic, conceptual, functional and mechanistic. For each of these categories we analyse their epistemic value and select paradigmatic examples that illustrate how ALife models can be fruitfully inserted in the study of life.

We are currently witnessing the emergence of new forms of collective identities and a redefinition of the old ones through networked digital interactions, and these can be explicitly measured and analyzed. We distinguish between three major trends on the development of the concept of identity in the social realm: (1) an essentialist sense (based on conditions and properties shared by members of a group), (2) a representational or ideational sense (based on the application of categories by oneself or others), and (3) a relational and interactional sense (based on interaction processes between actors and their environments). The interactional approach aligns with current empirical and methodological progress in social network analysis. Moreover, it has been argued that, within the network society, the notion of collective identity (Melucci, 1995) in the political field must be rethought as technologically mediated and interactive. We suggest that collective identities should be understood as recurrent, cohesive, and coordinated communicative interaction networks. We here propose that such identities can be depicted by: (a) mapping and filtering a relevant interaction network, (b) delimiting a set of communities, (c) determining the strongly connected component(s) of such communities (the core identity) in a directed graph, and (d) defining the identity audiences and sources within the community. This technical graph–theoretical characterization is explained and justified in...

Living agency is subject to a normative dimension (good-bad, adaptive-maladaptive) that is absent from other types of interaction. We review current and historical attempts to naturalize normativity from an organism-centered perspective, identifying two central problems and their solution: (1) How to define the topology of the viability space so as to include a sense of gradation that permits reversible failure, and (2) how to relate both the processes that establish norms and those that result in norm-following behavior. We present a minimal metabolic system that is coupled to a gradient-climbing chemotactic mechanism. Studying the relationship between metabolic dynamics and environmental resource conditions, we identify an emergent viable region and a precarious region where the system tends to die unless environmental conditions change. We introduce the concept of normative field as the change of environmental conditions required to bring the system back to its viable region. Norm-following, or normative action, is defined as the course of behavior whose effect is positively correlated with the normative field. We close with a discussion of the limitations and extensions of our model and some final reflections on the nature of norms and teleology in agency.

Decidim es una plataforma digital de democracia participativa desarrollada por el Ajuntament de Barcelona. Decidim es, además, un proyecto tecnopolítico que implica multitud de códigos más allá del informático. Distinguimos tres planos analíticos que sirven para conceptualizar de forma holística y sistemática el proyecto Decidim: un plano político, uno tecnopolítico, y un plano técnico. Decidim emerge como ejemplo de lo que denominamos “redes políticas” caracterizadas, frente a las “redes sociales”, por hacer del vínculo político y la construcción de inteligencia y voluntad colectivas el centro de su diseño y estructura. A su vez, la comunidad y los espacios “Metadecidim” operan como dispositivos para la democratización del software de Decidim y de la democracia en red en un sentido más amplio, constituyendo “redes tecnopolíticas”. Estas redes de nueva generación hacen de la plataforma una infraestructura público-común (financiada con dinero público y co-diseñada con la ciudadanía), abierta y libre para la democracia participativa, un proyecto que aspira a servir de dispositivo y modelo para la transformación política en un periodo de crisis de la hegemonía neoliberal.