A Storm in an IoT Cup: The Emergence of Cyber-Physical Social Machines

The concept of social machines is increasingly being used to characterise various socio-cognitive spaces on the Web. Social machines are human collectives using networked digital technology which initiate real-world processes and activities including human communication, interactions and knowledge creation. As such, they continuously emerge and fade on the Web. The relationship between humans and machines is made more complex by the adoption of Internet of Things (IoT) sensors and devices. The scale, automation, continuous sensing, and actuation capabilities of these devices add an extra dimension to the relationship between humans and machines making it difficult to understand their evolution at either the systemic or the conceptual level. This article describes these new socio-technical systems, which we term Cyber-Physical Social Machines, through different exemplars, and considers the associated challenges of security and privacy.Comment: 14 pages, 4 figure

Observing Environments

> Context • Society is faced with “wicked” problems of environmental sustainability, which are inherently multiperspectival, and there is a need for explicitly constructivist and perspectivist theories to address them. > Problem • However, different constructivist theories construe the environment in different ways. The aim of this paper is to clarify the conceptions of environment in constructivist approaches, and thereby to assist the sciences of complex systems and complex environmental problems. > Method • We describe the terms used for “the environment” in von Uexküll, Maturana & Varela, and Luhmann, and analyse how their conceptions of environment are connected to differences of perspective and observation. > Results • We show the need to distinguish between inside and outside perspectives on the environment, and identify two very different and complementary logics of observation, the logic of distinction and the logic of representation, in the three constructivist theories. > Implications • Luhmann’s theory of social systems can be a helpful perspective on the wicked environmental problems of society if we consider carefully the theory’s own blind spots: that it confines itself to systems of communication, and that it is based fully on the conception of observation as indication by means of distinction

Can a Turing Player identify itself?

We show that the problem of whether two Turing Machines are functionally equivalent is undecidable and explain why this is significant for the theory of repeated play and evolution

Apperceptive patterning: Artefaction, extensional beliefs and cognitive scaffolding

In “Psychopower and Ordinary Madness” my ambition, as it relates to Bernard Stiegler’s recent literature, was twofold: 1) critiquing Stiegler’s work on exosomatization and artefactual posthumanism—or, more specifically, nonhumanism—to problematize approaches to media archaeology that rely upon technical exteriorization; 2) challenging how Stiegler engages with Giuseppe Longo and Francis Bailly’s conception of negative entropy. These efforts were directed by a prevalent techno-cultural qualifier: the rise of Synthetic Intelligence (including neural nets, deep learning, predictive processing and Bayesian models of cognition). This paper continues this project but first directs a critical analytic lens at the Derridean practice of the ontologization of grammatization from which Stiegler emerges while also distinguishing how metalanguages operate in relation to object-oriented environmental interaction by way of inferentialism. Stalking continental (Kapp, Simondon, Leroi-Gourhan, etc.) and analytic traditions (e.g., Carnap, Chalmers, Clark, Sutton, Novaes, etc.), we move from artefacts to AI and Predictive Processing so as to link theories related to technicity with philosophy of mind. Simultaneously drawing forth Robert Brandom’s conceptualization of the roles that commitments play in retrospectively reconstructing the social experiences that lead to our endorsement(s) of norms, we compliment this account with Reza Negarestani’s deprivatized account of intelligence while analyzing the equipollent role between language and media (both digital and analog)

Farm enterprises as self-organizing systems: A new transdisciplinary framework for studying farm enterprises?

The growing attention to sustainable food production and multifunctional agriculture calls for a multidisciplinary or transdisciplinary research and development perspective on farming, which is able to grasp the environmental, social, technical, and financial aspects of a farm and the dynamic relationship between the farm enterprises and the surrounding world. Our thesis is that a transdisciplinary approach needs to build on a working ontology that goes beyond the epistemology of each discipline and that is not just pieced together of the ontologies connected to these different epistemologies. Based on a review of three prevailing theoretical frameworks within the field of agro-sociology: The farming styles approach, the Bawden approach, and Conway’s agroecosystem approach, we argue that these existing theories do not offer such a theoretical framework. The claim of this paper is that a new concept of a farm enterprise as a self-organizing social system, which combines ideas from Actor-Network theory (ANT) and Luhmann’s theory of social systems, can serve as a useful ontological platform for understanding a farm-enterprise as an entity independent of a scientific observer. In this framework, each farm is understood as a self-organizing node in a complex of heterogeneous socio-technical networks of food, supply, knowledge, technology, etc. This implies that a farm has to be understood as the way in which these network relationships are organised by the farm as a self-organizing social system. Among all the different possible ways in which to interact with the surrounding world, the system has to select a coherent strategy in order to make the farming processes possible at all. It will be discussed how this framework may add to the understanding of the continuous development of a heterogeneity of farm strategies and contribute to a more comprehensive view of the fields of regulation and extension

Towards Contextual Action Recognition and Target Localization with Active Allocation of Attention

Exploratory gaze movements are fundamental for gathering the most relevant information regarding the partner during social interactions. We have designed and implemented a system for dynamic attention allocation which is able to actively control gaze movements during a visual action recognition task. During the observation of a partners reaching movement, the robot is able to contextually estimate the goal position of the partner hand and the location in space of the candidate targets, while moving its gaze around with the purpose of optimizing the gathering of information relevant for the task. Experimental results on a simulated environment show that active gaze control provides a relevant advantage with respect to typical passive observation, both in term of estimation precision and of time required for action recognition. © 2012 Springer-Verlag

Misunderstanding Models in Environmental and Public Health Regulation

Computational models are fundamental to environmental regulation, yet their capabilities tend to be misunderstood by policymakers. Rather than rely on models to illuminate dynamic and uncertain relationships in natural settings, policymakers too often use models as “answer machines.” This fundamental misperception that models can generate decisive facts leads to a perverse negative feedback loop that begins with policymaking itself and radiates into the science of modeling and into regulatory deliberations where participants can exploit the misunderstanding in strategic ways. This paper documents the pervasive misperception of models as truth machines in U.S. regulation and the multi-layered problems that result from this misunderstanding. The paper concludes with a series of proposals for making better use of models in environmental policy analysis.The Kay Bailey Hutchison Center for Energy, Law, and Busines

Combining Luhmann and Actor-Network Theory to see Farm Enterprises as Self-organizing Systems

From a rural, sociological point of view no social theories have so far been able to grasp the ontological complexity and special character of a farm enterprise as an entity in a really satisfying way. The contention of this paper is that a combination of Luhmann’s theory of social systems and actor-network theory (ANT) of Latour, Callon, and Law offers a new and radical framework for understanding a farm as a self-organizing, heterogeneous system. Luhmann’s theory offers an approach to understand a farm as a self-organizing system (operating in meaning) that must produce and reproduce itself through demarcation from the surrounding world by selection of meaning. The meaning of the system is expressed through the goals, values, and the logic of the farming processes. His theory, however, is less useful when studying the heterogeneous character of a farm as a mixture of biology, sociology, technology, and economy. ANT offers an approach to focus on the heterogeneous network of interactions of human and non-human actors such as knowledge, technology, money, farmland, animals, plants, etc., and as to how these interactions depend on both the quality of the actors and the network context of interaction, but the theory is weak when it comes to explaining the self-organizing character of a farm enterprise

Combining Luhmann and Actor-Network Theory to see Farm Enterprises as Self-organizing Systems

From a rural, sociological point of view no social theories have so far been able to grasp the ontological complexity and special character of a farm enterprise as an entity in a really satisfying way. The contention of this paper is that a combination of Luhmann’s theory of social systems and the actor-network theory (ANT) of Latour, Callon, and Law offers a new and radical framework for understanding a farm as a self-organizing, heterogeneous system. Luhmann’s theory offers an approach to understand a farm as a self-organizing system (operating in meaning) that must produce and reproduce itself through demarcation from the surrounding world by selection of meaning. The meaning of the system is expressed through the goals, values, and logic of the farming processes. This theory is, however, less useful when studying the heterogeneous character of a farm as a mixture of biology, sociology, technology, and economy. ANT offers an approach to focus on the heterogeneous network of interactions of human and non-human actors, such as knowledge, technology, money, farmland, animals, plants, etc., and how these interactions depend on both the quality of the actors and the network context of interaction. But the theory is weak when it comes to explaining the self-organizing character of a farm enterprise. Using Peirce’s general semiotics as a platform, the two theories in combination open a new and radical framework for multidisciplinary studies of farm enterprises that may serve as a platform for communication between the different disciplines and approaches