Author Archive for Alessandro Cerboni

05
Lug
19

THE INHERENT INSTABILITY OF DISORDERED SYSTEMS

La legge multiscala della varietà richiesta è una legge scientifica relativa, in ciascuna scala, alla variazione di un ambiente rispetto alla variazione dello stato interno necessaria per una risposta efficace da parte di un sistema. Sebbene questa legge sia stata utilizzata per descrivere l’efficacia dei sistemi nell’autoregolamentazione, le conseguenze per il fallimento non sono state formalizzate. Qui usiamo questa legge per considerare le dinamiche interne di un sistema non strutturato e la sua risposta ad un ambiente strutturato. Scopriamo che, a causa della sua incapacità di rispondere, un sistema completamente non strutturato è intrinsecamente instabile per la formazione della struttura. E in generale, qualsiasi sistema senza una struttura al di sopra di una certa scala non è in grado di resistere a una struttura che sorge sopra quella scala. Per descrivere complicate dinamiche interne, sviluppiamo una caratterizzazione di modifiche multiscala in un sistema. Questa caratterizzazione è motivata dalle idee teoriche del rumore di Shannon, ma considera le informazioni strutturate. Quindi colleghiamo le nostre scoperte all’anarchismo politico mostrando che la società richiede alcuni processi organizzativi, anche se non esiste un governo o gerarchie tradizionali. Formuliamo anche i nostri risultati come una seconda legge inversa della termodinamica; mentre i sistemi chiusi collassano in disordine, i sistemi aperti a un ambiente strutturato generano spontaneamente ordine.

 

Abstract

The Multiscale Law of Requisite Variety is a scientific law relating, at each scale, the variation in an environment to the variation in internal state that is necessary for effective response by a system. While this law has been used to describe the effectiveness of systems in self-regulation, the consequences for failure have not been formalized. Here we use this law to consider the internal dynamics of an unstructured system, and its response to a structured environment. We find that, due to its inability to respond, a completely unstructured system is inherently unstable to the formation of structure. And in general, any system without structure above a certain scale is unable to withstand structure arising above that scale. To describe complicated internal dynamics, we develop a characterization of multiscale changes in a system. This characterization is motivated by Shannon information theoretic ideas of noise, but considers structured information. We then relate our findings to political anarchism showing that society requires some organizing processes, even if there is no traditional government or hierarchies. We also formulate our findings as an inverse second law of thermodynamics; while closed systems collapse into disorder, systems open to a structured environment spontaneously generate order.

https://necsi.edu/the-inherent-instability-of-disordered-systems?fbclid=IwAR1SbanBKzLaVnMVIgB-sKJ366Rhip3ahl2XHUNfkuT22YtHlRsKUQGRDEQ

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13
Mag
19

Semantic information, agency, & physics

via Semantic information, agency, & physics

Shannon information theory provides various measures of so-called syntactic information, which reflect the amount of statistical correlation between systems. By contrast, the concept of ‘semantic information’ refers to those correlations which carry significance or ‘meaning’ for a given system. Semantic information plays an important role in many fields, including biology, cognitive science and philosophy, and there has been a long-standing interest in formulating a broadly applicable and formal theory of semantic information. In this paper, we introduce such a theory. We define semantic information as the syntactic information that a physical system has about its environment which is causally necessary for the system to maintain its own existence. ‘Causal necessity’ is defined in terms of counter-factual interventions which scramble correlations between the system and its environment, while ‘maintaining existence’ is defined in terms of the system’s ability to keep itself in a low entropy state. We also use recent results in non-equilibrium statistical physics to analyse semantic information from a thermodynamic point of view. Our framework is grounded in the intrinsic dynamics of a system coupled to an environment, and is applicable to any physical system, living or otherwise. It leads to formal definitions of several concepts that have been intuitively understood to be related to semantic information, including ‘value of information’, ‘semantic content’ and ‘agency’.

 

https://www.researchgate.net/publication/328394982_Semantic_information_autonomous_agency_and_non-equilibrium_statistical_physics

13
Mag
19

Hello World: Being Human in the Age of Algorithms (Hannah Fry)

via Hello World: Being Human in the Age of Algorithms (Hannah Fry)

A look inside the algorithms that are shaping our lives and the dilemmas they bring with them.

If you were accused of a crime, who would you rather decide your sentence―a mathematically consistent algorithm incapable of empathy or a compassionate human judge prone to bias and error? What if you want to buy a driverless car and must choose between one programmed to save as many lives as possible and another that prioritizes the lives of its own passengers? And would you agree to share your family’s full medical history if you were told that it would help researchers find a cure for cancer?

 

https://www.theguardian.com/books/2018/sep/29/hello-world-hannah-fry-review-artificial-intelligence-algorithms

13
Mag
19

Attack Tolerance of Link Prediction Algorithms: How to Hide Your Relations in a Social Network

via Attack Tolerance of Link Prediction Algorithms: How to Hide Your Relations in a Social Network

Attack Tolerance of Link Prediction Algorithms: How to Hide Your Relations in a Social Network
Link prediction is one of the fundamental research problems in network analysis. Intuitively, it involves identifying the edges that are most likely to be added to a given network, or the edges that appear to be missing from the network when in fact they are present. Various algorithms have been proposed to solve this problem over the past decades. For all their benefits, such algorithms raise serious privacy concerns, as they could be used to expose a connection between two individuals who wish to keep their relationship private. With this in mind, we investigate the ability of such individuals to evade link prediction algorithms.

https://arxiv.org/abs/1809.00152

13
Mag
19

Connectivity and complex systems: learning from a multi-disciplinary perspective

via Connectivity and complex systems: learning from a multi-disciplinary perspective

Connectivity and complex systems: learning from a multi-disciplinary perspective

In recent years, parallel developments in disparate disciplines have focused on what has come to be termed connectivity; a concept used in understanding and describing complex systems. Conceptualisations and operationalisations of connectivity have evolved largely within their disciplinary boundaries, yet similarities in this concept and its application among disciplines are evident. However, any implementation of the concept of connectivity carries with it both ontological and epistemological constraints, which leads us to ask if there is one type or set of approach(es) to connectivity that might be applied to all disciplines. In this review we explore four ontological and epistemological challenges in using connectivity to understand complex systems from the standpoint of widely different disciplines. These are: (i) defining the fundamental unit for the study of connectivity; (ii) separating structural connectivity from functional connectivity; (iii) understanding emergent behaviour; and (iv) measuring connectivity. We draw upon discipline-specific insights from Computational Neuroscience, Ecology, Geomorphology, Neuroscience, Social Network Science and Systems Biology to explore the use of connectivity among these disciplines. We evaluate how a connectivity-based approach has generated new understanding of structural-functional relationships that characterise complex systems and propose a ‘common toolbox’ underpinned by network-based approaches that can advance connectivity studies by overcoming existing constraints.

https://link.springer.com/article/10.1007/s41109-018-0067-2

13
Mag
19

Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions

Abstract

Artificial intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime (AIC). AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space.

05
Apr
19

Ideologies, policies, and social complexity

A hard question that this line of thought poses and that I have not addressed here is whether policies can be formulated at all within the context of a fundamentally heterogeneous and contingent world. It might be argued that policy formation requires fairly simple cause-and-effect relationships in order to justify the idea of an intervention; and complexity makes it unlikely that such relationships exist. I believe policies can be formulated within this ontological framework; but I agree that the case must be made. A few earlier posts are relevant to this topic

Understanding Society

 

The approach to social and historical research that I favor is one that pays attention to the heterogeneity and contingency of social processes. It advises that social and historical researchers should disaggregate the large patterns they start with and try to identify the multiple underlying mechanisms, causes, motivations, movements, and contingencies that came together to create higher-level outcomes. Social research needs to focus on the micro- or meso-level processes that combined to create the macro world that interests us. The theory of assemblages fits this intellectual standpoint very well, since it emphasizes contingency and heterogeneity all the way down. The diagram above was chosen to give a visual impression of the complexity and interconnectedness of factors and causes that are associated with this approach to the social world.

According to the premises of this approach, we are not well served by imagining that there are simple, largescale forces that…

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