Information literacy and peer-to-peer infrastructures: An autopoietic perspective
Introduction
Complex adaptive systems (CAS) are built on interactions between interdependent agents which process energy, matter and information, that is, agents with both metabolic and cognitive processes. For example, a human being is developed on the interactions of different biological subsystems through cognitive (information processing) and metabolic (matter and energy processing) networks. Also, the emergent properties of societies are built on complex interactions between simple agents. However, in this case agents are not neurons or other sort of cells, but citizens that consume and produce matter, energy and information.
CAS evolution can be explained on a temporal axis with two fundamental dimensions (Heylighen, 1999). On the one side, there is a structural dimension exemplified by the transformation of communications, evolving from centralized societies with low connectivity between agents to distributed networks (view Fig. 1) with thousands of exchanges per second. On the other, there is a functional dimension; as it is pointed by Stewart (2000), the progress from hunter-gatherer societies to transnational communities with high levels of heterogeneity, complex division of labor and wide diversity of cultural trends. In case a CAS has achieved high structural decentralization and functional heterogeneity, and we project the aforementioned view to a social system, then we call this state of balance a peer-to-peer (P2P) paradigm.
In such a paradigm, the participating agents can potentially be both consumers and producers of information. P2P dynamics generate public information available worldwide in digital repositories, websites and bibliographic resources. The growth of the contents in collaborative platforms, such as Wikipedia or the increase of publications in blogs and other social media, implies a huge amount of unstructured, ambiguous and multi-lingual information. These resources can be only partially processed by human agents who are part of the same linguistic communities. However, parsing, translating and processing such amount of data require complex software mechanisms and it is not achievable by a single central-controlled system. We arguably need distributed and heterogeneous networks of coordinated mechanisms composed by both specialized human and artificial agents in order to improve information retrieval, filtering, reasoning and decision-making. Distributed, because the more complex a system becomes, the more difficult is to manage everything from a central node. Heterogeneous, because a larger variety of skills and approaches implies more possible solutions to common problems, avoids redundancy of efforts and therefore increases productivity (Heylighen, 2002).
In these distributed and heterogeneous networks, agents have to handle technical issues such as information overload, unstructured data and non-interoperability, but also have to be able to produce new knowledge and value from existing resources. These aspects imply a reformulation of knowledge management and a chance for Artificial Intelligence techniques such as Knowledge Representation and Reasoning.
In this paper we review different proposals, pointing out to possible answers for these issues. In Section 2, we introduce the idea of a P2P paradigm within the CAS. In Section 3, we address the problem of information overload and discuss some solutions proposed by Francis Heylighen. We also review some computer-based solutions that can be implemented in order to provide data interoperability and allow knowledge inference from heterogeneous and distributed sources. In Section 4, we explain briefly the notion of social autopoiesis and develop the idea of information literacy from an autopoietic perspective. Next, in Section 5, we focus on the Commons-based peer production and the basis of a new collaborative economy enabled by the P2P infrastructures. Finally, we summarize our conclusions.
Section snippets
Building P2P infrastructures
A CAS can be described as a network of interrelated agents able to adapt to changes in the environment (Levin, 2002). Such a system can also be considered autopoietic if it generates the necessary components to preserve its autonomy as a discrete unit. These two concepts (CAS and autopoiesis) can be used to describe a social system: we might use the CAS concept if we assume that the system evolves dynamically and is built on networked interactions between social agents; we might use an
Information overload and interoperability
According to a report of the School of Information Management and Systems at the University of California at Berkeley (2003), 18 exabytes of new information flowed through electronic channels in 2002. Only between 1999 and 2002 the amount of stored information grew about 30% a year (see Table 1). We could suppose that these numbers have largely increased during the last decade. How to manage this huge amount of information is a complex issue. Francis Heylighen is one of the scholars who have
Social autopoiesis: information literacy and self-production
Several approaches have been proposed regarding the concept of autopoiesis (Luisi, 2003, Radosavljevic, 2008, Razeto-Barry, 2012, Varela et al., 1974). We consider as an autopoietic system any open system that depends on external resources for survival while producing the needed mechanisms to preserve itself as a discrete and autonomous unity.
In social sciences, autopoiesis should be something more than just a useful metaphor to suggest structural organization, but also a theoretical framework
Commons-based peer production and collaborative economy
As said, the free encyclopedia Wikipedia and a myriad of free/open source software projects (FOSS) arguably epitomize a remarkable transformation in the organization of information production that occurred in the past two decades. Such projects emphasize the rising of technological capabilities shaped by human factors, which in turn shape the environment under which humans live and work (Kostakis et al., 2013). They create what Benkler (2006, p. 31) calls new “technological-economic feasibility
Conclusion
The emergence of a P2P paradigm would be the consequence of the development of communication networks, transportation and energy supply through an efficient distribution of information but also of material and energy resources. This new mode of social organization would be supported by the development of decentralized mechanisms that would allow exchanges between peers while preserving functional heterogeneity.
Even though we have not yet reached an actual P2P paradigm, we are already living a
Acknowledgments
Vasilis Kostakis acknowledges funding for facilities used in this research by IUT (19-13) of the Estonian Ministry of Education and Research.
Diego González-Rodríguez is Computer Systems Engineer and Master in Artificial Intelligence. He has worked in several Research and Development projects in different fields such as Natural Computing, Data Mining, Artificial Intelligence and Software as a Service. He is PhD Candidate in Information Science at the University Carlos III of Madrid, where he studies P2P Social Dynamics. He has been Visiting Researcher at the University of Toronto and the University of North Carolina.
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Diego González-Rodríguez is Computer Systems Engineer and Master in Artificial Intelligence. He has worked in several Research and Development projects in different fields such as Natural Computing, Data Mining, Artificial Intelligence and Software as a Service. He is PhD Candidate in Information Science at the University Carlos III of Madrid, where he studies P2P Social Dynamics. He has been Visiting Researcher at the University of Toronto and the University of North Carolina.
Vasilis Kostakis (PhD, MSc, MA) is political economist and founder of the P2P Lab. Currently he is a research fellow at the Ragnar Nurkse School of Innovation and Governance at Tallinn University of Technology, Estonia, and a collaborator of the P2P Foundation.