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The quality of collective intelligence flowing in and across systems communities of various disciplines, and the fragmentation or connectedness of their mental models of the world, shape their capacity to assist decision-makers and social movements in defining, mapping, and addressing the world problematique, by identifying policy options and anticipating their outcomes. In their current state of fragmentation, the systems sciences' epistemic communities cannot provide that assistance. Upgrading their collective intelligence is a vital imperative. This paper is suggest the prototyping of a Collective Intelligence Enhancement Lab and describes its core idea as a platform with an innovation architecture that integrates social, electronic, cognitive, and inner technologies and processes. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The 57th meeting and conference of the International Society for the Systems Sciences focused on the meta-theme of Curating the Conditions for a Thrivable Planet. The event was conceived as a living learning lab for collective intelligence that aimed to provide its participants with a set of total immersion environments in which to explore our role as systems scientists, and beyond that, as members of a globalizing species at this time in history. As such, the conference provided individual and collective opportunities to foster that basic feeling of being connected, to explore what it means to be appreciative systems (as Sir Geoffrey Vickers would have it) to manifest new levels of community and fundamentally, to evolve the narrative of our role as authors of the conscious evolution of our species. This paper presents the stage-setting remarks presented at the opening of the 57th annual meeting and conference of the ISSS, inviting members and conference participants to address the principal theme of this conference that took place in Vietnam: the search for systemic leverage points for emerging a global eco-civilization. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper attempts a preliminary analysis of the global desirability of different forms of openness in AI development (including openness about source code, science, data, safety techniques, capabilities, and goals). Short-term impacts of increased openness appear mostly socially beneficial in expectation. The strategic implications of medium and long-term impacts are complex. The evaluation of long-term impacts, in particular, may depend on whether the objective is to benefit the present generation or to promote a time-neutral aggregate of well-being of future generations. Some forms of openness are plausibly positive on both counts (openness about safety measures, openness about goals). Others (openness about source code, science, and possibly capability) could lead to a tightening of the competitive situation around the time of the introduction of advanced AI, increasing the probability that winning the AI race is incompatible with using any safety method that incurs a delay or limits performance. We identify several key factors that must be taken into account by any well-founded opinion on the matter. [ABSTRACT FROM AUTHOR]

This paper presents a preparation strategy for ethnographic field stays that seeks to speed up the process of gaining social access (after physical access) to the participants in the field by a thematic preparation for the stay. We build on our experiences of an ethnographic inquiry as well as on autopoietic systems theory by Niklas Luhmann. We shall argue that so far, little attention has been given to possibilities of preparation of topics of communication with field participants in the foregoing of a stay. However, the existing methodological literature in this respect so far focuses mainly on the preparation of professional topics for communication. We want to add to these strategies and propose to gain knowledge about possibly acceptable topics for sociable communication in the field by conducting ex ante interviews with existing gatekeepers. Researchers can therefore prepare those topics to quickly gain social access in the field. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Computational sociology models social phenomena using the concepts of emergence and downward causation. However, the theoretical status of these concepts is ambiguous; they suppose too much ontology and are invoked by two opposed sociological interpretations of social reality: the individualistic and the holistic. This paper aims to clarify those concepts and argue in favour of their heuristic value for social simulation. It does so by proposing a link between the concept of emergence and Luhmann's theory of communication. For Luhmann, society emerges from the bottom-up as communication and he describes the process by which society limits the possible selections of individuals as downward causation. It is argued that this theory is well positioned to overcome some epistemological drawbacks in computational sociology. [ABSTRACT FROM AUTHOR]

The accelerated datafication of social life has led to increased interest in advancing the use of big data in psychology. However, prevailing methodological preoccupations in big data psychology elide foundational issues which amplify the problems of modernity/coloniality, including the suppression of marginalized psychologies and the widened gap between researchers and their subjects. We propose decolonial foundations for utilizing big data in psychological scholarship. We move beyond prevailing technical concerns with data processing, to engage situated practices of knowledge production. The ontological object of computing shifts from a universal psychology of numerous individuals, to a localized psychology of collectives. Epistemological priorities shift from context‐free definition and control, to prioritizing temporal responsiveness and linguistic fidelity to emergent psychological phenomena. Ethical guidelines extend beyond issues of personal privacy, and address sociopolitical concerns in fragile democracies. Finally, reflexivities from the margins account for unequal systems that situate psychologists, big data, and the phenomena they study within the plurality of Global Souths. Two Philippine case studies operationalize these principles through localized data collection practices, participatory algorithmic design, interrogation of bias, and wrestling with state encroachments. We conclude with decolonial directions for advancing equitable practices of knowledge production within the computational and psychological sciences. [ABSTRACT FROM AUTHOR]

Prediction of a stage-discharge relationship is of immense importance for reliable planning, design and management of most water resources projects. The aim of this study is to compare the performance of artificial intelligence methods, namely, Artificial Neural Network, Adaptive Nero- Fuzzy Inference System ( ANFIS), and Gene- Expression Programming, with those of two conventional methods, i.e., stage-rating curve and Regression techniques in deriving a stage-discharge curve in the Kizilirmak River, Turkey. The daily minimum, mean and maximum river discharge, and stage data for period of 2005-2007 were used for training and testing the models. The comparison includes visual and parametric approaches, namely coefficient of correlation, mean absolute error and root mean square error. The results proved the high ability of the artificial intelligence methods in developing stage-discharge relationship. Furthermore, the performance of the ANFIS model was found to be superior to all the models. [ABSTRACT FROM AUTHOR]