A "Social Bitcoin" could sustain a democratic digital world

A multidimensional financial system could provide benefits for individuals, companies, and states. Instead of top-down control, which is destined to eventually fail in a hyperconnected world, a bottom-up creation of value can unleash creative potential and drive innovations. Multiple currency dimensions can represent different externalities and thus enable the design of incentives and feedback mechanisms that foster the ability of complex dynamical systems to self-organize and lead to a more resilient society and sustainable economy. Modern information and communication technologies play a crucial role in this process, as Web 2.0 and online social networks promote cooperation and collaboration on unprecedented scales. Within this contribution, we discuss how one dimension of a multidimensional currency system could represent socio-digital capital (Social Bitcoins) that can be generated in a bottom-up way by individuals who perform search and navigation tasks in a future version of the digital world. The incentive to mine Social Bitcoins could sustain digital diversity, which mitigates the risk of totalitarian control by powerful monopolies of information and can create new business opportunities needed in times where a large fraction of current jobs is estimated to disappear due to computerisation.Comment: Contribution to EPJ-ST special issue on 'Can economics be a Physical Science?', edited by S. Sinha, A. S. Chakrabarti & M. Mitr

NANO-INFORMÁTICA Y MODELACIONES PARA DIVULGAR LAS NANO-CIENCIAS

Esta comunicación intenta promover una idea que ha ido creciendo en popularidad y reconocimiento dentro de la comunidad de ciencia de materiales, la informática de ciencia de materiales, como una opción de integración entre las nano-ciencias y las demandas del mercado en el manejo y análisis de datos, conocido en inglés como data analytics. Las técnicas de aprendizaje computacional, minado de datos, y redes complejas han permitido representar la evolución termodinámica de aleaciones y compuestos y a partir de ese aprendizaje, se han pronosticado nuevos compuestos y aleaciones. A continuación, se muestran las ideas fundamentales de tal integración y cómo pueden ser aplicadas a materiales superconductores y de interés a la industria fotovoltaica.This communication intends promoting the materials science informatics, an idea that has been growing in popularity and recognition among materials scientists. It constitutes an option to integrate the nano-sciences with the market demands on data analytics skills and applications. Techniques as machine learning, data mining, and complex networks have allowed representing the thermodynamic evolution of existing alloys and compounds, from whom, new compounds have been predicted and created. In what follows, the main ideas of the nano-informatics are formulated and how the above-mentioned integration can be accomplished. Besides that, its application to superconductors and materials of interest for the photovoltaic industry is discussed

Lessons learned from challenging data science case studies

In this chapter, we revisit the conclusions and lessons learned of the chapters presented in Part II of this book and analyze them systematically. The goal of the chapter is threefold: firstly, it serves as a directory to the individual chapters, allowing readers to identify which chapters to focus on when they are interested either in a certain stage of the knowledge discovery process or in a certain data science method or application area. Secondly, the chapter serves as a digested, systematic summary of data science lessons that are relevant for data science practitioners. And lastly, we reflect on the perceptions of a broader public towards the methods and tools that we covered in this book and dare to give an outlook towards the future developments that will be influenced by them

From the digital data revolution to digital health and digital economy toward a digital society: Pervasiveness of Artificial Intelligence

Technological progress has led to powerful computers and communication technologies that penetrate nowadays all areas of science, industry and our private lives. As a consequence, all these areas are generating digital traces of data amounting to big data resources. This opens unprecedented opportunities but also challenges toward the analysis, management, interpretation and utilization of these data. Fortunately, recent breakthroughs in deep learning algorithms complement now machine learning and statistics methods for an efficient analysis of such data. Furthermore, advances in text mining and natural language processing, e.g., word-embedding methods, enable also the processing of large amounts of text data from diverse sources as governmental reports, blog entries in social media or clinical health records of patients. In this paper, we present a perspective on the role of artificial intelligence in these developments and discuss also potential problems we are facing in a digital society

CONTEXTUALIZING DISCRIMINATION IN AI: MORAL IMAGINATION AND VALUE SENSITIVE DESIGN AS A FRAMEWORK TO STUDY AI DEVELOPMENT IN THE EU

AI will continue to play a role in service provision by both public and private sector providers. These services sometimes border on fundamental rights such as the right not to be discriminated against. Commonly, most people hold the prevailing belief that data knows best and that algorithms ensure equality and fairness. However, algorithms do discriminate and sometimes they perpetuate inequality. The paper is built on the premise that the primary source of discrimination in AI is human input and not the underlying AI technology. Moral imagination, or more accurately, the lack of it, may be responsible for non-technical bias in AI decision-making. Prohibition of discrimination is recognised as a fundamental value of the EU and it follows that AI systems must comply with EU regulations in their decision-making to prevent discrimination and in the process protect human dignity. As concerns human dignity, algorithmic bias continues to be the main problem regarding automated decision-making. This bias, more often than not, is as a result of reinforcing some institutional and societal discrimination into AI systems in the development phase. This has the effect of continuing to perpetuate bias in the wider society when AI systems are used. This paper takes a dogmatic approach in analyzing the EU value of prohibition of discrimination as it is interpreted in the design process of AI systems by using moral imagination and value sensitive design as a framework of investigation

Ciencias de la complejidad : estado actual

Los aportes teóricos y aplicados de la complejidad en economía han tomado tantas direcciones y han sido tan frenéticos en las últimas décadas, que no existe un trabajo reciente, hasta donde conocemos, que los compile y los analice de forma integrada. El objetivo de este proyecto, por tanto, es desarrollar un estado situacional de las diferentes aplicaciones conceptuales, teóricas, metodológicas y tecnológicas de las ciencias de la complejidad en la economía. Asimismo, se pretende analizar las tendencias recientes en el estudio de la complejidad de los sistemas económicos y los horizontes que las ciencias de la complejidad ofrecen de cara al abordaje de los fenómenos económicos del mundo globalizado contemporáneo.The theoretical and applied contributions of complexity sciences in economy has taken so many directions and have been so fast in last decades, that actually does not exist a recent work, far from we know, that compiles and analyze integrally these contributions. The objective of this document is to develop a situational state of the different conceptual, theoretical, methodological and technological applications of complexity sciences in economy. Therefore, to analyze the actual tendencies in the complex economic systems research and the horizons that complexity sciences offers to the nowadays economic issues of a globalized world

Entrepreneurship Knowledge : When East meets West

Acknowledgements The lead guest editor would like to express his sincerest thanks to Fabian Jintae Froese, for his excellent patience and guidance of this special issue and his thanks to Robert Wuebker, Qunwan Li, Julio de Castro, Chunhua Chen, Song Lin, and Zuhui Xu who provided very useful helps at different stages of the developments of this special issue and when this editorial paper was developed.Peer reviewedPostprin

Knowledge work in the age of control: capitalising on human capital

The main claim that I aim to substantiate in this article is that power in the form of control is exerted in a more insidious manner now that knowledge work has become ‘networked’. To this end, I first describe societal control in the current epoch. Given the fact that my focus is on knowledge work, I next revisit the human capital literature with the aim of coming to a more precise understanding of what knowledge work is. The literature on “leveraging human capital” (Burud and Tumolo 2004) evidences how human capital theory draws on the conditions of free-floating control to optimally capitalise on knowledge workers. Models of overt management have come to be replaced by more expansive and insidious models of control that extend beyond the sphere of work into the intimate recesses of private life. Control operative at the societal level (Castells 1996) extends beyond the macro-level (neoliberal), to the meso-level (organisational), and the micro-level (self-governance). Next, I critically consider the implications of these conditions of control for the (self-)governance of the knowledge worker by drawing on Han’s (2017) further specification of control as “smart power”. I come to the conclusion that under the conditions of apparently greater autonomy and discretion that is so pervasive in the management literature discussing knowledge workers, governance as “control” induces constant work erasing the boundaries between work and private life. Neoliberalism with its mantra of investment in human capital has succeeded in producing an optimally efficient, ever-working subject. Throughout my analyses are informed by Foucault’s (2008) concept of “governmentality”, which fuses the presiding rationality (knowledge) with governance (power as control) to throw light on how human conduct is being conducted (orchestrated) for optimal efficiency