Zentrale Denkfiguren der von Wolfgang Klafki begründeten kritisch-konstruktiven Erziehungswissenschaft werden in diesem Buch aufgegriffen und in ihrem Innovationswert für die wissenschaftliche Pädagogik reflektiert. Namhafte Autorinnen und Autoren unterschiedlicher Subdisziplinen und Generationen vertiefen Klafkis Ansatz theoretisch wie methodisch und öffnen Problemstellungen, die bisher nicht bearbeitet worden sind.

Amazon Book Review Series of “Better Economics for the Earth: A Lesson from Quantum and Information Theories”.

There are growing discontinuities between the research practices of data science and established tools of research ethics regulation. Some of the core commitments of existing research ethics regulations, such as the distinction between research and practice, cannot be cleanly exported from biomedical research to data science research. Such discontinuities have led some data science practitioners and researchers to move toward rejecting ethics regulations outright. These shifts occur at the same time as a proposal for major revisions to the Common Rule—the (...) primary regulation governing human-subjects research in the USA—is under consideration for the first time in decades. We contextualize these revisions in long-running complaints about regulation of social science research and argue data science should be understood as continuous with social sciences in this regard. The proposed regulations are more flexible and scalable to the methods of non-biomedical research, yet problematically largely exclude data science methods from human-subjects regulation, particularly uses of public datasets. The ethical frameworks for Big Data research are highly contested and in flux, and the potential harms of data science research are unpredictable. We examine several contentious cases of research harms in data science, including the 2014 Facebook emotional contagion study and the 2016 use of geographical data techniques to identify the pseudonymous artist Banksy. To address disputes about application of human-subjects research ethics in data science, critical data studies should offer a historically nuanced theory of “data subjectivity” responsive to the epistemic methods, harms and benefits of data science and commerce. (shrink)

Using Big Data to better understand urban questions is an exciting field with challenging methodological and theoretical problems. It is also, however, potentially troubling when Big Data is applied uncritically to urban governance via the ideas and practices of “smart cities”. This essay reviews both the historical depth of central ideas within smart city governance —particular the idea that enough data/information/knowledge can solve society problems—but also the ways that the most recent version differs. Namely, that the motivations and ideological underpinning (...) behind the goal of urban betterment is largely driven by technology advocates and neoliberalism rather than the strong social justice themes associated with earlier applications of data to cities. Geosocial media data and metrics derived from them can provide useful insight and policy direction. But one must be ever mindful that metrics don’t simply measure; in the process of deciding what is important and possible to measure, these data are simultaneously defining what cities are. (shrink)

The collection and dissemination of data on human and nonhuman organisms has become a central feature of 21st-century biology and has been endorsed by funding agencies in the United States and Europe as crucial to translating biological research into therapeutic and agricultural innovation. Large molecular data sets, often referred to as “big data,” are increasingly incorporated into digital databases, many of which are freely accessible online. These data have come to be seen as resources that play a key role in (...) mediating global market exchange, thus achieving a prominent social and economic status well beyond science itself. At the same time, calls to make all such data publicly and freely available have garnered strength and visibility, most prominently in the form of the Open Data movement. I discuss these developments by considering the conditions under which data journey across the communities and institutions implicated in globalized biology and biomedicine, and what this indicates about how Internet-based communication and the use of online databases affect scientific research and its role within contemporary society. (shrink)

Before the EU General Data Protection Regulation entered into force in May 2018, we witnessed an intense struggle of actors associated with data-dependent fields of science, in particular health-related academia and biobanks striving for legal derogations for data reuse in research. These actors engaged in a similar line of argument and formed issue alliances to pool their collective power. Using descriptive coding followed by an interpretive analysis, this article investigates the argumentative repertoire of these actors and embeds the analysis in (...) ethical debates on data sharing and biobank-related data governance. We observe efforts to perform a paradigmatic shift of the discourse around the General Data Protection Regulation-implementation away from ‘protecting data’ as key concern to ‘protecting health’ of individuals and societies at large. Instead of data protection, the key risks stressed by health researchers became potential obstacles to research. In line, exchange of information with data subjects is not a key concern in the arguments of biobank-related actors and it is assumed that patients want ‘their’ data to be used. We interpret these narratives as a ‘reaction’ to potential restrictions for data reuse and in line with a broader trend towards Big Data science, as the very idea of biobanking is conceptualized around long-term use of readily prepared data. We conclude that a sustainable implementation of biobanks needs not only to comply with the General Data Protection Regulation, but must proactively re-imagine its relation to citizens and data subjects in order to account for the various ways that science gets entangled with society. (shrink)

Although the terminology of Big Data has so far gained little traction in economics, the availability of unprecedentedly rich datasets and the need for new approaches – both epistemological and computational – to deal with them is an emerging issue for the discipline. Using interviews conducted with a cross-section of economists, this paper examines perspectives on Big Data across the discipline, the new types of data being used by researchers on economic issues, and the range of responses to this opportunity (...) amongst economists. First, we outline the areas in which it is being used, including the prediction and ‘nowcasting’ of economic trends; mapping and predicting influence in the context of marketing; and acting as a cheaper or more accurate substitute for existing types of data such as censuses or labour market data. We then analyse the broader current and potential contributions of Big Data to economics, such as the ways in which econometric methodology is being used to shed light on questions beyond economics, how Big Data is improving or changing economic models, and the kinds of collaborations arising around Big Data between economists and other disciplines. (shrink)

Having been involved in a slew of recent scandals, many of the world’s largest technology companies embarked on devising numerous codes of ethics, intended to promote improved standards in the conduct of their business. These efforts have attracted largely critical interdisciplinary academic attention. The critics have identified the voluntary character of the industry ethics codes as among the main obstacles to their efficacy. This is because individual industry leaders and employees, flawed human beings that they are, cannot be relied on (...) voluntarily to conform with what justice demands, especially when faced with powerful incentives to pursue their own self-interest instead. Consequently, the critics have recommended a suite of laws and regulations to force the tech companies to better comply with the requirements of justice. At the same time, they have paid little attention to the possibility that individuals acting within the political context, e.g. as lawmakers and regulators, are also imperfect and need not be wholly compliant with what justice demands. This paper argues that such an omission is far from trivial. It creates a heavy argumentative burden on the part of the critics that they by and large fail to discharge. As a result, the case for Big Tech regulation that emerges from the recent literature has substantial lacunae and more work needs to be done before we can accept the critics’ calls for greater state involvement in the industry. (shrink)

The aim of this article is to assess the impact of Big Data technologies for insurance ratemaking, with a special focus on motor products.The first part shows how statistics and insurance mechanisms adopted the same aggregate viewpoint. It made visible regularities that were invisible at the individual level, further supporting the classificatory approach of insurance and the assumption that all members of a class are identical risks. The second part focuses on the reversal of perspective currently occurring in data analysis (...) with predictive analytics, and how this conceptually contradicts the collective basis of insurance. The tremendous volume of data and the personalization promise through accurate individual prediction indeed deeply shakes the homogeneity hypothesis behind pooling. The third part attempts to assess the extent of this shift in motor insurance. Onboard devices that collect continuous driving behavioural data could import this new paradigm into these products. An examination of the current state of research on models with telematics data shows however that the epistemological leap, for now, has not happened. (shrink)

This paper reviews the contemporary discussion on the epistemological and ontological effects of Big Data within social science, observing an increased focus on relationality and complexity, and a tendency to naturalize social phenomena. The epistemic limits of this emerging computational paradigm are outlined through a comparison with the discussions in the early days of digitalization, when digital technology was primarily seen through the lens of dematerialization, and as part of the larger processes of “postmodernity”. Since then, the online landscape has (...) become increasingly centralized, and the “liquidity” of dematerialized technology has come to empower online platforms in shaping the conditions for human behavior. This contrast between the contemporary epistemological currents and the previous philosophical discussions brings to the fore contradictions within the study of digital social life: While qualitative change has become increasingly dominant, the focus has gone towards quantitative methods; while the platforms have become empowered to shape social behavior, the focus has gone from social context to naturalizing social patterns; while meaning is increasingly contested and fragmented, the role of hermeneutics has diminished; while platforms have become power hubs pursuing their interests through sophisticated data manipulation, the data they provide is increasingly trusted to hold the keys to understanding social life. These contradictions, we argue, are partially the result of a lack of philosophical discussion on the nature of social reality in the digital era; only from a firm metatheoretical perspective can we avoid forgetting the reality of the system under study as we are affected by the powerful social life of Big Data. (shrink)

Theory in sociology is constructed as a canon, a very short list of social theorists who have been endowed with suprahistorical status. Drawing on the feminist analysis of gendered consciousness, the author argues that social theory is organized exactly as it should be if one were thinking like a White male capitalist. The perceptual frameworks it employs—a hierarchy of the social, logical dichotomies, decontextualized abstraction, an individualist approach—resonate well with descriptions of hegemonic masculine consciousness. As a result, social theory has (...) not just distorted social perception, it is becoming functionally irrelevant in contemporary social life. The author argues that reasonable understandings are more likely if we are developing via an epistemology of connection, moving from thinking of theory as a holy text to organizing theory to create bridges between diverse standpoints, across disciplinary boundaries, and between knowing and doing. (shrink)

Laplace once argued that if one could “comprehend all the forces by which nature is animated,” it would be possible to predict the future and explain the past. The advent of analysis of large-scale data sets has been accompanied by newfound concerns about “Laplace’s Demon” as it relates to certain fields of science as well as management, evaluation, and audit. I begin by asking how statistical data are constructed, illustrating the hermeneutic acts necessary to create a variable. These include attributing (...) a certain characteristic to a particular phenomenon, isolating the characteristic of interest, and assigning a value to it. In addition, a population must be identified and a sample must be “taken” from that population. Next, I examine how statistical analyses are conducted, examining the interpretive acts there as well. In each case, I show how big data add new challenges. I then show how statistics are incorporated into audits and evaluations, emphasizing how alternative interpretations are concealed in the audit process. I conclude by noting that these issues cannot be “resolved” as Laplace suggested. His Demon, already banished from physics, needs to be banished from other fields of science, management, audits, and evaluations as well. (shrink)

With a mass digitisation programme underway and the addition of non-print legal deposit and web archive collections, the National Library of Scotland is now both producing and collecting data at an unprecedented rate, with over 5PB of storage in the Library’s data centres. As well as the opportunities to support large scale analysis of the collections, this also presents new challenges around data management, storage, rights, formats, skills and access. Furthermore, by assuming the role of both creators and collectors, libraries (...) face broader questions about the concepts of ‘collections' and ‘heritage', and the ethical implications of collecting practices. While the ‘collections as data’ movement has encouraged cultural heritage organisations to present collections in machine-readable formats, new services, processes and tools also need to be established to enable these emerging forms of research, and new modes of working need to be established to take into account an increasing need for transparency around the creation and presentation of digital collections. This commentary explores the National Library of Scotland's new digital scholarship service, the implications of this new activity and the obstacles that libraries encounter when navigating a world of Big Data. (shrink)

Our objective is to examine the effects of Big Five personality traits on ethical ideologies using a time-lagged design of 406 employees of higher education institutions in Pakistan. Based on low/high idealism versus relativism, we investigate the conceptual linkage between each of the personality traits and moral philosophy. The results illustrate that extraversion and openness to experience believed on subjectivism moral philosophy, agreeableness believed on situationism, and neuroticism believed on absolutism moral philosophies. In addition, contentiousness believed on exceptionism moral philosophy. (...) Furthermore, managerial implications and future research directions are suggested. (shrink)

Uma reflexão crítica sobre os caminhos e descaminhos das tecnologias contemporâneas se impõe com cada vez mais força na atualidade. Não se pode mais falar das dimensões “social” e “política” apenas se referindo à interação intersubjetiva; é preciso focar igualmente na interação humana com os aparatos técnicos. Tendo como pano de fundo a crescente digitalização da vida, acompanhada de processos de captação e armazenamento massivos de dados por parte de diferentes mecanismos e instâncias, gostaria de abordar, neste artigo, uma série (...) de análises sobre os impactos do big data nos campos da economia, da política e da subjetividade a fim de colocar a seguinte questão: em que medida esse novo fenômeno não altera a configuração dos espaços de socialização e subjetivação, notadamente a esfera privada, de sorte a gerar um impacto na própria estruturação das democracias modernas? Tal questão se impõe na medida em que a antropologia política da modernidade é baseada, predominantemente, em uma noção substancial de sujeito autônomo, que possui na esfera privada um espaço fundamental de atividade e vivência cujo acesso lhe é privilegiado. Sendo assim, o objetivo do artigo é o de iniciar uma discussão sobre até que ponto as bases da antropologia política da modernidade não estariam sendo solapadas a partir de uma “mudança estrutural da esfera privada”, uma vez que o acesso privilegiado do indivíduo a determinados dados privados poderia ser suplantado pelo advento do Big Data, ameaçando um dos principais pressupostos teóricos e institucionais do liberalismo e da democracia moderna, a saber: a de que somos seres autônomos, responsáveis e os únicos capazes de legitimamente deliberar e tomar determinadas decisões. Procurarei trabalhar tal questionamento a partir de uma proposta de reatualização do conceito habermasiano de consciência tecnocrática. (shrink)

Internet of thing building sensors can capture several types of building operations, performances, and conditions and send them to a central dashboard to analyze data to support decision-making. Traditionally, laptops and cell phones are the majority of Internet-connected devices. IoT tracking allows customers to close the distance between devices and enterprises by collecting and analyzing various IoT data through connected devices, customers, and applications on the network. There is a lack of requirements for IoT edge applications security and approval. There (...) are no best practices regarding operations focused on IoT incidents. IoT elements are not covered by audit and logging requirements. In this article, a big data analytics-based customer operation system analyzes the operation. With the exponential rise in data usage, the explosive development in the IoT devices reflects the ideal overlap of big data growth with IoT. Big data analytics continuously evolving network raises trivial questions about the performance, distribution of data, analysis, and protection of data collection. IoT modifies almost all the construction industry characteristics. Human-centered artificial intelligence is described as systems that always improve because of human input while also delivering an effective experience between the human and the robotic. The IoT is the key factor that ensures greater building performance. It was the first evolution of technology in a long time to turn genuine inventions into an industry that depended heavily on paper and manual processes. The benefits of the IoT in construction are now quite obviously much heavier than those of current manual processes. As a result, more construction companies explore and incorporate IoT strategies to address their productivity challenges, increasing efficiencies and profits. The simulation analysis shows that the proposed BDA-CO model enhances the trust score of 98.5%, accuracy detection ratio of 93.4%, probability ratio of 97.6%, and security ratio of 98.7% and reduces the false negative ratio of 21.3%, response time of 10.5%, delay rate of 19.9%, and packet loss ratio of 15.4% when compared to other existing techniques. (shrink)

With the progress of urbanization, urban management is facing a series of challenges in the new situation. The scale of the city is growing, urban management problems are increasingly prominent, the urban population is showing a rapid growth trend, and various elements of urban infrastructure management, such as rapid growth and urban expansion, have increased the load of urban infrastructure. To make overall planning for urban transportation, municipal administration, economic industry, and public service, intelligent urban planning and construction came into (...) being. Big data technology provides important support for the construction and development of smart city, which is not only an effective means to improve the design of smart city, but also the premise for the development of smart city. Therefore, this paper first introduces the characteristics of smart city, analyses the application of big data technology in smart city design, and finally evaluates the impact of smart city planning and construction based on big data on economic and social benefits. (shrink)

At present, a series of economic structural changes created by the network economy have brought challenges to the entire economy and society. Traditional social commerce has also suffered severe tests under the background of network economy and global integration, and the rise and development of network commercial activities lack legal constraints. Based on the Big Data technology, in view of the characteristics of data mining services, this paper expands and changes the traditional model and proposes the Big Data alliance data (...) mining service process model. Moreover, this paper uses intelligent decision-making theory and knowledge reasoning methods to construct a fast-responding, service-reusable, and intelligent service model to realize the scalability of data mining services. In addition, this paper constructs system function modules according to the requirements of Internet commercial judicial data mining and verifies the performance of the system constructed in this paper through experimental analysis. The research results show that the system constructed in this paper has certain practical effects. (shrink)

In the 1990s, the Dutch astronomical community had to choose its next big telescope project. The starting point of their discussions was not a plan in search of support, but a scientific community in search of a plan. Their discussion demonstrates how big science projects are an integral part of the moral and institutional economy of modern astronomy. Large telescopes are unique but not exceptional: big science has become part of “normal science,” both scientifically and institutionally. In retrospect, the discussions (...) anaylized in this paper discussions concern the earliest phase of three major astronomical instruments: the Atacama Large Millimeter Array, the Square Kilometer Array, and the Low Frequency Array. Interestingly, the Dutch astronomers focused on what they called “strategic” arguments, explicitly excluding arguments regarding scientific merit. I demonstrate how this should be understood in the context of the moral economy of the community. This analysis, based on rich archive material and background interviews with key actors, adds to our understanding of big science or “megascience” in the post–Cold War era. (shrink)

Are theories judged on the basis of empirical tests of their predictions, as proposed by Karl Popper and others, or are new theories adopted by younger scientists while old theories fade away when their advocates die, as Max Planck suggested? A famous historical episode, the rejection of steady state cosmology and the revival of the big bang cosmology following the 1965 discovery of the cosmic microwave background radiation, is examined to determine whether the scientific community followed Popper’s or Planck’s principle. (...) It is found that by 1975 almost all supporters of the steady state had either switched to the big bang or stopped publishing on cosmology. This case therefore seems to exemplify Popper’s principle, although it should be noted that two of the founders of steady state cosmology had strongly proclaimed their adherence to that principle. The case does not support the Popperian claim that successful novel predictions provide better evidence for a theory than deductions of known facts. (shrink)

In the paper, several data reduction techniques for machine learning from big datasets are discussed and evaluated. The discussed approach focuses on combining several techniques including stacking, rotation, and data reduction aimed at improving the performance of the machine classification. Stacking is seen as the technique allowing to take advantage of the multiple classification models. The rotation-based techniques are used to increase the heterogeneity of the stacking ensembles. Data reduction makes it possible to classify instances belonging to big datasets. We (...) propose to use an agent-based population learning algorithm for data reduction in the feature and instance dimensions. For diversification of the classifier ensembles within the rotation also, alternatively, principal component analysis and independent component analysis are used. The research question addressed in the paper is formulated as follows: does the performance of a classifier using the reduced dataset be improved by integrating the data reduction mechanism with the rotation-based technique and the stacking? (shrink)

Introducing the Special Theme on Veillance and Transparency: A Critical Examination of Mutual Watching in the Post-Snowden, Big Data Era, this article presents a series of provocations and practices on veillance and transparency in the context of Big Data in a post-Snowden period. In introducing the theoretical and empirical research papers, artistic, activist and educational provocations and commentaries in this Special Theme, it highlights three central debates. Firstly, concerning theory/practice, it queries how useful theories of veillance and transparency are in (...) explaining mutual watching in the post-Snowden, Big Data era. Secondly, it presents a range of questions concerning norms, ethics, regulation, resistance and social change around veillance and transparency. Thirdly, it interrogates the upsurge in veillance and transparency discourses and practices post-Snowden, and asks whether they are adequate to the task of educating and engaging people on abstract and secretive surveillance practices, as well as on the possibilities and pitfalls of sousveillance. (shrink)

ResumenEn este trabajo queremos indagar sobre algunas cuestiones epistemológicas que se discuten en torno al fenómeno del big data. Como principal herramienta de análisis epistemológico utilizamos a la noción de Marco Epistémico formulada por Piaget y García, y revisada por nosotros en trabajos más recientes, para problematizar los condicionamientos de los valores éticos y políticos, así como de otras regulaciones, en el desarrollo del conocimiento científico. Para ello, proponemos ordenar los debates que se registran en la literatura reciente sobre big (...) data a través de diversas dualidades, tales como dato/interpretación, automático/no-automático o causalidad/correlación, en torno a las cuales vamos a argumentar que es posible pensar dos marcos epistémicos específicos tendientes a la escisión de estos términos o a su integración. Abogando por esta última manera de focalizar los debates, hacia el final del trabajo identificamos algunos desafíos epistemológicos de la investigación con big data, especialmente en las ciencias sociales computacionales.Palabras clave: big data; marco epistémico; constructivismo; computación. (shrink)

Do our lives have meaning? Should we create more people? Is death bad? Should we commit suicide? Would it be better to be immortal? Should we be optimistic or pessimistic? Since Life, Death, and Meaning: Key Philosophical Readings on the Big Questions first appeared, David Benatar’s distinctive anthology designed to introduce students to the key existential questions of philosophy has won a devoted following among users in a variety of upper-level and even introductory courses.

Chinese characters are central to understanding how learners learn to read a logographic script. However, researchers know little about the role of character writing in reading Chinese as a second language (CSL). Unlike an alphabetic script, a Chinese character symbol transmits semantic information and is a cultural icon bridging embodied experience and text meaning. As a unique embodied practice, writing by hand contributes to cognitive processing in Chinese reading. Therefore, it is essential to clarify how Chinese character writing (bodily activity), (...) language distance (past language usage), and cultural background (bodily coupling with the environment) influence CSL reading proficiency. Based on extant research on L2 reading acquisition and strength of key theoretical perspectives of embodied cognition theory (ECT), this study tested a regression model for CSL reading involving individual-level factors (Chinese character writing proficiency [CCWP]) and group-level predictors (language distance and cultural background). This study collected big data in a sample of 74,362 CSL learners with 67 diverse L1s. Results of hierarchical linear modeling showed a significant effect of CCWP and significant language distance × CCWP interaction effect on reading proficiency; however, cultural background × CCWP interaction effect was not significant. These results conform to the ECT and indicate that bodily activity, past language usage, and cultural background aided reading. CCWP may benefit from withstanding the negative transfer from L1s. Furthermore, CCWP and cultural background are not synergistic predictors of reading. This study may open novel avenues for explorations of CSL reading development. (shrink)

The Higgs particle has been detected a few years ago, that is what newspapers tell us. For many physicists, the Standard Model of particle physics has accomplished all the jobs. Or to put it simply: The game is over. Is it true? Then some physicists began to ask: can go beyond the Standard Model? Because the supersymmetric extension of the Standard Model has failed. If you feel that theoretical physics is becoming boring, you are not alone. Fortunately, there is good (...) news: a new generation of physicists are doing table-top experiments in their basements. Can we expect new results later? If so, what will the future of physics look like? This article discusses this question, starting with a blunt look at the relationship between mathematics and physical reality, written from the perspectives of a mathematician and a cosmologist. (shrink)

How did the 3.5-inch Winchester hard disk drive become the fundamental building block of the modern data center? In attempting to answer this question, I theorize the concept of "data peripheries" to attend to the awkward, uneven, and unintended outsides of data infrastructures. I explore the concept of data peripheries by first situating Big Data in one of its many unintended outsides—an unassuming dog kennel in Indiana housed in a former permanent magnet manufacturing plant. From the perspective of this dog (...) kennel, I then build a history of the 3.5-inch Winchester hard disk drive, and weave this hard drive history through the industrial histories of rare earth mining and permanent magnet manufacturing, focusing principally on Magnequench, a former General Motors subsidiary, and its sale and movement of operations from Indiana to China in the mid-1990s and early 2000s. I then discuss how mobilities of rare earths, both as materials and political discourse, shape Big Data futures, and conclude by speculating on how using the situated lenses of data peripheries can open up new methods for studying the material entanglements of Big Data writ large. (shrink)

“We shouldn’t be scared of philosophy. Ideas are always in charge, we might as well get self-conscious about what they are.”.

Big historians are attempting to construct a general holistic narrative of human origins enabling an approach to studying the emergence of complexity, the relation between evolutionary processes, and the modern context of human experience and actions. In this paper I attempt to explore the past and future of cosmic evolution within a big historical foundation characterized by physical, biological, and cultural eras of change. From this analysis I offer a model of the human future that includes an addition and/or reinterpretation (...) of technological singularity theory with a new theory of biocultural evolution focused on the potential birth of technological life: the theory of atechnogenesis. Furthermore, I explore the potential deep futures of technological life and extrapolate towards two hypothetical versions of an ‘Omega Civilization’: expansion and compression. (shrink)

Big data increasingly enables prediction of the behaviour and characteristics of individuals. This is ethically concerning on privacy grounds. However, this article discusses other reasons for concern. These predictions usually rely on generalisations about what certain sorts of people tend to do. Generalisations of this sort are often under scrutiny in legal cases, where, for example, lawyers argue that people with prior convictions are more likely to be guilty of the crime they are currently on trial for. This article applies (...) criteria for distinguishing acceptable from unacceptable generalisations in legal cases to a number of big data examples. It argues that these criteria are helpful, and highlights three issues that should be taken into account when deciding whether predictions about individuals are ethical. (shrink)

Este artículo se centra en el análisis del uso de la industria del big data en la política. Se examina de forma pormenorizada el caso de la empresa Cambridge Analytica y se profundiza en los efectos del uso de la tecnología del big data en el referéndum de permanencia de Reino Unido en la Unión Europea y en las elecciones presidenciales estadounidenses de 2016. El objetivo es exponer los efectos nocivos que tiene el uso de la tecnología del big data (...) en los procesos electorales y los daños que esta tecnología puede producir en los sistemas democráticos. (shrink)

The big bang idea is not only a dominant idea in cosmology but also a very successfully idea out of cosmology. Although sometimes just in metaphorical sense, the big bang idea is present, since some decades, in a variety of domains such as natural sciences, humanities, social sciences, arts, and it also has a great acceptance by the general public. Furthermore, the term Big Bang has become increasingly popular and currently it is often used with very different purposes, including commercial (...) purposes, in contexts that have nothing to do with science, such as music, television, cinema, circus, house decoration, food, and other unexpected domains. Proposed by Gerald Holton, thematic analysis is a useful tool for studying cases like this, because it identifies and describes elements that cross and connect all areas of knowledge and culture in general and thus can help to understand the reception, appropriation and use of certain ideas in different but contemporary disciplinary and cultural contexts, which may be involved in intellectual fashions and in styles of thought of one particular time. (shrink)

A comprehensive introduction to current research on the psychology of concept formation and use.

Commercial success of big data has led to speculation that big-data-like reasoning could partly replace theory-based approaches in science. Big data typically has been applied to ‘small problems’, which are well-structured cases characterized by repeated evaluation of predictions. Here, we show that in climate research, intermediate categories exist between classical domain science and big data, and that big-data elements have also been applied without the possibility of repeated evaluation. Big-data elements can be useful for climate research beyond small problems if (...) combined with more traditional approaches based on domain-specific knowledge. The biggest potential for big-data elements, we argue, lies in socioeconomic climate research. (shrink)

The aim of this work is to identify and analyze a set of challenges that are likely to be encountered when one embarks on fieldwork in linguistic communities that feature small, young, and/or non-standard languages with a goal to elicit big sets of rich data. For each challenge, we (i) explain its nature and implications, (ii) offer one or more examples of how it is manifested in actual linguistic communities, and (iii) where possible, offer recommendations for addressing it effectively. Our (...) list of challenges involves static characteristics (e.g., absence of orthographic conventions and how it affects data collection), dynamic processes (e.g., speed of language change in small languages and how it affects longitudinal collection of big amounts of data), and interactive relations between non-dynamic features that are nevertheless subject to potentially rapid change (e.g., absence of standardized assessment tools or estimates for psycholinguistic variables). The identified challenges represent the domains of data collection and handling, participant recruitment, and experimental design. Among other issues, we discuss population limits and degree of power, inter- and intraspeaker variation, absence of metalanguage and its implications for the process of eliciting acceptability judgments, and challenges that arise from absence of local funding, conflicting regulations in relation to privacy issues, and exporting large samples of data across countries. Finally, the ten experimental challenges presented cover a broad typological spectrum, encompassing both spoken and sign, extant and nearly extinct languages. (shrink)

Big philosophical questions—about the mind, the idea of the good, justice, beauty, knowledge—have been the prime interest of philosophers ever since Plato first raised them in his dialogues. However, regardless of how hard philosophers have been trying to find answers to them, it seems that all they have ever managed to do was to find reasons for disagreements, and, on the whole, to have failed to reach a consensus on pretty much anything. Some philosophers now claim that there hasn’t been (...) much progress in philosophy, especially when compared to the sciences. I take up this verdict and try to refute it, first by offering an alternative view on what counts as progress, and then by analyzing big philosophical questions and their relevance for our intellectual and practical pursuits. I argue that, due to the distinctive nature of philosophical curiosity, coming up with answers to the big philosophical questions is an ideal that can hardly be met, but that philosophy nevertheless delivers various benefits, intellectual and practical, which the proponents of the No-Progress View tend to ignore. (shrink)

As a way to address both ominous and ordinary threats of artificial intelligence, researchers have started proposing ways to stop an AI system before it has a chance to escape outside control and cause harm. A so-called “big red button” would enable human operators to interrupt or divert a system while preventing the system from learning that such an intervention is a threat. Though an emergency button for AI seems to make intuitive sense, that approach ultimately concentrates on the point (...) when a system has already “gone rogue” and seeks to obstruct interference. A better approach would be to make ongoing self-evaluation and testing an integral part of a system’s operation, diagnose how the system is in error and to prevent chaos and risk before they start. In this paper, we describe the demands that recent big red button proposals have not addressed, and we offer a preliminary model of an approach that could better meet them. We argue for an ethical core that consists of a scenario-generation mechanism and a simulation environment that are used to test a system’s decisions in simulated worlds, rather than the real world. This EC would be kept opaque to the system itself: through careful design of memory and the character of the scenario, the system’s algorithms would be prevented from learning about its operation and its function, and ultimately its presence. By monitoring and checking for deviant behavior, we conclude, a continual testing approach will be far more effective, responsive, and vigilant toward a system’s learning and action in the world than an emergency button which one might not get to push in time. (shrink)

This paper presents a new 'discontinuous' view of Popper's theory of corroboration, where theories cease to have corroboration values when new severe tests are devised which have not yet been performed, on the basis of a passage from The Logic of Scientific Discovery. Through subsequent analysis and discussion, a novel problem for Popper's account of corroboration, which holds also for the standard view, emerges. This is the problem of the Big Test : that the severest test of any hypothesis is (...) actually to perform all possible tests. But this means that Popper's demand for 'the severest tests' amounts simply to a demand for 'all possible tests'. The paper closes by considering how this bears on accommodation vs. prediction, with respect to corroboration. (shrink)

Big Data Analytics promises to help companies and public sector service providers anticipate consumer and service user behaviours so that they can be targeted in greater depth. The attempts made by these organisations to connect analytically with users raise questions about whether surveillance, and its associated ethical and rights-based concerns, are intensified. The articles in this special themed issue explore this question from both organisational and user perspectives. They highlight the hype which firms use to drive consumer, employee and service (...) user engagement with analytics within both private and public spaces. Further, they explore extent to which, through Big Data, there is an attempt to expand surveillance into the emotional registers of domestic, embodied experience. Collectively, the papers reveal a fascinating nexus between the much-vaunted potential of analytics, the data practices themselves and the newly configured intimate spheres which have been drawn into the commercial value chain. Together, they highlight the need for conceptual and regulatory innovation so that analytics in practice may be better understood and critiqued. Whilst there is now a rich variety of scholarship on Big Data Analytics, critical perspectives on the organising practices of Big Data Analytics and its surveillance implications are thin on the ground. Combined, the articles published in this special theme begin to address this shortcoming. (shrink)