What the Hack? – Towards a Taxonomy of Hackathons

Curated on Posted on by Stefaan Verhulst

Paper by Christoph Kollwitz and Barbara Dinter: “In order to master the digital transformation and to survive in global competition, companies face the challenge of improving transformation processes, such as innovation processes. However, the design of these processes poses a challenge, as the related knowledge is still largely in its infancy. A popular trend since the mid-2000s are collaborative development events, so-called hackathons, where people with different professional backgrounds work collaboratively on development projects for a defined period. While hackathons are a widespread phenomenon in practice and many field reports and individual observations exist, there is still a lack of holistic and structured representations of the new phenomenon in literature.

The paper at hand aims to develop a taxonomy of hackathons in order to illustrate their nature and underlying characteristics. For this purpose, a systematic literature review is combined with existing taxonomies or taxonomy-like artifacts (e.g. morphological boxes, typologies) from similar research areas in an iterative taxonomy development process. The results contribute to an improved understanding of the phenomenon hackathon and allow the more effective use of hackathons as a new tool in organizational innovation processes. Furthermore, the taxonomy provides guidance on how to apply hackathons for organizational innovation processes….(More)”.

Governing Complexity: Analyzing and Applying Polycentricity

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Book edited by Andreas Thiel, William A. Blomquist, and Dustin E. Garrick: “There has been a rapid expansion of academic interest and publications on polycentricity. In the contemporary world, nearly all governance situations are polycentric, but people are not necessarily used to thinking this way. Governing Complexity provides an updated explanation of the concept of polycentric governance. The editors provide examples of it in contemporary settings involving complex natural resource systems, as well as a critical evaluation of the utility of the concept. With contributions from leading scholars in the field, this book makes the case that polycentric governance arrangements exist and it is possible for polycentric arrangements to perform well, persist for long periods, and adapt. Whether they actually function well, persist, or adapt depends on multiple factors that are reviewed and discussed, both theoretically and with examples from actual cases….(More)”.

After Technopoly

Curated on Posted on by Stefaan Verhulst

Alan Jacobs at the New Atlantis: “Technocratic solutionism is dying. To replace it, we must learn again the creation and reception of myth….
What Neil Postman called “technopoly” may be described as the universal and virtually inescapable rule of our everyday lives by those who make and deploy technology, especially, in this moment, the instruments of digital communication. It is difficult for us to grasp what it’s like to live under technopoly, or how to endure or escape or resist the regime. These questions may best be approached by drawing on a handful of concepts meant to describe a slightly earlier stage of our common culture.

First, following on my earlier essay in these pages, “Wokeness and Myth on Campus” (Summer/Fall 2017), I want to turn again to a distinction by the Polish philosopher Leszek Kołakowski between the “technological core” of culture and the “mythical core” — a distinction he believed is essential to understanding many cultural developments.

“Technology” for Kołakowski is something broader than we usually mean by it. It describes a stance toward the world in which we view things around us as objects to be manipulated, or as instruments for manipulating our environment and ourselves. This is not necessarily meant in a negative sense; some things ought to be instruments — the spoon I use to stir my soup — and some things need to be manipulated — the soup in need of stirring. Besides tools, the technological core of culture includes also the sciences and most philosophy, as those too are governed by instrumental, analytical forms of reasoning by which we seek some measure of control.

By contrast, the mythical core of culture is that aspect of experience that is not subject to manipulation, because it is prior to our instrumental reasoning about our environment. Throughout human civilization, says Kołakowski, people have participated in myth — they may call it “illumination” or “awakening” or something else — as a way of connecting with “nonempirical unconditioned reality.” It is something we enter into with our full being, and all attempts to describe the experience in terms of desire, will, understanding, or literal meaning are ways of trying to force the mythological core into the technological core by analyzing and rationalizing myth and pressing it into a logical order. This is why the two cores are always in conflict, and it helps to explain why rational argument is often a fruitless response to people acting from the mythical core….(More)”.

How technology can enable a more sustainable agriculture industry

Curated on Posted on by Stefaan Verhulst

Matt High at CSO:”…The sector also faces considerable pressure in terms of its transparency, largely driven by shifting consumer preferences for responsibly sourced and environmentally-friendly goods. The UK, for example, has seen shoppers transition away from typical agricultural commodities towards ‘free-from’ or alternative options that combine health, sustainability and quality.

It means that farmers worldwide must work harder and smarter in embedding corporate social responsibility (CSR) practices into their operations. Davis, who through Anthesis delivers financially driven sustainability strategies, strongly believes that sustainability is no longer a choice. “The agricultural sector is intrinsic to a wide range of global systems, societies and economies,” he says, adding that those organisations that do not embed sustainability best practice into their supply chains will face “increasing risk of price volatility, security of supply, commodity shortages, fraud and uncertainty.” To counter this, he urges businesses to develop CSR founded on a core set of principles that enable sustainable practices to be successfully adopted at a pace and scale that mitigates those risks discussed.

Data is proving a particularly useful tool in this regard. Take the Cool Farm Tool, for example, which is a global, free-to-access online greenhouse gas (GHG), water and biodiversity footprint calculator used by farmers in more than 115 countries worldwide to enable effective management of critical on-farm sustainability challenges. Member organisations such as Pepsi, Tesco and Danone aggregate their supply chain data to report total agricultural footprint against key sustainability metrics – outputs from which are used to share knowledge and best practice on carbon and water reductions strategies….(More)”.

Data Management Law for the 2020s: The Lost Origins and the New Needs

Curated on Posted on by Stefaan Verhulst

Paper by Przemysław Pałka: “In the data analytics society, each individual’s disclosure of personal information imposes costs on others. This disclosure enables companies, deploying novel forms of data analytics, to infer new knowledge about other people and to use this knowledge to engage in potentially harmful activities. These harms go beyond privacy and include difficult to detect price discrimination, preference manipulation, and even social exclusion. Currently existing, individual-focused, data protection regimes leave law unable to account for these social costs or to manage them. 

This Article suggests a way out, by proposing to re-conceptualize the problem of social costs of data analytics through the new frame of “data management law.” It offers a critical comparison of the two existing models of data governance: the American “notice and choice” approach and the European “personal data protection” regime (currently expressed in the GDPR). Tracing their origin to a single report issued in 1973, the article demonstrates how they developed differently under the influence of different ideologies (market-centered liberalism, and human rights, respectively). It also shows how both ultimately failed at addressing the challenges outlined already forty-five years ago. 

To tackle these challenges, this Article argues for three normative shifts. First, it proposes to go beyond “privacy” and towards “social costs of data management” as the framework for conceptualizing and mitigating negative effects of corporate data usage. Second, it argues to go beyond the individual interests, to account for collective ones, and to replace contracts with regulation as the means of creating norms governing data management. Third, it argues that the nature of the decisions about these norms is political, and so political means, in place of technocratic solutions, need to be employed….(More)”.

The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism

Curated on Posted on by Stefaan Verhulst

Book by Nick Couldry: “We are told that progress requires human beings to be connected, and that science, medicine and much else that is good demands the kind massive data collection only possible if every thing and person are continuously connected.

But connection, and the continuous surveillance that connection makes possible, usher in an era of neocolonial appropriation. In this new era, social life becomes a direct input to capitalist production, and data – the data collected and processed when we are connected – is the means for this transformation. Hence the need to start counting the costs of connection.

Capturing and processing social data is today handled by an emerging social quantification sector. We are familiar with its leading players, from Acxiom to Equifax, from Facebook to Uber. Together, they ensure the regular and seemingly natural conversion of daily life into a stream of data that can be appropriated for value. This stream is extracted from sensors embedded in bodies and objects, and from the traces left by human interaction online. The result is a new social order based on continuous tracking, and offering unprecedented new opportunities for social discrimination and behavioral influence.  This order has disturbing consequences for freedom, justice and power — indeed, for the quality of human life.

The true violence of this order is best understood through the history of colonialism. But because we assume that colonialism has been replaced by advanced capitalism, we often miss the connection. The concept of data colonialism can thus be used to trace continuities from colonialism’s historic appropriation of territories and material resources to the datafication of everyday life today. While the modes, intensities, scales and contexts of dispossession have changed, the underlying function remains the same: to acquire resources from which economic value can be extracted.

In data colonialism, data is appropriated through a new type of social relation: data relations. We are living through a time when the organization of capital and the configurations of power are changing dramatically because of this contemporary form of social relation. Data colonialism justifies what it does as an advance in scientific knowledge, personalized marketing, or rational management, just as historic colonialism claimed a civilizing mission. Data colonialism is global, dominated by powerful forces in East and West, in the USA and China. The result is a world where, wherever we are connected, we are colonized by data.

Where is data colonialism heading in the long term? Just as historical colonialism paved the way for industrial capitalism, data colonialism is paving the way for a new stage of capitalism whose outlines we only partly see: the capitalization of life without limit. There will be no part of human life, no layer of experience, that is not extractable for economic value. Human life will be there for mining by corporations without reserve as governments look on appreciatively. This process of capitalization will be the foundation for a highly unequal new social arrangement, a social order that is deeply incompatible with human freedom and autonomy.

But resistance is still possible, drawing on past and present decolonial struggles, as well as the on the best of the humanities, philosophy, political economy, information and social science. The goal is to name what is happening and imagine better ways of living together without the exploitation on which today’s models of ‘connection’ are founded….(More)”

Tackling Climate Change with Machine Learning

Curated on Posted on by Stefaan Verhulst

Paper by David Rolnick et al: “Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change….(More)”.

Guidance Note: Statistical Disclosure Control

Curated on Posted on by Stefaan Verhulst

Centre for Humanitarian Data: “Survey and needs assessment data, or what is known as ‘microdata’, is essential for providing adequate response to crisis-affected people. However, collecting this information does present risks. Even as great effort is taken to remove unique identifiers such as names and phone numbers from microdata so no individual persons or communities are exposed, combining key variables such as location or ethnicity can still allow for re-identification of individual respondents. Statistical Disclosure Control (SDC) is one method for reducing this risk. 

The Centre has developed a Guidance Note on Statistical Disclosure Control that outlines the steps involved in the SDC process, potential applications for its use, case studies and key actions for humanitarian data practitioners to take when managing sensitive microdata. Along with an overview of what SDC is and what tools are available, the Guidance Note outlines how the Centre is using this process to mitigate risk for datasets shared on HDX. …(More)”.

Innovation Beyond Technology: Science for Society and Interdisciplinary Approaches

Curated on Posted on by Stefaan Verhulst

Book edited by Sébastien Lechevalier: ” The major purpose of this book is to clarify the importance of non-technological factors in innovation to cope with contemporary complex societal issues while critically reconsidering the relations between science, technology, innovation (STI), and society. For a few decades now, innovation—mainly derived from technological advancement—has been considered a driving force of economic and societal development and prosperity.

With that in mind, the following questions are dealt with in this book: What are the non-technological sources of innovation? What can the progress of STI bring to humankind? What roles will society be expected to play in the new model of innovation? The authors argue that the majority of so-called technological innovations are actually socio-technical innovations, requiring huge resources for financing activities, adapting regulations, designing adequate policy frames, and shaping new uses and new users while having the appropriate interaction with society.

This book gathers multi- and trans-disciplinary approaches in innovation that go beyond technology and take into account the inter-relations with social and human phenomena. Illustrated by carefully chosen examples and based on broad and well-informed analyses, it is highly recommended to readers who seek an in-depth and up-to-date integrated overview of innovation in its non-technological dimensions….(More)”.

Bringing machine learning to the masses

Curated on Posted on by Stefaan Verhulst

Matthew Hutson at Science: “Artificial intelligence (AI) used to be the specialized domain of data scientists and computer programmers. But companies such as Wolfram Research, which makes Mathematica, are trying to democratize the field, so scientists without AI skills can harness the technology for recognizing patterns in big data. In some cases, they don’t need to code at all. Insights are just a drag-and-drop away. One of the latest systems is software called Ludwig, first made open-source by Uber in February and updated last week. Uber used Ludwig for projects such as predicting food delivery times before releasing it publicly. At least a dozen startups are using it, plus big companies such as Apple, IBM, and Nvidia. And scientists: Tobias Boothe, a biologist at the Max Planck Institute of Molecular Cell Biology and Genetics in Dresden, Germany, uses it to visually distinguish thousands of species of flatworms, a difficult task even for experts. To train Ludwig, he just uploads images and labels….(More)”.