Stefaan Verhulst
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)”.
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)”.
Karolina Mackiewicz at ICT & Health: “…Better innovation opportunities, quicker access to comprehensive ready-combined data, smoother permit procedures needed for research – those are some of the benefits for society, academia or business announced by the Ministry of Social Affairs and Health of Finland when the Act on the Secondary Use of Health and Social Data was introduced.
It came into force on 1st of May 2019. According to the Finnish Innovation Fund SITRA, which was involved in the development of the legislation and carried out the pilot projects, it’s a ‘groundbreaking’ piece of legislation. It’ not only effectively introduces a one-stop-shop for data but it’s also one of the first, if not the first, implementations of the GDPR (the EU’s General Data Protection Regulation) for the secondary use of data in Europe.
The aim of the Act is “to facilitate the effective and safe processing and access to the personal social and health data for steering, supervision, research, statistics and development in the health and social sector”. A second objective is to guarantee an individual’s legitimate expectations as well as their rights and freedoms when processing personal data. In other words, the Ministry of Health promises that the Act will help eliminate the administrative burden in access to the data by the researchers and innovative businesses while respecting the privacy of individuals and providing conditions for the ethically sustainable way of using data….(More)”.
Blog post by Cassie Kozyrkov: “…Decision intelligence is a new academic discipline concerned with all aspects of selecting between options. It brings together the best of applied data science, social science, and managerial science into a unified field that helps people use data to improve their lives, their businesses, and the world around them. It’s a vital science for the AI era, covering the skills needed to lead AI projects responsibly and design objectives, metrics, and safety-nets for automation at scale.
Let’s take a tour of its basic terminology and concepts. The sections are designed to be friendly to skim-reading (and skip-reading too, that’s where you skip the boring bits… and sometimes skip the act of reading entirely).
What’s a decision?
Data are beautiful, but it’s decisions that are important. It’s through our decisions — our actions — that we affect the world around us.
We define the word “decision” to mean any selection between options by any entity, so the conversation is broader than MBA-style dilemmas (like whether to open a branch of your business in London).
In this terminology, labeling a photo as cat versus not-cat is a decision executed by a computer system, while figuring out whether to launch that system is a decision taken thoughtfully by the human leader (I hope!) in charge of the project.
What’s a decision-maker?
In our parlance, a “decision-maker” is not that stakeholder or investor who swoops in to veto the machinations of the project team, but rather the person who is responsible for decision architecture and context framing. In other words, a creator of meticulously-phrased objectives as opposed to their destroyer.
What’s decision-making?
Decision-making is a word that is used differently by different disciplines, so it can refer to:
- taking an action when there were alternative options (in this sense it’s possible to talk about decision-making by a computer or a lizard).
- performing the function of a (human) decision-maker, part of which is taking responsibility for decisions. Even though a computer system can execute a decision, it will not be called a decision-maker because it does not bear responsibility for its outputs — that responsibility rests squarely on the shoulders of the humans who created it.
Decision intelligence taxonomy
One way to approach learning about decision intelligence is to break it along traditional lines into its quantitative aspects (largely overlapping with applied data science) and qualitative aspects (developed primarily by researchers in the social and managerial sciences)….(More)”.
Report by the European Directorate-General for Parliamentary Research Services (EPRS): “Blockchain is a much-discussed instrument that, according to some, promises to inaugurate a new era of data storage and code-execution, which could, in turn, stimulate new business models and markets. The precise impact of the technology is, of course, hard to anticipate with certainty, in particular as many remain sceptical of blockchain’s potential impact. In recent times, there has been much discussion in policy circles, academia and the private sector regarding the tension between blockchain and the European Union’s General Data Protection Regulation (GDPR). Indeed, many of the points of tension between blockchain and the GDPR are due to two overarching factors.
First, the GDPR is based on an underlying assumption that in relation to each personal data point there is at least one natural or legal person – the data controller – whom data subjects can address to enforce their rights under EU data protection law. These data controllers must comply with the GDPR’s obligations. Blockchains, however, are distributed databases that often seek to achieve decentralisation by replacing a unitary actor with many different players. The lack of consensus as to how (joint-)controllership ought to be defined hampers the allocation of responsibility and accountability.
Second, the GDPR is based on the assumption that data can be modified or erased where necessary to comply with legal requirements, such as Articles 16 and 17 GDPR. Blockchains, however, render the unilateral modification of data purposefully onerous in order to ensure data integrity and to increase trust in the network. Furthermore, blockchains underline the challenges of adhering to the requirements of data minimisation and purpose limitation in the current form of the data economy.
This study examines the European data protection framework and applies it to blockchain technologies so as to document these tensions. It also highlights the fact that blockchain may help further some of the GDPR’s objectives. Concrete policy options are developed on the basis of this analysis….(More)”
Paper by Sven Schade et al: “Amplified by the phenomenon of globalisation, such as increased human mobility and the worldwide shipping of goods, we observe an increasing spread of animals and plants outside their native habitats. A few of these ‘aliens’ have negative impacts on their environment, including threats to local biodiversity, agricultural productivity, and human health. Our work addresses these threats, particularly within the European Union (EU), where a related legal framework has been established. We follow an open and participatory approach that allows more people to share their experiences of invasive alien species (IAS) in their surroundings. Over the past three years, we developed a mobile phone application, together with the underlying data management and validation infrastructure, which allows smartphone users to report a selected list of IAS. We put quality assurance and data integration mechanisms into place that allows the uptake of information into existing official systems in order to make it accessible to the relevant policy-making at EU level.
This article summarises our scientific methodology and technical approach, explains our decisions, and provides an outlook to the future of IAS monitoring involving citizens and utilising the latest technological advancements. Last but not least we emphasise on software design for reuse, within the domain of IAS monitoring, but also for supporting citizen science apps more generally. Whereas much could already be achieved, many scientific, technical and organizational challenges still remain to be addressed before data can be seamlessly shared and integrated. Here, we particularly highlight issues that emerge in an international setting, which involves many different stakeholders….(More)”.
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)”.
Book by Kris Shaffer: “Human attention is in the highest demand it has ever been. The drastic increase in available information has compelled individuals to find a way to sift through the media that is literally at their fingertips. Content recommendation systems have emerged as the technological solution to this social and informational problem, but they’ve also created a bigger crisis in confirming our biases by showing us only, and exactly, what it predicts we want to see. Data versus Democracy investigates and explores how, in the era of social media, human cognition, algorithmic recommendation systems, and human psychology are all working together to reinforce (and exaggerate) human bias. The dangerous confluence of these factors is driving media narratives, influencing opinions, and possibly changing election results.
In this book, algorithmic recommendations, clickbait, familiarity bias, propaganda, and other pivotal concepts are analyzed and then expanded upon via fascinating and timely case studies: the 2016 US presidential election, Ferguson, GamerGate, international political movements, and more events that come to affect every one of us. What are the implications of how we engage with information in the digital age? Data versus Democracy explores this topic and an abundance of related crucial questions. We live in a culture vastly different from any that has come before. In a society where engagement is currency, we are the product. Understanding the value of our attention, how organizations operate based on this concept, and how engagement can be used against our best interests is essential in responsibly equipping ourselves against the perils of disinformation….(More)”.
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)”.
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)”