Should Consumers Be Able to Sell Their Own Personal Data?

Curated on Posted on by Stefaan Verhulst

The Wall Street Journal: “People around the world are confused and concerned about what companies do with the data they collect from their interactions with consumers.

A global survey conducted last fall by the research firm Ipsos gives a sense of the scale of people’s worries and uncertainty. Roughly two-thirds of those surveyed said they knew little or nothing about how much data companies held about them or what companies did with that data. And only about a third of respondents on average said they had at least a fair amount of trust that a variety of corporate and government organizations would use the information they had about them in the right way….

Christopher Tonetti, an associate professor of economics at Stanford Graduate School of Business, says consumers should own and be able to sell their personal data. Cameron F. Kerry, a visiting fellow at the Brookings Institution and former general counsel and acting secretary of the U.S. Department of Commerce, opposes the idea….

YES: It Would Encourage Sharing of Data—a Plus for Consumers and Society…Data isn’t like other commodities in one fundamental way—it doesn’t diminish with use. And that difference is the key to why consumers should own the data that’s created when they interact with companies, and have the right to sell it.YES: It Would Encourage Sharing of Data—a Plus for Consumers and Society…

NO: It Would Do Little to Help Consumers, and Could Leave Them Worse Off Than Now…

But owning data will do little to help consumers’ privacy—and may well leave them worse off. Meanwhile, consumer property rights would create enormous friction for valid business uses of personal information and for the free flow of information we value as a society.

In our current system, consumers reflexively click away rights to data in exchange for convenience, free services, connection, endorphins or other motivations. In a market where consumers could sell or license personal information they generate from web browsing, ride-sharing apps and other digital activities, is there any reason to expect that they would be less motivated to share their information? …(More)”.

Linked Democracy: Foundations, Tools, and Applications

Curated on Posted on by Stefaan Verhulst

Book edited by Marta Poblet, Pompeu Casanovas and Víctor Rodríguez-Doncel: “This open access book shows the factors linking information flow, social intelligence, rights management and modelling with epistemic democracy, offering licensed linked data along with information about the rights involved. This model of democracy for the web of data brings new challenges for the social organisation of knowledge, collective innovation, and the coordination of actions. Licensed linked data, licensed linguistic linked data, right expression languages, semantic web regulatory models, electronic institutions, artificial socio-cognitive systems are examples of regulatory and institutional design (regulations by design). The web has been massively populated with both data and services, and semantically structured data, the linked data cloud, facilitates and fosters human-machine interaction. Linked data aims to create ecosystems to make it possible to browse, discover, exploit and reuse data sets for applications. Rights Expression Languages semi-automatically regulate the use and reuse of content…(More)”.

Official Statistics 4.0: Verified Facts for People in the 21st Century

Curated on Posted on by Stefaan Verhulst

Book by Walter J. Radermacher: “This book explores official statistics and their social function in modern societies. Digitisation and globalisation are creating completely new opportunities and risks, a context in which facts (can) play an enormously important part if they are produced with a quality that makes them credible and purpose-specific. In order for this to actually happen, official statistics must continue to actively pursue the modernisation of their working methods.This book is not about the technical and methodological challenges associated with digitisation and globalisation; rather, it focuses on statistical sociology, which scientifically deals with the peculiarities and pitfalls of governing-by-numbers, and assigns statistics a suitable position in the future informational ecosystem. Further, the book provides a comprehensive overview of modern issues in official statistics, embodied in a historical and conceptual framework that endows it with different and innovative perspectives. Central to this work is the quality of statistical information provided by official statistics. The implementation of the UN Sustainable Development Goals in the form of indicators is another driving force in the search for answers, and is addressed here….(More)”.

The Economics of Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Book edited by Ajay Agrawal, Joshua Gans and Avi Goldfarb: “Advances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI.

It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted. It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions…. (More)”

Data gaps threaten achievement of development goals in Africa

Curated on Posted on by Stefaan Verhulst

Sara Jerving at Devex: “Data gaps across the African continent threaten to hinder the achievement of the Sustainable Development Goals and the African Union’s Agenda 2063, according to the Mo Ibrahim Foundation’s first governance report released on Tuesday.

The report, “Agendas 2063 & 2030: Is Africa On Track?“ based on an analysis of the foundation’s Ibrahim index of African governance, found that since the adoption of both of these agendas, the availability of public data in Africa has declined. With data focused on social outcomes, there has been a notable decline in education, population and vital statistics, such as birth and death records, which allow citizens to access public services.

The index, on which the report is based, is the most comprehensive dataset on African governance, drawing on ten years of data of all 54 African nations. An updated index is released every two years….

The main challenge in the production of quality, timely data, according to the report, is a lack of funding and lack of independence of the national statistical offices.

Only one country, Mauritius, had a perfect score in terms of independence of its national statistics office – meaning that its office can collect the data it chooses, publish without approval from other arms of the government, and is sufficiently funded. Fifteen African nations scored zero in terms of the independence of their offices….(More)”.

Road Traffic Accidents Analysis in Mexico City through Crowdsourcing Data and Data Mining Techniques

Curated on Posted on by Stefaan Verhulst

Paper by Gabriela V. Angeles et al: “Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current.

However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze.

The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS….(More)”.

Data Power: tactics, access and shaping

Curated on Posted on by Stefaan Verhulst

Introduction to the Data Power Special Issue of Online Information Review by Ysabel Gerrard and Jo Bates : “…The Data Power Conference 2017, and by extension the seven papers in this Special Issue, addressed three questions:

  1. How can we reclaim some form of data-based power and autonomy, and advance data-based technological citizenship, while living in regimes of data power?
  2. Is it possible to regain agency and mobilise data for the common good? To do so, which theories help to interrogate and make sense of the operations of data power?
  3. What kind of design frameworks are needed to build and deploy data-based technologies with values and ethics that are equitable and fair? How can big data be mobilised to improve how we live, beyond notions of efficiency and innovation?

These questions broadly emphasise the reclamation of power, retention of agency and ethics of data-based technologies, and they reflect a broader moment in recent data studies scholarship. While early critical research on “big data” – a term that captures the technologies, analytics and mythologies of increasingly large data sets (Boyd and Crawford, 2012) – could only hypothesise the inequalities and deepened forms discrimination that might emerge as data sets grew in volume, many of those predictions have now become real. The articles in this Special Issue ask pressing questions about data power at a time when we have learned that data are too frequently handled in a way that deepens social inequalities and injustices (amongst others, Eubanks, 2018; Noble, 2018).

The papers in this Special Issue approach discussions of inequality and injustice through three broad lenses: the tactics people use to confront unequal distributions of (data) power; the access to data that are most relevant and essential for particular social groups, coupled with the changing and uncertain legalities of data access; and the shaping of social relations by and through data, whether through the demands placed on app users to disclose more personal information, the use of data to construct cultures of compliance or through the very methodologies commonly used to organise and label information. While these three themes do not exhaustively capture the range of topics addressed in this Special Issue, at the Data Power Conferences, or within the field at large, they represent an emphasis within data studies scholarship on shedding light on the most pressing issues confronting our increasingly datafied world…(More)”.

Contracting for Personal Data

Curated on Posted on by Stefaan Verhulst

Paper by Kevin E. Davis and Florencia Marotta-Wurgler: “Is contracting for the collection, use, and transfer of data like contracting for the sale of a horse or a car or licensing a piece of software? Many are concerned that conventional principles of contract law are inadequate when some consumers may not know or misperceive the full consequences of their transactions. Such concerns have led to proposals for reform that deviate significantly from general rules of contract law. However, the merits of these proposals rest in part on testable empirical claims.

We explore some of these claims using a hand-collected data set of privacy policies that dictate the terms of the collection, use, transfer, and security of personal data. We explore the extent to which those terms differ across markets before and after the adoption of the General Data Protection Regulation (GDPR). We find that compliance with the GDPR varies across markets in intuitive ways, indicating that firms take advantage of the flexibility offered by a contractual approach even when they must also comply with mandatory rules. We also compare terms offered to more and less sophisticated subjects to see whether firms may exploit information barriers by offering less favorable terms to more vulnerable subjects….(More)”.

From smart to rebel city? Worlding, provincialising and the Barcelona Model

Curated on Posted on by Stefaan Verhulst

Paper by Greig Charnock, Hug March, Ramon Ribera-Fumaz: “This article examines the evolution of the ‘Barcelona Model’ of urban transformation through the lenses of worlding and provincialising urbanism. We trace this evolution from an especially dogmatic worlding vision of the smart city, under a centre-right city council, to its radical repurposing under the auspices of a municipal government led, after May 2015, by the citizens’ platform Barcelona en Comú. We pay particular attention to the new council’s objectives to harness digital platform technologies to enhance participative democracy, and its agenda to secure technological sovereignty and digital rights for its citizens. While stressing the progressive intent of these aims, we also acknowledge the challenge of going beyond the repurposing of smart technologies so as to engender new and radical forms of subjectivity among citizens themselves; a necessary basis for any urban revolution….(More)”.

How to ensure that your data science is inclusive

Curated on Posted on by Stefaan Verhulst

Blog by Samhir Vasdev: “As a new generation of data scientists emerges in Africa, they will encounter relatively little trusted, accurate, and accessible data upon which to apply their skills. It’s time to acknowledge the limitations of the data sources upon which data science relies, particularly in lower-income countries.

The potential of data science to support, measure, and amplify sustainable development is undeniable. As public, private, and civic institutions around the world recognize the role that data science can play in advancing their growth, an increasingly robust array of efforts has emerged to foster data science in lower-income countries.

This phenomenon is particularly salient in Sub-Saharan Africa. There, foundations are investing millions into building data literacy and data science skills across the continent. Multilaterals and national governments are pioneering new investments into data science, artificial intelligence, and smart cities. Private and public donors are building data science centers to build cohorts of local, indigenous data science talent. Local universities are launching graduate-level data science courses.

Despite this progress, among the hype surrounding data science rests an unpopular and inconvenient truth: As a new generation of data scientists emerges in Africa, they will encounter relatively little trusted, accurate, and accessible data that they can use for data science.

We hear promises of how data science can help teachers tailor curricula according to students’ performances, but many school systems don’t collect or track that performance data with enough accuracy and timeliness to perform those data science–enabled tweaks. We believe that data science can help us catch disease outbreaks early, but health care facilities often lack the specific data, like patient origin or digitized information, that is needed to discern those insights.

These fundamental data gaps invite the question: Precisely what data would we perform data science on to achieve sustainable development?…(More)”.