A distributed model for internet governance

Global Partners Digital: “Across the world, increased internet adoption has radically altered people’s lives – creating the need for new methods of internet governance that are more effective, flexible, inclusive, and legitimate. Conversations about reforming the internet governance ecosystem are already taking place at the CSTD Working Group on Enhanced Cooperation, and within the wider IGF community.

A new paper by GovLab co-founder and GPD Advisory Board member Stefaan Verhulst – A distributed model for internet governance – seeks to contribute to this evolving debate by proposing a distributed yet coordinated framework for internet governance – one which accommodates existing and emerging decision-making approaches, while also enabling broader participation by a wider range of institutions and actors….(More)”

Big Data: A New Empiricism and its Epistemic and Socio-Political Consequences

Chapter by Gernot Rieder and Judith Simon in by Berechenbarkeit der Welt? Philosophie und Wissenschaft im Zeitalter von Big Data: “…paper investigates the rise of Big Data in contemporary society. It examines the most prominent epistemological claims made by Big Data proponents, calls attention to the potential socio-political consequences of blind data trust, and proposes a possible way forward. The paper’s main focus is on the interplay between an emerging new empiricism and an increasingly opaque algorithmic environment that challenges democratic demands for transparency and accountability. It concludes that a responsible culture of quantification requires epistemic vigilance as well as a greater awareness of the potential dangers and pitfalls of an ever more data-driven society….(More)”.

Data Collaboratives: exchanging data to create public value across Latin America and the Caribbean

Stefaan Verhulst, Andrew Young and Prianka Srinivasan at IADB’s Abierto al Publico: “Data is playing an ever-increasing role in bolstering businesses across Latin America – and the rest of the word. In Brazil, Mexico and Colombia alone, the revenue from Big Data is calculated at more than US$603.7 million, a market that is only set to increase as more companies across Latin America and the Caribbean embrace data-driven strategies to enhance their bottom-line. Brazilian banking giant Itau plans to create six data centers across the country, and already uses data collected from consumers online to improve cross-selling techniques and streamline their investments. Data from web-clicks, social media profiles, and telecommunication services is fueling a new generation of entrepreneurs keen to make big dollars from big data.

What if this same data could be used not just to improve business, but to improve the collective well-being of our communities, public spaces, and cities? Analysis of social media data can offer powerful insights to city officials into public trends and movements to better plan infrastructure and policies. Public health officials and humanitarian workers can use mobile phone data to, for instance, map human mobility and better target their interventions. By repurposing the data collected by companies for their business interests, governments, international organizations and NGOs can leverage big data insights for the greater public good.

Key question is thus: How to unlock useful data collected by corporations in a responsible manner and ensure its vast potential does not go to waste?

Data Collaboratives” are emerging as a possible answer. Data collaboratives are a new type of public-private partnerships aimed at creating public value by exchanging data across sectors.

Research conducted by the GovLab finds that Data Collaboratives offer several potential benefits across a number of sectors, including humanitarian and anti-poverty efforts, urban planning, natural resource stewardship, health, and disaster management. As a greater number of companies in Latin America look to data to spur business interests, our research suggests that some companies are also sharing and collaborating around data to confront some of society’s most pressing problems.

Consider the following Data Collaboratives that seek to enhance…(More)”

Data collaboratives as “bazaars”? A review of coordination problems and mechanisms to match demand for data with supply

Iryna Susha , Marijn Janssen , and Stefaan Verhulst in Transforming Government: People, Process and Policy: “In “data collaboratives” private and public organizations coordinate their activities to leverage data to address a societal challenge. This paper focuses on analyzing challenges and coordination mechanisms of data collaboratives….This study uses coordination theory to identify and discuss the coordination problems and coordination mechanisms associated with data collaboratives. We also use a taxonomy of data collaborative forms from a previous empirical study to discuss how different forms of data collaboratives may require different coordination mechanisms….

The study analyzed data collaboratives from the perspective of organizational and task levels. At the organizational level we argue that data collaboratives present an example of the bazaar form of coordination. At the task level we identified five coordination problems and discussed potential coordination mechanisms to address them, such as coordination by negotiation, by third party, by standardization, to name a few…This study is one of the first few to systematically analyze the phenomenon of “data collaboratives”.

…can help practitioners understand better the coordination challenges they may face when initiating a data collaborative and to develop successful data collaboratives by using coordination mechanisms to mitigate these challenges…(More)”

Corporate Social Responsibility for a Data Age

Stefaan G. Verhulst in the Stanford Social Innovation Review: “Proprietary data can help improve and save lives, but fully harnessing its potential will require a cultural transformation in the way companies, governments, and other organizations treat and act on data….

We live, as it is now common to point out, in an era of big data. The proliferation of apps, social media, and e-commerce platforms, as well as sensor-rich consumer devices like mobile phones, wearable devices, commercial cameras, and even cars generate zettabytes of data about the environment and about us.

Yet much of the most valuable data resides with the private sector—for example, in the form of click histories, online purchases, sensor data, and call data records. This limits its potential to benefit the public and to turn data into a social asset. Consider how data held by business could help improve policy interventions (such as better urban planning) or resiliency at a time of climate change, or help design better public services to increase food security.

Data responsibility suggests steps that organizations can take to break down these private barriers and foster so-called data collaboratives, or ways to share their proprietary data for the public good. For the private sector, data responsibility represents a new type of corporate social responsibility for the 21st century.

While Nepal’s Ncell belongs to a relatively small group of corporations that have shared their data, there are a few encouraging signs that the practice is gaining momentum. In Jakarta, for example, Twitter exchanged some of its data with researchers who used it to gather and display real-time information about massive floods. The resulting website, PetaJakarta.org, enabled better flood assessment and management processes. And in Senegal, the Data for Development project has brought together leading cellular operators to share anonymous data to identify patterns that could help improve health, agriculture, urban planning, energy, and national statistics.

Examples like this suggest that proprietary data can help improve and save lives. But to fully harness the potential of data, data holders need to fulfill at least three conditions. I call these the “the three pillars of data responsibility.”…

The difficulty of translating insights into results points to some of the larger social, political, and institutional shifts required to achieve the vision of data responsibility in the 21st century. The move from data shielding to data sharing will require that we make a cultural transformation in the way companies, governments, and other organizations treat and act on data. We must incorporate new levels of pro-activeness, and make often-unfamiliar commitments to transparency and accountability.

By way of conclusion, here are four immediate steps—essential but not exhaustive—we can take to move forward:

  1. Data holders should issue a public commitment to data responsibility so that it becomes the default—an expected, standard behavior within organizations.
  2. Organizations should hire data stewards to determine what and when to share, and how to protect and act on data.
  3. We must develop a data responsibility decision tree to assess the value and risk of corporate data along the data lifecycle.
  4. Above all, we need a data responsibility movement; it is time to demand data responsibility to ensure data improves and safeguards people’s lives…(More)”

DataCollaboratives.org – A New Resource on Creating Public Value by Exchanging Data

Recent years have seen exponential growth in the amount of data being generated and stored around the world. There is increasing recognition that this data can play a key role in solving some of the most difficult public problems we face.

However, much of the potentially useful data is currently privately held and not available for public insights. Data in the form of web clicks, social “likes,” geo location and online purchases are typically tightly controlled, usually by entities in the private sector. Companies today generate an ever-growing stream of information from our proliferating sensors and devices. Increasingly, they—and various other actors—are asking if there is a way to make this data available for the public good. There is an ongoing search for new models of corporate responsibility in the digital era around data toward the creation of “data collaboratives”.

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Today, the GovLab is excited to launch a new resource for Data Collaboratives (datacollaboratives.org). Data Collaboratives are an emerging form of public-private partnership in which participants from different sectors — including private companies, research institutions, and government agencies — exchange data to help solve public problems.

The resource results from different partnerships with UNICEF (focused on creating data collaboratives to improve children’s lives) and Omidyar Network (studying new ways to match (open) data demand and supply to increase impact).

Natalia Adler, a data, research and policy planning specialist and the UNICEF Data Collaboratives Project Lead notes, “At UNICEF, we’re dealing with the world’s most complex problems affecting children. Data Collaboratives offer an exciting opportunity to tap on previously inaccessible datasets and mobilize a wide range of data expertise to advance child rights around the world. It’s all about connecting the dots.”

To better understand the potential of these Collaboratives, the GovLab collected information on dozens of examples from across the world. These many and diverse initiatives clearly suggest the potential of Data Collaboratives to improve people’s lives when done responsibly. As Stefaan Verhulst, co-founder of the GovLab, puts it: “In the coming months and years, Data Collaboratives will be essential vehicles for harnessing the vast stores of privately held data toward the public good.”

In particular, our research to date suggests that Data Collaboratives offer a number of potential benefits, including enhanced:

  • Situational Awareness and Response: For example, Orbital Insights and the World Bank are using satellite imagery to measure and track poverty. This technology can, in some instances, “be more accurate than U.S. census data.”
  • Public Service Design and Delivery: Global mapping company, Esri, and Waze’s Connected Citizen’s program are using crowdsourced traffic information to help governments design better transportation.
  • Impact Assessment and Evaluation: Nielsen and the World Food Program (WFP) have been using data collected via mobile phone surveys to better monitor food insecurity in order to advise the WFP’s resource allocations….(More)

Data Collaboratives as a New Frontier of Cross-Sector Partnerships in the Age of Open Data: Taxonomy Development

Paper by Iryna Susha, Marijn Janssen and Stefaan Verhulst: “Data collaboratives present a new form of cross-sector and public-private partnership to leverage (often corporate) data for addressing a societal challenge. They can be seen as the latest attempt to make data accessible to solve public problems. Although an increasing number of initiatives can be found, there is hardly any analysis of these emerging practices. This paper seeks to develop a taxonomy of forms of data collaboratives. The taxonomy consists of six dimensions related to data sharing and eight dimensions related to data use. Our analysis shows that data collaboratives exist in a variety of models. The taxonomy can help organizations to find a suitable form when shaping their efforts to create public value from corporate and other data. The use of data is not only dependent on the organizational arrangement, but also on aspects like the type of policy problem, incentives for use, and the expected outcome of data collaborative….(More)”

The Centre for Humanitarian Data

Centre for HumData: “The United Nations Office for the Coordination of Humanitarian Affairs (OCHA) is establishing a Centre for Humanitarian Data in the Netherlands. It will be operational by early 2017 for an initial three years.

The Centre’s mission is to increase the use and impact of data in the humanitarian sector. The vision is to create a future where all people involved in a humanitarian situation have access to the data they need, when and how they need it, to make responsible and informed decisions.

The Centre will support humanitarian partners and OCHA staff in the field and at headquarters with their data efforts. It will be part of the city of The Hague’s Humanity Hub, a dedicated building for organizations working on data and innovation in the social sector. The location offers OCHA and partners a new, neutral setting where a hybrid culture can be created around data collaboration.

The Centre is a key contribution towards the Secretary-General’s Agenda for Humanity under core commitment four — changing the way we work to end need. The Centre’s activities will accelerate the changes required for the humanitarian system to become data driven….(More)”

The ethical impact of data science

Theme issue of Phil. Trans. R. Soc. A compiled and edited by Mariarosaria Taddeo and Luciano Floridi: “This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data ethics builds on the foundation provided by computer and information ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the level of abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations—the interactions among hardware, software and data—rather than on the variety of digital technologies that enable them. And it emphasizes the complexity of the ethical challenges posed by data science. Because of such complexity, data ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework. Only as a macroethics will data ethics provide solutions that can maximize the value of data science for our societies, for all of us and for our environments….(More)”

Table of Contents:

  • The dynamics of big data and human rights: the case of scientific research; Effy Vayena, John Tasioulas
  • Facilitating the ethical use of health data for the benefit of society: electronic health records, consent and the duty of easy rescue; Sebastian Porsdam Mann, Julian Savulescu, Barbara J. Sahakian
  • Faultless responsibility: on the nature and allocation of moral responsibility for distributed moral actions; Luciano Floridi
  • Compelling truth: legal protection of the infosphere against big data spills; Burkhard Schafer
  • Locating ethics in data science: responsibility and accountability in global and distributed knowledge production systems; Sabina Leonelli
  • Privacy is an essentially contested concept: a multi-dimensional analytic for mapping privacy; Deirdre K. Mulligan, Colin Koopman, Nick Doty
  • Beyond privacy and exposure: ethical issues within citizen-facing analytics; Peter Grindrod
  • The ethics of smart cities and urban science; Rob Kitchin
  • The ethics of big data as a public good: which public? Whose good? Linnet Taylor
  • Data philanthropy and the design of the infraethics for information societies; Mariarosaria Taddeo
  • The opportunities and ethics of big data: practical priorities for a national Council of Data Ethics; Olivia Varley-Winter, Hetan Shah
  • Data science ethics in government; Cat Drew
  • The ethics of data and of data science: an economist’s perspective; Jonathan Cave
  • What’s the good of a science platform? John Gallacher


How Companies Can Help Cities Close the Data Gap

Shamina Singh in Governing: “Recent advances in data analytics have revolutionized the way many companies do business. Starbucks, for example, rolls out new beverages and chooses its store locations by analyzing customer, economic and other data. And as Amazon’s customers know so well, the company makes purchase recommendations to them in real time based on items they’ve viewed or bought. So why aren’t more of our cities leveraging data in the same way to improve services for their residents?

According to a recent report by Bloomberg Philanthropies’ What Works Cities initiative, city officials say they simply lack the capacity to do so. Nearly half pointed to a shortage of staff and financial resources dedicated to gathering and evaluating data.

This gap between companies’ and cities’ ability to use data is not surprising. Businesses have invested heavily in data and analytics in recent years, and they are spending an average of $7 million annually per company on data-related activities. These investments are made with the understanding that they will improve the companies’ bottom line, and they have started paying off.

City halls, on the other hand, find themselves hamstrung when it comes to investing in data and analytics. Despite recent growth, city revenues remain below pre-recession levels, with spending demands on the rise. Furthermore, many cities face the need to balance long-term opportunity with real short-term needs. Do you hire a data scientist — who may command a salary north of $200,000 — to research strategies to reduce crime in the long run, or do you hire more police officers to keep neighborhoods safe today?….

One way companies can help is through data philanthropy, leveraging their data analytics and capabilities to advance social progress. A step beyond conventional philanthropy and traditional corporate social-responsibility initiatives, data philanthropy is a new kind of response to social issues.

There are a number of ways cities could employ data philanthropy. For starters, they could partner with relevant apps to help ameliorate deteriorating roads. In Oklahoma City, for example, potholes are a particularly serious problem. Data from Waze, the community-based mapping and navigation app, could be leveraged to build a system through which residents could report potholes, allowing city services to efficiently fill them in.

Some data-philanthropy projects are already underway. Uber, for example, recently partnered with the city of Boston in the hopes that its data could help the city improve traffic congestion and community planning. Uber donates anonymized trip data by Zip code, allowing city officials to see the date and time of a trip, its duration and distance traveled. Boston’s transportation, neighborhood development and redevelopment agencies will have access to the data, equipping them with a new tool for more-effective policymaking.

While there is demonstrated enthusiasm from cities for more effective use of data to improve their residents’ lives, cities won’t be able to close the data gap on their own. Private-sector companies must answer the call. Helped in part by the better use of data, cities can create improved, more inclusive and stronger business environments. Who would argue with that goal?…(More)”