Democratic Transparency in the Platform Society

Curated on Posted on by Stefaan Verhulst

Chapter by Robert Gorwa and Timothy Garton Ash: “Following an host of major scandals, transparency has emerged in recent years as one of the leading accountability mechanisms through which the companies operating global platforms for user-generated content have attempted to regain the trust of the public, politicians, and regulatory authorities. Ranging from Facebook’s efforts to partner with academics and create a reputable mechanism for third party data access and independent research to the expanded advertising disclosure tools being built for elections around the world, transparency is playing a major role in current governance debates around free expression, social media, and democracy.

This article thus seeks to (a) contextualize the recent implementation of transparency as enacted by platform companies with an overview of the ample relevant literature on digital transparency in both theory and practice; (b) consider the potential positive governance impacts of transparency as a form of accountability in the current political moment; and (c) reflect upon the potential shortfalls of transparency that should be considered by legislators, academics, and funding bodies weighing the relative benefits of policy or research dealing with transparency in this area…(More)”.

Urban Slums in a Datafying Milieu: Challenges for Data-Driven Research Practice

Curated on Posted on by Stefaan Verhulst

Paper by Bijal Brahmbhatt et al: “With the ongoing trend of urban datafication and growing use of data/evidence to shape developmental initiatives by state as well as non-state actors, this exploratory case study engages with the complex and often contested domains of data use. This study uses on-the-ground experience of working with informal settlements in Indian cities to examine how information value chains work in practice and the contours of their power to intervene in building an agenda of social justice into governance regimes. Using illustrative examples from ongoing action-oriented projects of Mahila Housing Trust in India such as the Energy Audit Project, Slum Mapping Exercise and women-led climate resilience building under the Global Resilience Partnership, it raises questions about challenges of making effective linkages between data, knowledge and action in and for slum communities in the global South by focussing on two issues.

First, it reveals dilemmas of achieving data accuracy when working with slum communities in developing cities where populations are dynamically changing, and where digitisation and use of ICT has limited operational currency. The second issue focuses on data ownership. It foregrounds the need for complementary inputs and the heavy requirement for support systems in informal settlements in order to translate data-driven knowledge into actionable forms. Absence of these will blunt the edge of data-driven community participation in local politics. Through these intersecting streams, the study attempts to address how entanglements between southern urbanism, datafication, governance and social justice diversify the discourse on data justice. It highlights existing hurdles and structural hierarchies within a data-heavy developmental register emergent across multiple cities in the global South where data-driven governmental regimes interact with convoluted urban forms and realities….(More)”.

Algorithmic Impact Assessments under the GDPR: Producing Multi-layered Explanations

Curated on Posted on by Stefaan Verhulst

Paper by Margot E. Kaminski and Gianclaudio Malgieri: “Policy-makers, scholars, and commentators are increasingly concerned with the risks of using profiling algorithms and automated decision-making. The EU’s General Data Protection Regulation (GDPR) has tried to address these concerns through an array of regulatory tools. As one of us has argued, the GDPR combines individual rights with systemic governance, towards algorithmic accountability. The individual tools are largely geared towards individual “legibility”: making the decision-making system understandable to an individual invoking her rights. The systemic governance tools, instead, focus on bringing expertise and oversight into the system as a whole, and rely on the tactics of “collaborative governance,” that is, use public-private partnerships towards these goals. How these two approaches to transparency and accountability interact remains a largely unexplored question, with much of the legal literature focusing instead on whether there is an individual right to explanation.

The GDPR contains an array of systemic accountability tools. Of these tools, impact assessments (Art. 35) have recently received particular attention on both sides of the Atlantic, as a means of implementing algorithmic accountability at early stages of design, development, and training. The aim of this paper is to address how a Data Protection Impact Assessment (DPIA) links the two faces of the GDPR’s approach to algorithmic accountability: individual rights and systemic collaborative governance. We address the relationship between DPIAs and individual transparency rights. We propose, too, that impact assessments link the GDPR’s two methods of governing algorithmic decision-making by both providing systemic governance and serving as an important “suitable safeguard” (Art. 22) of individual rights….(More)”.

Data Fiduciary in Order to Alleviate Principal-Agent Problems in the Artificial Big Data Age

Curated on Posted on by Stefaan Verhulst

Paper by Julia M. Puaschunder: “The classic principal-agent problem in political science and economics describes agency dilemmas or problems when one person, the agent, is put in a situation to make decisions on behalf of another entity, the principal. A dilemma occurs in situations when individual profit maximization or principal and agent are pitted against each other. This so-called moral hazard is nowadays emerging in the artificial big data age, when big data reaping entities have to act on behalf of agents, who provide their data with trust in the principal’s integrity and responsible big data conduct. Yet to this day, no data fiduciary has been clearly described and established to protect the agent from misuse of data. This article introduces the agent’s predicament between utility derived from information sharing and dignity in privacy as well as hyper-hyperbolic discounting fallibilities to not clearly foresee what consequences information sharing can have over time and in groups. The principal’s predicament between secrecy and selling big data insights or using big data for manipulative purposes will be outlined. Finally, the article draws a clear distinction between manipulation and nudging in relation to the potential social class division of those who nudge and those who are nudged…(More)”.

The Urban Institute Data Catalog

Curated on Posted on by Stefaan Verhulst

Data@Urban: “We believe that data make the biggest impact when they are accessible to everyone.

Today, we are excited to announce the public launch of the Urban Institute Data Catalog, a place to discover, learn about, and download open data provided by Urban Institute researchers and data scientists. You can find data that reflect the breadth of Urban’s expertise — health, education, the workforce, nonprofits, local government finances, and so much more.

Built using open source technology, the catalog holds valuable data and metadata that Urban Institute staff have created, enhanced, cleaned, or otherwise added value to as part of our work. And it will provide, for the first time, a central, searchable resource to find many of Urban’s published open data assets.

We hope that researchers, data analysts, civic tech actors, application developers, and many others will use this tool to enhance their work, save time, and generate insights that elevate the policy debate. As Urban produces data for research, analysis, and data visualization, and as new data are released, we will continue to update the catalog.

We’re thrilled to put the power of data in your hands to better understand and respond to many critical issues facing us locally and nationally. If you have comments about the tool or the data it contains, or if you would like to share examples of how you are using these data, please feel free to contact us at [email protected].

Here are some current highlights of the Urban Data Catalog — both the data and research products we’ve built using the data — as of this writing:

– LODES data: The Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) from the US Census Bureau provide detailed information on workers and jobs by census block. We have summarized these large, dispersed data into a set of census tract and census place datasets to make them easier to use. For more information, read our earlier Data@Urban blog post.

– Medicaid opioid data: Our Medicaid Spending and Prescriptions for the Treatment of Opioid Use Disorder and Opioid Overdose dataset is sourced from state drug utilization data and provides breakdowns by state, year, quarter, drug type, and brand name or generic drug status. For more information and to view our data visualization using the data, see the complete project page.

– Nonprofit and foundation data: Members of Urban’s National Center for Charitable Statistics (NCCS) compile, clean, and standardize data from the Internal Revenue Service (IRS) on organizations filing IRS forms 990 or 990-EZ, including private charities, foundations, and other tax-exempt organizations. To read more about these data, see our previous blog posts on redesigning our Nonprofit Sector in Brief Report in R and repurposing our open code and data to create your own custom summary tables….(More)”.

Nudging the Nudger: Toward a Choice Architecture for Regulators

Curated on Posted on by Stefaan Verhulst

Working Paper by Susan E. Dudley and Zhoudan Xie: “Behavioral research has shown that individuals do not always behave in ways that match textbook definitions of rationality. Recognizing that “bounded rationality” also occurs in the regulatory process and building on public choice insights that focus on how institutional incentives affect behavior, this article explores the interaction between the institutions in which regulators operate and their cognitive biases. It attempts to understand the extent to which the “choice architecture” regulators face reinforces or counteracts predictable cognitive biases. Just as behavioral insights are increasingly used to design choice architecture to frame individual decisions in ways that encourage welfare-enhancing choices, consciously designing the institutions that influence regulators’ policy decisions with behavioral insights in mind could lead to more public-welfare-enhancing policies. The article concludes with some modest ideas for improving regulators’ choice architecture and suggestions for further research….(More)”.

The crowd in crowdsourcing: Crowdsourcing as a pragmatic research method

Curated on Posted on by Stefaan Verhulst

Lina Eklund, Isabell Stamm, Wanda Katja Liebermann at First Monday:
“Crowdsourcing, as a digital process employed to obtain information, ideas, and solicit contributions of work, creativity, etc., from large online crowds stems from business, yet is increasingly used in research. Engaging with previous literature and a symposium on academic crowdsourcing this study explores the underlying assumptions about crowdsourcing as a potential academic research method and how these affect the knowledge produced. Results identify crowdsourcing research as research about and with the crowd, explore how tasks can be productive, reconfiguring, and evaluating, and how these are linked to intrinsic and extrinsic rewards, we also identify three types of platforms: commercial platforms, research-specific platforms, and project specific platforms. Finally, the study suggests that crowdsourcing is a digital method that could be considered a pragmatic method; the challenge of a sound crowdsourcing project is to think about the researcher’s relationship to the crowd, the tasks, and the platform used….(More)”.

Big Data Analytics in Healthcare

Curated on Posted on by Stefaan Verhulst

Book edited by Anand J. Kulkarni, Patrick Siarry, Pramod Kumar Singh, Ajith Abraham, Mengjie Zhang, Albert Zomaya and Fazle Baki: “This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations.

The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms…(More)”.

Risk identification and management for the research use of government administrative data

Curated on Posted on by Stefaan Verhulst

Paper by Elizabeth Shepherd, Anna Sexton, Oliver Duke-Williams, and Alexandra Eveleigh: “Government administrative data have enormous potential for public and individual benefit through improved educational and health services to citizens, medical research, environmental and climate interventions and exploitation of scarce energy resources. Administrative data is usually “collected primarily for administrative (not research) purposes by government departments and other organizations for the purposes of registration, transaction and record keeping, during the delivery of a service” such as health care, vehicle licensing, tax and social security systems (https://esrc.ukri.org/funding/guidance-for-applicants/research-ethics/useful-resources/key-terms-glossary/). Administrative data are usually distinguished from data collected for statistical use such as the census. Unlike administrative records, they do not provide evidence of activities and generally lack metadata and context relating to provenance. Administrative data, unlike open data, are not routinely made open or accessible, but access can be provided only on request to named researchers for specified research projects through research access protocols that often take months to negotiate and are subject to significant constraints around re-use such as the use of safe havens. Researchers seldom make use of freedom of information or access to information protocols to access such data because they need specific datasets and particular levels of granularity and an ability to re-process data, which are not made generally available. This study draws on research undertaken by the authors as part of the Administrative Data Research Centre in England (ADRC-E). The research examined perspectives on the sharing, linking and re-use (secondary use) of administrative data in England, viewed through three analytical themes: trust, consent and risk. This study presents the analysis of the identification and management of risk in the research use of government administrative data and presents a risk framework. Risk management (i.e. coordinated activities that allow organizations to control risks, Lemieux, 2010) enables us to think about the balance between risk and benefit for the public good and for other stakeholders. Mitigating activities or management mechanisms used to control the identified risks depend on the resources available to implement the options, on the risk appetite or tolerance of the community and on the cost and likely effectiveness of the mitigation. Mitigation and risk do not work in isolation and should be holistically viewed by keeping the whole information infrastructure in balance across the administrative data system and between multiple stakeholders.

This study seeks to establish a clearer picture of risk with regard to government administrative data in England. It identifies and categorizes the risks arising from the research use of government administrative data. It identifies mitigating risk management activities, linked to five key stakeholder communities and discusses the locus of responsibility for risk management actions. The identification of the risks and of mitigation strategies is derived from the viewpoints of the interviewees and associated documentation; therefore, they reflect their lived experience. The five stakeholder groups identified from the data are as follows: individual researchers; employers of researchers; wider research community; data creators and providers and data subjects and the broader public. The primary sections of the study, following the methodology and research context, set out the seven identified types of risk events in the research use of administrative data, present a stakeholder mapping of the communities in this research affected by the risks and discuss the findings related to managing and mitigating the risks identified. The conclusion presents the elements of a new risk framework to inform future actions by the government data community and enable researchers to exploit the power of administrative data for public good….(More)”.

Lessons Learned for New Office of Innovation

Curated on Posted on by Stefaan Verhulst

Blog by Catherine Tkachyk: “I have worked in a government innovation office for the last eight years in four different roles and two different communities.  In that time, I’ve had numerous conversations on what works and doesn’t work for innovation in local government.  Here’s what I’ve learned: starting an innovation office in government is hard.  That is not a complaint, I love the work I do, but it comes with its own challenges.  When you think about many of the services government provides: Police; Fire; Health and Human Services; Information Technology; Human Resources; Finance; etc. very few people question whether government should provide those services.  They may question how they are provided, who is providing them, or how much they cost, but they don’t question the service.  That’s not true for innovation offices.  One of the first questions I can get from people when they hear what I do is, “Why does government need an Office of Innovation.”  My first answer is, “Do you like how government works?  If not, then maybe there should be a group of people focused on fixing it.” 

Over my career, I have come across a few lessons on how to start up an innovation office to give you the best chance for success. Some of these lessons come from listening to others, but many (probably too many) come from my own mistakes….(More)”.