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 datacatalog@urban.org.

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)”.

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)”.

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)”.

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)”.

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)”.

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)”.

Report by Andrew Zahuranec, Andrew Young and Stefaan G. Verhulst: “Around the world, public leaders are seeking new ways to better understand the needs of their citizens, and subsequently improve governance, and how we solve public problems. The approaches proposed toward changing public engagement tend to focus on leveraging two innovations. The first involves artificial intelligence (AI), which offers unprecedented abilities to quickly process vast quantities of data to deepen insights into public needs. The second is collective intelligence (CI), which provides means for tapping into the “wisdom of the crowd.” Both have strengths and weaknesses, but little is known on how the combination of both could address their weaknesses while radically transform how we meet public demands for more responsive governance.

Today, The GovLab is releasing a new report, Identifiying Citizens’ Needs By Combining AI and CI, which seeks to identify and assess how institutions might responsibly experiment in how they engage with citizens by leveraging AI and CI together.

The report, authored by Stefaan G. Verhulst, Andrew J. Zahuranec, and Andrew Young, builds upon an initial examination of the intersection of AI and CI conducted in the context of the MacArthur Foundation Research Network on Opening Governance. …

The report features five in-depth case studies and an overview of eight additional examples from around the world on how AI and CI together can help to: 

• Anticipate citizens’ needs and expectations through cognitive insights and process automation and pre-empt problems through improved forecasting and anticipation;
• Analyze large volumes of citizen data and feedback, such as identifying patterns in complaints;
• Allow public officials to create highly personalized campaigns and services; or
• Empower government service representatives to deliver relevant actions….(More)”.

Paper by Jonathan L. Zittrain: “To understand where digital governance is going, we must take stock of where it’s been, because the timbre of mainstream thinking around digital governance today is dramatically different than it was when study of “Internet governance” coalesced in the late 1990s.

Perhaps the most obvious change has been from emphasizing networked technologies’ positive effects and promise – couched around concepts like connectivity, innovation, and, by this author, “generativity” – to pointing out their harms and threats. It’s not that threats weren’t previously recognized, but rather that they were more often seen in external clamps on technological development and upon the corresponding new freedoms for users, whether government intervention to block VOIP services like Skype to protect incumbent telco revenues, or in the shaping of technology to effect undue surveillance, whether for government or corporate purposes.

The shift in emphasis from positive to negative corresponds to a change in the overarching frameworks for talking about regulating information technology. We have moved from a discourse around rights – particularly those of end-users, and the ways in which abstention by intermediaries is important to facilitate citizen flourishing – to one of public health, which naturally asks for a weighing of the systemic benefits or harms of a technology, and to think about what systemic interventions might curtail its apparent excesses.

Each framework captures important values around the use of technology that can both empower and limit individual freedom of action, including to engage in harmful conduct. Our goal today should be to identify where competing values frameworks themselves preclude understanding of others’ positions about regulation, and to see if we can map a path forward that, if not reconciling the frameworks, allows for satisfying, if ever-evolving, resolutions to immediate questions of public and private governance…(More)”.

Peter Batali, Ajoma Christopher & Katie Drew in the Stanford Social Innovation Review: “…Based on this experience, UNHCR and CTEN developed a pragmatic, refugee-led, “good enough” approach to experimentation in humanitarian contexts. We believe a wide range of organizations, including grassroots community organizations and big-tech multinationals, can apply this approach to ensure that the people they aim to help hold the reigns of the experimentation process.

1. Collaborate Authentically and Build Intentional Partnerships

Resource and information asymmetry are inherent in the humanitarian system. Refugees have long been constructed as “‘victims”’ in humanitarian response, waiting for “salvation” from heroic humanitarians. Researcher Matthew Zagor describes this construct as follows: “The genuine refugee … is the passive, coerced, patient refugee, the one waiting in the queue—the victim, anticipating our redemptive touch, defined by the very passivity which in our gaze both dehumanizes them, in that they lack all autonomy in our eyes, and romanticizes them as worthy in their potentiality.”

Such power dynamics make authentic collaboration challenging….

2. Avoid Technocratic Language

Communication can divide us or bring us together. Using exclusive or “expert” terminology (terms like “ideation,” “accelerator,” and “design thinking”) or language that reinforces power dynamics or assigns an outsider role (such as “experimenting on”) can alienate community participants. Organizations should aim to use inclusive language than everyone understands, as well as set a positive and realistic tone. Communication should focus on the need to co-develop solutions with the community, and the role that testing or trying something new can play….

3. Don’t Assume Caution Is Best

Research tells us that we feel more regret over actions that lead to negative outcomes than we do over inactions that lead to the same or worse outcomes. As a result, we tend to perceive and weigh action and inaction unequally. So while humanitarian organizations frequently consider the implications of our actions and the possible negative outcome for communities, we don’t always consider the implications of doing nothing. Is it ethical to continue an activity that we know isn’t as effective as it could be, when testing small and learning fast could reap real benefits? In some cases, taking a risk might, in fact, be the least risky path of action. We need to always ask ourselves, “Is it really ethical to do nothing?”…

4. Choose Experiment Participants Based on Values

Many humanitarian efforts identify participants based on their societal role, vulnerability, or other selection criteria. However, these methods often lead to challenges related to incentivization—the need to provide things like tea, transportation, or cash payments to keep participants engaged. Organizations should instead consider identifying participants who demonstrate the values they hope to promote—such as collaboration, transparency, inclusivity, or curiosity. These community members are well-poised to promote inclusivity, model positive behaviors, and engage participants across the diversity of your community….

5. Monitor Community Feedback and Adapt

While most humanitarian agencies know they need to listen and adapt after establishing communication channels, the process remains notoriously challenging. One reason is that community members don’t always share their feedback on experimentation formally; feedback sometimes comes from informal channels or even rumors. Yet consistent, real-time feedback is essential to experimentation. Listening is the pressure valve in humanitarian experimentation; it allows organizations to adjust or stop an experiment if the community flags a negative outcome….(More)”.

Book by Daron Acemoglu and James A. Robinson: “…In their new book, they build a new theory about liberty and how to achieve it, drawing a wealth of evidence from both current affairs and disparate threads of world history.  

Liberty is hardly the “natural” order of things. In most places and at most times, the strong have dominated the weak and human freedom has been quashed by force or by customs and norms. Either states have been too weak to protect individuals from these threats, or states have been too strong for people to protect themselves from despotism. Liberty emerges only when a delicate and precarious balance is struck between state and society.

There is a Western myth that political liberty is a durable construct, arrived at by a process of “enlightenment.” This static view is a fantasy, the authors argue. In reality, the corridor to liberty is narrow and stays open only via a fundamental and incessant struggle between state and society: The authors look to the American Civil Rights Movement, Europe’s early and recent history, the Zapotec civilization circa 500 BCE, and Lagos’s efforts to uproot corruption and institute government accountability to illustrate what it takes to get and stay in the corridor. But they also examine Chinese imperial history, colonialism in the Pacific, India’s caste system, Saudi Arabia’s suffocating cage of norms, and the “Paper Leviathan” of many Latin American and African nations to show how countries can drift away from it, and explain the feedback loops that make liberty harder to achieve. 

Today we are in the midst of a time of wrenching destabilization. We need liberty more than ever, and yet the corridor to liberty is becoming narrower and more treacherous. The danger on the horizon is not “just” the loss of our political freedom, however grim that is in itself; it is also the disintegration of the prosperity and safety that critically depend on liberty. The opposite of the corridor of liberty is the road to ruin….(More)”.