‘Anyway, the dashboard is dead’: On trying to build urban informatics


Paper by Jathan Sadowski: “How do the idealised promises and purposes of urban informatics compare to the material politics and practices of their implementation? To answer this question, I ethnographically trace the development of two data dashboards by strategic planners in an Australian city over the course of 2 years. By studying this techno-political process from its origins onward, I uncovered an interesting story of obdurate institutions, bureaucratic momentum, unexpected troubles, and, ultimately, frustration and failure. These kinds of stories, which often go untold in the annals of innovation, contrast starkly with more common framings of technological triumph and transformation. They also, I argue, reveal much more about how techno-political systems are actualised in the world…(More)”.

Perspectives on Platform Regulation


Open Access Book edited by Judit Bayer, Bernd Holznage, Päivi Korpisaari and Lorna Woods: “Concepts and Models of Social Media GovernanceOnline social media platforms set the agenda and structure for public and private communication in our age. Their influence and power is beyond any traditional media empire. Their legal regulation is a pressing challenge, but currently, they are mainly governed by economic pressures. There are now diverse legislative attempts to regulate platforms in various parts of the world. The European Union and most of its Member States have historically relied on soft law, but are now looking to introduce regulation.

Leading researchers of the field analyse the hard questions and the responses given by various states. The book offers legislative solutions from various parts of the world, compares regulatory concepts and assesses the use of algorithms….(More)”.

The Birth of Digital Human Rights


Book by Rebekah Dowd on “Digitized Data Governance as a Human Rights Issue in the EU”: “…This book considers contested responsibilities between the public and private sectors over the use of online data, detailing exactly how digital human rights evolved in specific European states and gradually became a part of the European Union framework of legal protections. The author uniquely examines why and how European lawmakers linked digital data protection to fundamental human rights, something heretofore not explained in other works on general data governance and data privacy. In particular, this work examines the utilization of national and European Union institutional arrangements as a location for activism by legal and academic consultants and by first-mover states who legislated digital human rights beginning in the 1970s. By tracing the way that EU Member States and non-state actors utilized the structure of EU bodies to create the new norm of digital human rights, readers will learn about the process of expanding the scope of human rights protections within multiple dimensions of European political space. The project will be informative to scholar, student, and layperson, as it examines a new and evolving area of technology governance – the human rights of digital data use by the public and private sectors….(More)”.

Decolonizing Innovation


Essay by Tony Roberts and Andrea Jimenez Cisneros: “In order to decolonize global innovation thinking and practice, we look instead to indigenous worldviews such as Ubuntu in Southern Africa, Swaraj in South Asia, and Buen Vivir in South America. Together they demonstrate that a radically different kind of innovation is possible.

The fate of Kenya’s Silicon Savannah should serve as a cautionary tale about exporting Western models to the Global South.

The fate of Kenya’s Silicon Savannah should serve as a cautionary tale about exporting Western models to the Global South. The idea of an African Silicon Valley emerged around 2011 amidst the digital technology ecosystem developing in Nairobi. The success of Nairobi’s first innovation hub inspired many imitators and drove ambitious plans by the government to build a new innovation district in the city. The term “Silicon Savannah” captured these aspirations and featured in a series of blog posts, white papers, and consultancy reports. Advocates argued that Nairobi could leapfrog other innovation centers due to lower entry barriers and cost advantages.

These promises caught the attention of many tech entrepreneurs and policymakers—including President Barack Obama, who cohosted the 2015 Global Entrepreneurship Summit in Kenya. As part of its Silicon Savannah vision, the Kenyan government proposed to build a “smart city” called Konza Technopolis in the south of Nairobi. This government-led initiative—designed with McKinsey consultants—was supposed to help turn Kenya into a “middle-income country providing a high quality life to all its citizens by the year 2030.” The city was proposed to attract investors, create jobs at a mass scale, and use technology to manage the city effectively and efficiently. Its website identified Konza as the place where “Africa’s silicon savannah begins.” Years later, the dream remains unfulfilled. As Kenyan writer Carey Baraka’s has recently detailed, the plan has only reinforced existing inequalities as it caters mainly to international multinationals and the country’s wealthy elite.

One of the most important lessons to be derived from studying such efforts to import foreign technologies and innovation models is that they inevitably come with ideological baggage. Silicon Valley is not just a theoretical model for economic growth: it represents a whole way of life, carrying with it all kinds of implications for how people think about themselves, each other, and their place in the world. Venture capital pitching sessions prize what is most monetizable, what stands to deliver the greatest return on investment, and what offers the earliest exit opportunities. Breznitz is right to criticize this way of thinking, but similar worries arise about his own examples, which say little about environmental sustainability or maintaining the integrity of local communities. Neoliberal modes of private capital accumulation are not value neutral, and we must be sensitive to the way innovation models are situated in uneven structures of power, discourse, and resource distribution…(More)”.

Randomistas vs. Contestistas


Excerpt by By Beth Simone Noveck: “Social scientists who either run experiments or conduct systematic reviews tend to be fervent proponents of the value of RCTs. But that evidentiary hierarchy—what some people call the “RCT industrial complex”—may actually lead us to discount workable solutions just because there is no accompanying RCT.

A trawl of the solution space shows that successful interventions developed by entrepreneurs in business, philanthropy, civil society, social enterprise, or business schools who promote and study open innovation, often by developing and designing competitions to source ideas, often come from more varied places. Uncovering these exciting social innovations lays bare the limitations of confining a definition of what works only to RCTs.

Many more entrepreneurial and innovative solutions are simply not tested with an RCT and are not the subject of academic study. As one public official said to me, you cannot saddle an entrepreneur with having to do a randomized controlled trial (RCT), which they do not have the time or know-how to do. They are busy helping real people, and we have to allow them “to get on with it.”

For example, MIT Solve, which describes itself as a marketplace for socially impactful innovation designed to identify lasting solutions to the world’s most pressing problems. It catalogs hundreds of innovations in use around the world, like Faircap, a chemical-free water filter used in Mozambique, or WheeLog!, an application that enables individuals and local governments to share accessibility information in Tokyo.

Research funding is also too limited (and too slow) for RCTs to assess every innovation in every domain. Many effective innovators do not have the time, resources, or know-how to partner with academic researchers to conduct a study, or they evaluate projects by some other means.

There are also significant limitations to RCTs. For a start, systematic evidence reviews are quite slow, frequently taking upward of two years, and despite published standards for review, there is a lack of transparency. Faster approaches are important. In addition, many solutions that have been tested with an RCT clearly do not work. Interestingly, the first RCT in an area tends to produce an inflated effect size….(More)”.

Automating Decision-making in Migration Policy: A Navigation Guide


Report by Astrid Ziebarth and Jessica Bither: “Algorithmic-driven or automated decision-making models (ADM) and programs are increasingly used by public administrations to assist human decision-making processes in public policy—including migration and refugee policy. These systems are often presented as a neutral, technological fix to make policy and systems more efficient. However, migration policymakers and stakeholders often do not understand exactly how these systems operate. As a result, the implications of adopting ADM technology are still unclear, and sometimes not considered. In fact, automated decision-making systems are never neutral, nor is their employment inevitable. To make sense of their function and decide whether or how to use them in migration policy will require consideration of the specific context in which ADM systems are being employed.

Three concrete use cases at core nodes of migration policy in which automated decision-making is already either being developed or tested are examined: visa application processes, placement matching to improve integration outcomes, and forecasting models to assist for planning and preparedness related to human mobility or displacement. All cases raise the same categories of questions: from the data employed, to the motivation behind using a given system, to the action triggered by models. The nuances of each case demonstrate why it is crucial to understand these systems within a bigger socio-technological context and provide categories and questions that can help policymakers understand the most important implications of any new system, including both technical consideration (related to accuracy, data questions, or bias) as well as contextual questions (what are we optimizing for?).

Stakeholders working in the migration and refugee policy space must make more direct links to current discussions surrounding governance, regulation of AI, and digital rights more broadly. We suggest some first points of entry toward this goal. Specifically, for next steps stakeholders should:

  1. Bridge migration policy with developments in digital rights and tech regulation
  2. Adapt emerging policy tools on ADM to migration space
  3. Create new spaces for exchange between migration policymakers, tech regulators, technologists, and civil society
  4. Include discussion on the use of ADM systems in international migration fora
  5. Increase the number of technologists or bilinguals working in migration policy
  6. Link tech and migration policy to bigger questions of foreign policy and geopolitics…(More)”.

Do we know what jobs are in high demand?


Emma Rindlisbacher at Work Shift: “…Measuring which fields are in demand is harder than it sounds. Many of the available data sources, experts say, have significant flaws. And that causes problems for education providers who are trying to understand market demand and map their programs to it.

“If you are in higher education and trying to understand where the labor market is going, use BLS data as a general guide but do not rely too heavily on it when it comes to building programs and making investments,” said Jason Tyszko, the Vice President of the Center for Education and Workforce at the US Chamber of Commerce Foundation.

What’s In-Demand?

Why it matters: Colleges are turning to labor market data as they face increasing pressure from lawmakers and the public to demonstrate value and financial ROI. A number of states also have launched specialized grant and “free college” programs for residents pursuing education in high-demand fields. And many require state agencies to determine which fields are in high demand as part of workforce planning processes.

Virginia is one of those states. To comply with state law, the Board of Workforce Development has to regularly update a list of high demand occupations. Deciding how to do so can be challenging.

According to a presentation given at a September 2021 meeting, the board chose to determine which occupations are in high demand by using BLS data. The reason: the BLS data is publicly available.

“Although in some instances, proprietary data sources have different or additional nuances, in service of guiding principle #1 (transparency, replicability), our team has relied exclusively on publicly available data for this exercise,” the presentation said. (A representative from the board declined to comment, citing the still ongoing nature of constructing the high demand occupations list.)

The limits of the gold standard

For institutions looking to study job market trends, there are typically two main data sources available. The first, from BLS, are official government statistics primarily designed to track economic indicators such as the unemployment rate. The second, from proprietary companies such as Emsi Burning Glass, typically relies on postings to job board websites like LinkedIn. 

The details: The two sources have different strengths and weaknesses. The Emsi Burning Glass data can be considered “real time” data, because it identifies new job postings as they are released online. The BLS data, on the other hand, is updated less frequently but is comprehensive.

The BLS data is designed to compare economic trends across decades, and to map to state systems so that statistics like unemployment rates can be compared across states. For those reasons, the agency is reluctant to change the definitions underlying the data. That consistency, however, can make it difficult for education providers to use the data to determine which fields are in high demand.

BLS data is broken down according to the Standard Occupation Classification system, or SOC, a taxonomy used to classify different occupations. That taxonomy is designed to be public facing—the BLS website, for example, features a guide for job seekers that purports to tell them which occupation codes have the highest wages or the greatest potential for growth.

But the taxonomy was last updated in 2010, according to a BLS spokesperson…(More)”.

Academic Incentives and Research Impact: Developing Reward and Recognition Systems to Better People’s Lives


Report by Jonathan Grant: “…offers new strategies to increase the societal impact that health research can have on the community and critiques the existing academic reward structure that determines the career trajectories of so many academics—including, tenure, peer-review publication, citations, and grant funding, among others. The new assessment illustrates how these incentives can lead researchers to produce studies as an end-goal, rather than pursuing impact by applying the work in real world settings.

Dr. Grant also outlines new system-, institution-, and person-level changes to academic incentives that, if implemented, could make societal impact an integral part of the research process. Among the changes offered by Dr. Grant are tying a percentage of grant funding to the impact the research has on the community, breaking from the tenure model to incentivize ongoing development and quality research, and encouraging academics themselves to prioritize social impact when submitting or reviewing research and grant proposals…(More)”.

Public Crowdsourcing: Analyzing the Role of Government Feedback on Civic Digital Platforms


Paper by Lisa Schmidthuber, Dennis Hilgers, and Krithika Randhawa: “Government organizations increasingly use crowdsourcing platforms to interact with citizens and integrate their requests in designing and delivering public services. Government usually provides feedback to individual users on whether the request can be considered. Drawing on attribution theory, this study asks how the causal attributions of the government response affect continued participation in crowdsourcing platforms. To test our hypotheses, we use a 7-year dataset of both online requests from citizens to government and government responses to citizen requests. We focus on citizen requests that are denied by government, and find that stable and uncontrollable attributions of the government response have a negative effect on future participation behavior. Also, a local government’s locus of causality negatively affects continued participation. This study contributes to research on the role of responsiveness in digital interaction between citizens and government and highlights the importance of rationale transparency to sustain citizen participation…(More)”.

Data and Society: A Critical Introduction


Book by Anne Beaulieu and Sabina Leonelli: “Data and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book

  • fosters informed debate over the role of data in contemporary society
  • explains the significance of data as evidence beyond the “Big Data” hype
  • spans the technical, sociological, philosophical and ethical dimensions of data
  • provides guidance on how to use data responsibly
  • includes data stories that provide concrete cases and discussion questions.

Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work…(More)”.