“Learning report” by Partners for Review (P4R/GIZ), the Danish Institute for Human Rights (DIHR), and the International Civil Society Centre: “It brought together National SDG Units, National Statistics Offices, National Human Rights Institutions and civil society organisations from across six countries. The initiative’s purpose is to advance data partnerships for the SDGs and to strengthen multi-actor data ecosystems at the national level. Goal is to meet the SDG data challenge by improving the use of alternative data sources, particularly data produced by civil society and human rights institutions, and complementary to official statistics….(More)”.
The Open Data Policy Lab’s City Incubator
The GovLab: “Hackathons. Data Jams. Dashboards. Mapping, analyzing, and releasing open data. These are some of the essential first steps in building a data-driven culture in government. Yet, it’s not always easy to get data projects such as these off the ground. Governments often work in difficult situations under constrained resources. They have to manage various stakeholders and constituencies who have to be sold on the value that data can generate in their daily work.
Through the Open Data Policy Lab, The GovLab and Microsoft are providing various resources — such as the Data Stewards Academy, and the Third Wave of Open Data Toolkit — to support this goal. Still, we recognize that more tailored guidance is needed so cities can build new sustainable data infrastructure and launch projects that meet their policy goals.
Today, we’re providing that resource in the form of the Open Data Policy Lab’s City Incubator. A first-of-its-kind program to support data innovations in cities’ success and scale, the City Incubator will give 10 city officials access to the hands-on training and access to mentors to take their ideas to the next level. It will enable cutting edge work on various urban challenges and empower officials to create data collaboratives, data-sharing agreements, and other systems. This work is supported by Microsoft, Mastercard City Possible, Luminate, NYU CUSP and the Public Sector Network.
Our team is launching a call for ten city government intrapreneurs from around the world working on data-driven projects to apply to the City Incubator. Over the course of six months, participants will use start-up innovation and public sector program solving frameworks to develop and launch new data innovations. They will also receive support from a council of mentors from around the world.
Applications are due August 31, with an early application deadline of August 6 for applicants looking for feedback. Applicants are expected to present their idea and include information on the value their proposal will generate, the resources it will use, the partners it will involve, and the risks it might entail alongside other information in the form of a Data Innovation Canvas. Additional information can be found on the website here.”
Financial data unbound: The value of open data for individuals and institutions
Paper by McKinsey Global Institute: “As countries around the world look to ensure rapid recovery once the COVID-19 crisis abates, improved financial services are emerging as a key element to boost growth, raise economic efficiency, and lift productivity. Robust digital financial infrastructure proved its worth during the crisis, helping governments cushion people and businesses from the economic shock of the pandemic. The next frontier is to create an open-data ecosystem for finance.
Already, technological, regulatory, and competitive forces are moving markets toward easier and safer financial data sharing. Open-data initiatives are springing up globally, including the United Kingdom’s Open Banking Implementation Entity, the European Union’s second payment services directive, Australia’s new consumer protection laws, Brazil’s drafting of open data guidelines, and Nigeria’s new Open Technology Foundation (Open Banking Nigeria). In the United States, the Consumer Financial Protection Bureau aims to facilitate a consumer-authorized data-sharing market, while the Financial Data Exchange consortium attempts to promote common, interoperable standards for secure access to financial data. Yet, even as many countries put in place stronger digital financial infrastructure and data-sharing mechanisms, COVID-19 has exposed limitations and gaps in their reach, a theme we explored in earlier research.
This discussion paper from the McKinsey Global Institute (download full text in 36-page PDF) looks at the potential value that could be created—and the key issues that will need to be addressed—by the adoption of open data for finance. We focus on four regions: the European Union, India, the United Kingdom, and the United States.
By open data, we mean the ability to share financial data through a digital ecosystem in a manner that requires limited effort or manipulation. Advantages include more accurate credit risk evaluation and risk-based pricing, improved workforce allocation, better product delivery and customer service, and stronger fraud protection.
Our analysis suggests that the boost to the economy from broad adoption of open-data ecosystems could range from about 1 to 1.5 percent of GDP in 2030 in the European Union, the United Kingdom, and the United States, to as much as 4 to 5 percent in India. All market participants benefit, be they institutions or consumers—either individuals or micro-, small-, and medium-sized enterprises (MSMEs)—albeit to varying degrees….(More)”.
Democracy in a Pandemic: Participation in response to Covid
Open Access Book by Involve: “Covid-19 has highlighted limitations in our democratic politics – but also lessons for how to deepen our democracy and more effectively respond to future crises.
In the face of an emergency, the working assumption all too often is that only a centralised, top-down response is possible. This book exposes the weakness of this assumption, making the case for deeper participation and deliberation in times of crises. During the pandemic, mutual aid and self-help groups have realised unmet needs. And forward-thinking organisations have shown that listening to and working with diverse social groups leads to more inclusive outcomes.
Participation and deliberation are not just possible in an emergency. They are valuable, perhaps even indispensable.
This book draws together a diverse range of voices of activists, practitioners, policy makers, researchers and writers. Together they make visible the critical role played by participation and deliberation during the pandemic and make the case for enhanced engagement during and beyond emergency contexts.
Another, more democratic world can be realised in the face of a crisis. The contributors to this book offer us meaningful insights into what this could look like….(More)”.
The Predictive Power of Patents
Paper by Sabrina Safrin: “This article explains that domestic patenting activity may foreshadow a country’s level of regulation of path-breaking technologies. The article considers whether different governments will act with a light or a heavy regulatory hand when encountering a new disruptive technology. The article hypothesizes that part of the answer to this important regulatory, economic, and geopolitical question may lie in an unexpected place: the world’s patent offices. Countries with early and significant patent activity in an emerging technology are more likely to view themselves as having a stake in the technology and therefore will be less inclined to subject the technology to extensive health, safety and environmental regulation that would constrain it. The article introduces the term “patent footprint” to describe a country’s degree of patenting activity in a new technology, and the article posits that a country’s patent footprint may provide an early clue to its willingness or reluctance to strenuously regulate the new technology. Even more so, lack of geographic diversity in patent footprints may help predict whether an emerging technology will face extensive international regulation. Patent footprints provide a useful tool to policymakers, businesses, investors, and NGOs considering the health, safety, and environmental regulation of a disruptive technology. The predictive power of patent footprints adds to the literature on the broader function of patents in society….(More)”.
On the forecastability of food insecurity
Paper by Pietro Foini, Michele Tizzoni, Daniela Paolotti, and Elisa Omodei: “Food insecurity, defined as the lack of physical or economic access to safe, nutritious and sufficient food, remains one of the main challenges included in the 2030 Agenda for Sustainable Development. Near real-time data on the food insecurity situation collected by international organizations such as the World Food Programme can be crucial to monitor and forecast time trends of insufficient food consumption levels in countries at risk.
Here, using food consumption observations in combination with secondary data on conflict, extreme weather events and economic shocks, we build a forecasting model based on gradient boosted regression trees to create predictions on the evolution of insufficient food consumption trends up to 30 days in to the future in 6 countries (Burkina Faso, Cameroon, Mali, Nigeria, Syria and Yemen). Results show that the number of available historical observations is a key element for the forecasting model performance. Among the 6 countries studied in this work, for those with the longest food insecurity time series, the proposed forecasting model makes it possible to forecast the prevalence of people with insufficient food consumption up to 30 days into the future with higher accuracy than a naive approach based on the last measured prevalence only. The framework developed in this work could provide decision makers with a tool to assess how the food insecurity situation will evolve in the near future in countries at risk. Results clearly point to the added value of continuous near real-time data collection at sub-national level…(More)”.
The State of Global Emotions
Gallup: “Nobody was alone in feeling more sad, angry, worried or stressed last year. Gallup’s latest Negative Experience Index, which annually tracks these experiences worldwide in more than 100 countries and areas, shows that collectively, the world was feeling the worst it had in 15 years. The index score reached a new high of 32 in 2020.
Line graph. The Negative Experience Index, an annual composite index of stress, anger, worry, sadness and physical pain, continued to rise in 2020, hitting a new record of 32.
Gallup asked adults in 115 countries and areas if they had five specific negative experiences on the day preceding the survey. Four in 10 adults said they had experienced worry (40%) or stress (40%), and just under three in 10 had experienced physical pain (29%) during a lot of the previous day. About one in four or more experienced sadness (27%) or anger (24%).
Already at or near record highs in 2019, experiences of worry, stress, sadness and anger continued to gain steam and set new records in 2020. Worry and sadness each rose one percentage point, anger rose two, and stress rocketed up five. The percentage of adults worldwide who experienced pain was the only index item that declined — dropping two points after holding steady for several years at 31%.
But 2020 officially became the most stressful year in recent history. The five-point jump from 35% in 2019 to 40% in 2020 represents nearly 190 million more people globally who experienced stress during a lot of the previous day.
Line graph. Reported stress worldwide soared to a record 40% in 2020 amid the COVID-19 pandemic.
Worldwide, not everyone was feeling this stress to the same degree. Reported stress ranged from a high of 66% in Peru — which represents a new high for the country — to a low of 13% in Kyrgyzstan, where stress levels have historically been low and stayed low in 2020….(More)”
What Is Behavioral Data Science and How to Get into It?
Blogpost by Ganna Pogrebna: “Behavioral Data Science is a new, emerging, interdisciplinary field, which combines techniques from the behavioral sciences, such as psychology, economics, sociology, and business, with computational approaches from computer science, statistics, data-centric engineering, information systems research and mathematics, all in order to better model, understand and predict behavior.
Behavioral Data Science lies at the interface of all these disciplines (and a growing list of others) — all interested in combining deep knowledge about the questions underlying human, algorithmic, and systems behavior with increasing quantities of data. The kinds of questions this field engages are not only exciting and challenging, but also timely, such as:
- How can people’s wellbeing at scale be measured and improved using behavioral data science?
- How can we improve the entire supply chain in creative industries and produce movies, which viewers really want to see?
- How can we better understand machine behavior and algorithmic behavior?
- How can we better model social systems by mapping risk through time?
- How can we design and deliver personalized services ethically and responsibly?
Behavioral Data Science is capable of addressing all these issues (and many more) partly because of the availability of new data sources and partly due to the emergence of new (hybrid) models, which merge behavioral science and data science models. The main advantage of these models is that they expand machine learning techniques, operating, essentially, as black boxes, to fully tractable, and explainable upgrades. Specifically, while a deep learning model can generate accurate prediction of why people select one product or brand over the other, it will not tell you what exactly drives people’s preferences; whereas hybrid models, such as anthropomorphic learning, will be able to provide this insight….(More)”
Political Science Has Its Own Lab Leaks
Paul Musgrave at Foreign Policy: “The idea of a lab leak has gone, well, viral. As a political scientist, I cannot assess whether the evidence shows that COVID-19 emerged naturally or from laboratory procedures (although many experts strenuously disagree). Yet as a political scientist, I do think that my discipline can learn something from thinking seriously about our own “lab leaks” and the damage they could cause.
A political science lab leak might seem as much of a punchline as the concept of a mad social scientist. Nevertheless, the notion that scholarly ideas and findings can escape the nuanced, cautious world of the academic seminar and transform into new forms, even becoming threats, becomes more of a compelling metaphor if you think of academics as professional crafters of ideas intended to survive in a hostile environment. Given the importance of what we study, from nuclear war to international economics to democratization and genocide, the escape of a faulty idea could have—and has had—dangerous consequences for the world.
Academic settings provide an evolutionarily challenging environment in which ideas adapt to survive. The process of developing and testing academic theories provides metaphorical gain-of-function accelerations of these dynamics. To survive peer review, an idea has to be extremely lucky or, more likely, crafted to evade the antibodies of academia (reviewers’ objections). By that point, an idea is either so clunky it cannot survive on its own—or it is optimized to thrive in a less hostile environment.
Think tanks and magazines like the Atlantic (or Foreign Policy) serve as metaphorical wet markets where wild ideas are introduced into new and vulnerable populations. Although some authors lament a putative decline of social science’s influence, the spread of formerly academic ideas like intersectionality and the use of quantitative social science to reshape electioneering suggest that ideas not only move from the academy but can flourish once transplanted. This is hardly new: Terms from disciplines including psychoanalysis (“ego”), evolution (“survival of the fittest”), and economics (the “free market” and Marxism both) have escaped from the confines of academic work before…(More)”.
How data governance technologies can democratize data sharing for community well-being
Paper by Dan Wu, Stefaan Verhulst, Alex Pentland, Thiago Avila, Kelsey Finch, and Abhishek Gupta in Data & Policy (Cambridge University Press) focusing on “Data sharing efforts to allow underserved groups and organizations to overcome the concentration of power in our data landscape…
A few special organizations, due to their data monopolies and resources, are able to decide which problems to solve and how to solve them. But even though data sharing creates a counterbalancing democratizing force, it must nevertheless be approached cautiously. Underserved organizations and groups must navigate difficult barriers related to technological complexity and legal risk.
To examine what those common barriers are, one type of data sharing effort—data trusts—are examined, specifically the reports commenting on that effort. To address these practical issues, data governance technologies have a large role to play in democratizing data trusts safely and in a trustworthy manner. Yet technology is far from a silver bullet. It is dangerous to rely upon it. But technology that is no-code, flexible, and secure can help more responsibly operate data trusts. This type of technology helps innovators put relationships at the center of their efforts….(More)”.