Book by Common Sense: “…collection of essential essays, provocative perspectives, and calls to action that challenge the status quo, and that could—if we are willing to listen—redefine our relationship with technology….The onset of the coronavirus pandemic brought cascading crises and a deeper dependency on technology to keep us connected—but at a cost. We’re using tech for work, education, health care, essential services, and fun. That same technology is spreading misinformation and threatening free and open democracies. It’s widening the gap between rich and poor, taxing our emotional capacities and mental health, and creating social inequities by leaving behind those of us who are underserved and under-connected…(More)”.
Digital Government Initiative in response to the COVID-19 Pandemic
Compendium, prepared by the Division for Public Institutions and Digital Government (DPIDG) of the United Nations Department of Economic and Social Affairs (UN DESA): “…aims to capture emerging trends in digital responses of the United Nations Member States against the COVID-19 pandemic, and provide a preliminary analysis of their main features….
The initiatives listed in this compendium were submitted by Member States in response to a call for inputs launched by UN DESA/DPIDG in April/May 2020. The compendium lists selected initiatives according to major categories of action areas. While this publication does not list all initiatives submitted by Member States, the complete list can be accessed here: https://bit.ly/EGOV_COVID19_APPS .
Major groupings of action areas are:
- Information sharing
- E-participation
- E-health
- E-business
- Contact tracing
- Social distancing and virus tracking
- Working and learning from home
- Digital policy
- Partnerships…(More)”.
Institutional Change and Institutional Persistence
Paper by Daron Acemoglu, Georgy Egorov, and Konstantin Sonin: “In this essay, we provide a simple conceptual framework to elucidate the forces that lead to institutional persistence and change. Our framework is based on a dynamic game between different groups, who care both about current policies and institutions and future policies, which are themselves determined by current institutional choices, and clarifies the forces that lead to the most extreme form of institutional persistence (“institutional stasis”) and the potential drivers of institutional change. We further study the strategic stability of institutions, which arises when institutions persist because of fear of subsequent, less beneficial changes that would follow initial reforms. More importantly, we emphasize that, despite the popularity of ideas based on institutional stasis in the economics and political science literatures, most institutions are in a constant state of flux, but their trajectory may still be shaped by past institutional choices, thus exhibiting “path-dependent change”, so that initial conditions determine both the subsequent trajectories of institutions and how they respond to shocks. We conclude the essay by discussing how institutions can be designed to bolster stability, the relationship between social mobility and institutions, and the interplay between culture and institutions….(More)”
AI Localism
Today, The GovLab is excited to launch a new platform which seeks to monitor, analyze and guide how AI is being governed in cities around the world: AI Localism.
AI Localism refers to the actions taken by local decision-makers to address the use of AI within a city or community. AI Localism has often emerged because of gaps left by incomplete state, national or global governance frameworks.
“AI Localism offers both immediacy and proximity. Because it is managed within tightly defined geographic regions, it affords policymakers a better understanding of the tradeoffs involved. By calibrating algorithms and AI policies for local conditions, policymakers have a better chance of creating positive feedback loops that will result in greater effectiveness and accountability.”
The initial AI Localism projects include:
The Ethics and Practice of AI Localism at a Time of Covid-19 and Beyond – In collaboration with the TUM School of Governance and University of Melbourne The GovLab will conduct a comparative review of current practices worldwide to gain a better understanding of successful AI Localism in the context of COVID-19 as to inform and guide local leaders and city officials towards best practices.
Responsible AI at the Local Level – Together with the NYU Center Responsible AI, The GovLab will seek to develop an interactive repository and a set of training modules of Responsible AI approaches at the local level.
Join us as we seek to understand and develop new forms of governance to guide local leaders towards responsible AI implementation or share any effort you are working on to establishing responsible AI at the local level by visiting: http://ailocalism.org
Situating Open Data: Global Trends in Local Contexts
Open Access Book edited by Danny Lämmerhirt, Ana Brandusescu, Natalia Domagala & Patrick Enaholo: “Open data and its effects on society are always woven into infrastructural legacies, social relations, and the political economy. This raises questions about how our understanding and engagement with open data shifts when we focus on its situated use.
To shed a light on these questions, Situating Open Data provides several empirical accounts of open data practices, the local implementation of global initiatives, and the development of new open data ecosystems. Drawing on case studies in different countries and contexts, the chapters demonstrate the practices and actors involved in open government data initiatives unfolding within different socio-political settings.
The book proposes three recommendations for researchers, policy-makers and practitioners. First, beyond upskilling through ‘data literacy’ programmes, open data initiatives should be specified through the kinds of data practices and effects they generate. Second, global visions of open data implementation require more studies of the resonances and tensions created in localised initiatives. And third, research into open data ecosystems requires more attention to the histories and legacies of information infrastructures and how these shape who benefits from open data flows.
As such, this volume departs from the framing of data as a resource to be deployed. Instead, it proposes a prism of different data practices in different contexts through which to study the social relations, capacities, infrastructural histories and power structures affecting open data initiatives. It is hoped that the contributions collected in Situating Open Data will spark critical reflection about the way open data is locally practiced and implemented. The contributions should be of interest to open data researchers, advocates, and those in or advising government administrations designing and rolling out effective open data initiatives….(More)”.
Science and Scientists Held in High Esteem Across Global Publics
Pew Research: “As publics around the world look to scientists and the research and development process to bring new treatments and preventive strategies for the novel coronavirus, a new international survey finds scientists and their research are widely viewed in a positive light across global publics, and large majorities believe government investments in scientific research yield benefits for society.
Still, the wide-ranging survey, conducted before the COVID-19 outbreak reached pandemic proportions, reveals ambivalence about certain scientific developments – in areas such as artificial intelligence and genetically modified foods – often exists alongside high trust for scientists generally and positive views in other areas such as space exploration….
Scientists as a group are highly regarded, compared with other prominent groups and institutions in society. In all publics, majorities have at least some trust in scientists to do what is right. A median of 36% have “a lot” of trust in scientists, the same share who say this about the military, and much higher than the shares who say this about business leaders, the national government and the news media.
Still, an appreciation for practical experience, more so than expertise, in general, runs deep across publics. A median of 66% say it’s better to rely on people with practical experience to solve pressing problems, while a median of 28% say it’s better to rely on people who are considered experts about the problems, even if they don’t have much practical experience….(More)”.
The Wisdom of the Crowd: Promoting Media Development through Deliberative Initiatives
Report by Craig Matasick: “…innovative new set of citizen engagement practices—collectively known as deliberative democracy—offers important lessons that, when applied to the media development efforts, can help improve media assistance efforts and strengthen independent media environments around the world. At a time when disinformation runs rampant, it is more important than ever to strengthen public demand for credible information, reduce political polarization, and prevent media capture. Deliberative democracy approaches can help tackle these issues by expanding the number and diversity of voices that participate in policymaking, thereby fostering greater collective action and enhancing public support for media reform efforts.
Through a series of five illustrative case studies, the report demonstrates how deliberative democracy practices can be employed in both media development and democracy assistance efforts, particularly in the Global South. Such initiatives produce recommendations that take into account a plurality of voices while building trust between citizens and decision-makers by demonstrating to participants that their issues will be heard and addressed. Ultimately, this process can enable media development funders and practitioners to identify priorities and design locally relevant projects that have a higher likelihood for long-term impact.
– Deliberative democracy approaches, which are characterized by representative participation and moderated deliberation, provide a framework to generate demand-driven media development interventions while at the same time building greater public support for media reform efforts.
– Deliberative democracy initiatives foster collaboration across different segments of society, building trust in democratic institutions, combatting polarization, and avoiding elite capture.
– When employed by news organizations, deliberative approaches provide a better understanding of the issues their audiences care most about and uncover new problems affecting citizens that might not otherwise have come to light….(More)”.
Private Sector Data for Humanitarian Response: Closing the Gaps
Jos Berens at Bloomberg New Economy Forum: “…Despite these and other examples, data sharing between the private sector and humanitarian agencies is still limited. Out of 281 contributing organizations on HDX, only a handful come from the private sector.
So why don’t we see more use of private sector data in humanitarian response? One obvious set of challenges concerns privacy, data protection and ethics. Companies and their customers are often wary of data being used in ways not related to the original purpose of data collection. Such concerns are understandable, especially given the potential legal and reputational consequences of personal data breaches and leaks.
Figuring out how to use this type of sensitive data in an already volatile setting seems problematic, and it is — negotiations between public and private partners in the middle of a crisis often get hung up on a lack of mutual understanding. Data sharing partnerships negotiated during emergencies often fail to mature beyond the design phase. This dynamic creates a loop of inaction due to a lack of urgency in between crises, followed by slow and halfway efforts when action is needed most.
To ensure that private sector data is accessible in an emergency, humanitarian organizations and private sector companies need to work together to build partnerships before a crisis. They can do this by taking the following actions:
- Invest in relationships and build trust. Both humanitarian organizations and private sector organizations should designate focal points who can quickly identify potentially useful data during a humanitarian emergency. A data stewards network which identifies and connects data responsibility leaders across organizations, as proposed by the NYU Govlab, is a great example of how such relations could look. Efforts to build trust with the general public regarding private sector data use for humanitarian response should also be strengthened, primarily through transparency about the means and purpose of such collaborations. This is particularly important in the context of COVID-19, as noted in the UN Comprehensive Response to COVID-19 and the World Economic Forum’s ‘Great Reset’ initiative…(More)”.
Can fake news really change behaviour? Evidence from a study of COVID-19 misinformation.
Paper by Ciara Greene and Gillian Murphy: “Previous research has argued that fake news may have grave consequences for health behaviour, but surprisingly, no empirical data have been provided to support this assumption. This issue takes on new urgency in the context of the coronavirus pandemic. In this large preregistered study (N = 3746) we investigated the effect of exposure to fabricated news stories about COVID-19 on related behavioural intentions. We observed small but measurable effects on some related behavioural intentions but not others – for example, participants who read a story about problems with a forthcoming contact-tracing app reported reduced willingness to download the app. We found no effects of providing a general warning about the dangers of online misinformation on response to the fake stories, regardless of the framing of the warning in positive or negative terms. We conclude with a call for more empirical research on the real-world consequences of fake news….(More)”
Why Modeling the Spread of COVID-19 Is So Damn Hard
Matthew Hutson at IEEE Spectrum: “…Researchers say they’ve learned a lot of lessons modeling this pandemic, lessons that will carry over to the next.
The first set of lessons is all about data. Garbage in, garbage out, they say. Jarad Niemi, an associate professor of statistics at Iowa State University who helps run the forecast hub used by the CDC, says it’s not clear what we should be predicting. Infections, deaths, and hospitalization numbers each have problems, which affect their usefulness not only as inputs for the model but also as outputs. It’s hard to know the true number of infections when not everyone is tested. Deaths are easier to count, but they lag weeks behind infections. Hospitalization numbers have immense practical importance for planning, but not all hospitals release those figures. How useful is it to predict those numbers if you never have the true numbers for comparison? What we need, he said, is systematized random testing of the population, to provide clear statistics of both the number of people currently infected and the number of people who have antibodies against the virus, indicating recovery. Prakash, of Georgia Tech, says governments should collect and release data quickly in centralized locations. He also advocates for central repositories of policy decisions, so modelers can quickly see which areas are implementing which distancing measures.
Researchers also talked about the need for a diversity of models. At the most basic level, averaging an ensemble of forecasts improves reliability. More important, each type of model has its own uses—and pitfalls. An SEIR model is a relatively simple tool for making long-term forecasts, but the devil is in the details of its parameters: How do you set those to match real-world conditions now and into the future? Get them wrong and the model can head off into fantasyland. Data-driven models can make accurate short-term forecasts, and machine learning may be good for predicting complicated factors. But will the inscrutable computations of, for instance, a neural network remain reliable when conditions change? Agent-based models look ideal for simulating possible interventions to guide policy, but they’re a lot of work to build and tricky to calibrate.
Finally, researchers emphasize the need for agility. Niemi of Iowa State says software packages have made it easier to build models quickly, and the code-sharing site GitHub lets people share and compare their models. COVID-19 is giving modelers a chance to try out all their newest tools, says Meyers, of the University of Texas. “The pace of innovation, the pace of development, is unlike ever before,” she says. “There are new statistical methods, new kinds of data, new model structures.”…(More)”.