Social Media Seen as Mostly Good for Democracy Across Many Nations, But U.S. is a Major Outlier


Pew Research: “As people across the globe have increasingly turned to Facebook, Twitter, WhatsApp and other platforms to get their news and express their opinions, the sphere of social media has become a new public space for discussing – and often arguing bitterly – about political and social issues. And in the mind of many analysts, social media is one of the major reasons for the declining health of democracy in nations around the world.

Bar chart showing most say that social media has been good for democracy but has had important negative and positive effects on politics and society

However, as a new Pew Research Center survey of 19 advanced economies shows, ordinary citizens see social media as both a constructive and destructive component of political life, and overall most believe it has actually had a positive impact on democracy. Across the countries polled, a median of 57% say social media has been more of a good thing for their democracy, with 35% saying it is has been a bad thing.

There are substantial cross-national differences on this question, however, and the United States is a clear outlier: Just 34% of U.S. adults think social media has been good for democracy, while 64% say it has had a bad impact. In fact, the U.S. is an outlier on a number of measures, with larger shares of Americans seeing social media as divisive…(More)”.

Navigating the Crisis: How Governments Used Intelligence for Decision Making During the COVID-19 Pandemic


Report by Geoff Mulgan, Oliver Marsh, and Anina Henggeler: “…examines how governments — and the societies around them — mobilised intelligence to handle the COVID-19 pandemic and its effects. It also makes recommendations as to how they could improve their ability to organise intelligence for future challenges of all kinds, from pandemics to climate change.

The study draws on dozens of interviews with senior officials and others in many countries including Estonia, Australia, New Zealand, Germany, Finland, USA, Chile, Canada, Portugal, Taiwan, Singapore, India, Bangladesh, UAE, South Korea and the UK, as well as the European Commission and UN agencies — along with roundtables and literature analysis.

The pandemic was an unprecedented event in its global impacts and in the scale of government responses. It required a myriad of policy decisions: about testing, lockdowns, masks, school closures, visiting rules at care homes and vaccinations.

Our interest is in what contributed to those decisions, and we define intelligence broadly to include data, evidence, models, tacit knowledge, foresight and creativity and innovation — all the means that can help governments make better decisions, particularly under conditions of stress and uncertainty.

Each type of intelligence played an important role. Governments needed health as well as non-health data to help understand how the virus was spreading in real time and its impacts. They needed models — for example, to judge if their hospitals were at risk of being overrun. They needed evidence — for example on whether enforcing mask-wearing would be effective. And they needed to tap into the knowledge of citizens and frontline staff quickly to spot potential problems and frictions.

Most governments had to improvise new methods of organising that intelligence, particularly as they grappled not just with the immediate health challenges, but also with the knock-on challenges to economies, communities, mental health, school systems and sectors such as hospitality.

As we show there was extraordinary innovation globally around the gathering of data, from mass serological testing to analysis of sewage, from mobilising mobile phone data to citizen generated data on symptoms. There was an equally impressive explosion of research and evidence; and innovative approaches to problem solving and creativity, from vaccine development to Personal Protective Equipment (PPE).

However, we also point to problems:

  • Imbalances in terms of what was attended to — with physical health given much more attention than mental health or educational impacts in models and data, which was understandable in the early phases of the crisis but more problematic later on as trade-offs had to be managed
  • Imbalances in different kinds of expertise in scientific advice and influence, for instance in who got to sit on and be heard in expert advisory committees
  • Very varied ability of countries to share information and data between tiers of government
  • Very varied ability to mobilise key sources, such as commercial data, and varied use of intelligence from outside sources, such as from other countries or from civic groups,
  • Even when there were strong sources of advice and evidence, weak capacities to synthesise multiple kinds of intelligence at the core of governments…(More)”.

Using private sector geospatial data to inform policy


OECD Report: “Over the last decade, a large variety of geospatial data sources, such as GPS trajectories, geotagged photos, and social media have become available for research and statistical applications. These new data sources are often generated, voluntarily or non-voluntarily, by private sector organisations and can provide highly granular and timely information to policymakers. Drawing on experiences of several OECD countries, this paper highlights the potential of combining traditional and unconventional data from both public and private sources, and makes the case for facilitating co-operation between data providers and organisations responsible for public policy. In addition, the paper provides a series of best practices on leveraging private data for the public good and identifies opportunities, challenges, and ways forward for public and private sector partnerships on data sharing….(More)”.

Digital Sovereignty: From Narrative To Policy?


Report by EU Cyber Direct: “The debate in Europe about digital sovereignty, technological sovereignty, data sovereignty and strategic autonomy has been building over recent years at both the EU level and the level of individual Member States. The different concepts – and their diverse interpretations – cover the sovereignty concerns of citizens, states and the EU itself, and range from the protection of fundamental rights to addressing geo-economic strengths and vulnerabilities and European military concerns. The language of digital sovereignty and strategic autonomy has become integrated into the policy statements and documents of the European Union, even if definitions of the terminology remain scarce. While there has been much analysis of these new narratives of digital sovereignty and strategic autonomy, less attention has been paid to the alignment – or misalignment – between these narratives and the EU policies that would translate the concepts into everyday life.

This lacuna was the point of departure for the EU Cyber Direct Research Seminar co-organised with The Hague Program on International Cyber Security on 18 March 2022 under the title Digital Sovereignty: From Narrative to Policy?, the results of which are published in this publication…(More)”.

Smart city planning must work for both private business and public citizens


Article by Neil Britto; Suparno Banerjee and Constanza Movsichoff: “The challenges associated with the design, development and maintenance of digital urban infrastructure are substantial and have to balance the needs and incentives of both public and private stakeholders. While proofs of concepts and test-beds have been tried and are often successful, scaling these to city scale has been challenging for a number of reasons:

  • Scope. There is too often a focus on solutions that address narrow aspects of the city’s needs.
  • Capital requirements. Many cities do not have adequate capital for deploying solutions at scale and might struggle to attract investment from the private sector.
  • Procurement. Procurement models favor vendor-buyer relationships as opposed to multi-year, multi-enterprise, complex partnerships.
  • Time scales. Some of the most pressing challenges that cities face will need multiple years to address. These complex journeys need partnerships that can withstand the pressures of time, budgets and expectations.
  • Data. A nuanced understanding of public concern over data sourcing and use can be critical for a successful public-private collaboration. These dynamics contribute to the unique challenges and opportunities for smart city public-private collaborations that range from intelligent street lighting to broadband access.

In recognition of these challenges, the World Economic Forum’s G20 Global Smart Cities Alliance assembled a taskforce to look for best practices and model policies in the area of public-private collaborations in 2021. That taskforce, comprised of experts and officers from cities, companies and institutions deeply involved in smart city projects, compiled case studies, insights and feedback from across the sector. As members of that taskforce, we are happy to provide a distillation of these resources in the form of our new Primer for Smart City Public Private Collaborations…(More)”.

Leveraging Data to Improve Racial Equity in Fair Housing


Report by Temilola Afolabi: “Residential segregation is related to inequalities in education, job opportunities, political power, access to credit, access to health care, and more. Steering, redlining, mortgage lending discrimination, and other historic policies have all played a role in creating this state of affairs.

Over time, federal efforts including the Fair Housing Act and Home Mortgage Disclosure Act have been designed to improve housing equity in the United States. While these laws have not been entirely effective, they have made new kinds of data available—data that can shed light on some of the historic drivers of housing inequity and help inform tailored solutions to their ongoing impact.

This report explores a number of current opportunities to strengthen longstanding data-driven tools to address housing equity. The report also shows how the effects of mortgage lending discrimination and other historic practices are still being felt today. At the same time, it outlines opportunities to apply data to increase equity in many areas related to the homeownership gap, including negative impacts on health and well-being, socioeconomic disparities, and housing insecurity….(More)”.

The Ethics of Automated Warfare and Artificial Intelligence


Essay series introduced by Bessma Momani, Aaron Shull and Jean-François Bélanger: “…begins with a piece written by Alex Wilner titled “AI and the Future of Deterrence: Promises and Pitfalls.” Wilner looks at the issue of deterrence and provides an account of the various ways AI may impact our understanding and framing of deterrence theory and its practice in the coming decades. He discusses how different countries have expressed diverging views over the degree of AI autonomy that should be permitted in a conflict situation — as those more willing to cut humans out of the decision-making loop could gain a strategic advantage. Wilner’s essay emphasizes that differences in states’ technological capability are large, and this will hinder interoperability among allies, while diverging views on regulation and ethical standards make global governance efforts even more challenging.

Looking to the future of non-state use of drones as an example, the weapon technology transfer from nation-state to non-state actors can help us to understand how next-generation technologies may also slip into the hands of unsavoury characters such as terrorists, criminal gangs or militant groups. The effectiveness of Ukrainian drone strikes against the much larger Russian army should serve as a warning to Western militaries, suggests James Rogers in his essay “The Third Drone Age: Visions Out to 2040.” This is a technology that can level the field by asymmetrically advantaging conventionally weaker forces. The increased diffusion of drone technology enhances the likelihood that future wars will also be drone wars, whether these drones are autonomous systems or not. This technology, in the hands of non-state actors, implies future Western missions against, say, insurgent or guerilla forces will be more difficult.

Data is the fuel that powers AI and the broader digital transformation of war. In her essay “Civilian Data in Cyber Conflict: Legal and Geostrategic Considerations,” Eleonore Pauwels discusses how offensive cyber operations are aiming to alter the very data sets of other actors to undermine adversaries — whether through targeting centralized biometric facilities or individuals’ DNA sequence in genomic analysis databases, or injecting fallacious data into satellite imagery used in situational awareness. Drawing on the implications of international humanitarian law, Pauwels argues that adversarial data manipulation constitutes another form of “grey zone” operation that falls below a threshold of armed conflict. She evaluates the challenges associated with adversarial data manipulation, given that there is no internationally agreed upon definition of what constitutes cyberattacks or cyber hostilities within international humanitarian law (IHL).

In “AI and the Actual International Humanitarian Law Accountability Gap,” Rebecca Crootoff argues that technologies can complicate legal analysis by introducing geographic, temporal and agency distance between a human’s decision and its effects. This makes it more difficult to hold an individual or state accountable for unlawful harmful acts. But in addition to this added complexity surrounding legal accountability, novel military technologies are bringing an existing accountability gap in IHL into sharper focus: the relative lack of legal accountability for unintended civilian harm. These unintentional acts can be catastrophic, but technically within the confines of international law, which highlights the need for new accountability mechanisms to better protect civilians.

Some assert that the deployment of autonomous weapon systems can strengthen compliance with IHL by limiting the kinetic devastation of collateral damage, but AI’s fragility and apparent capacity to behave in unexpected ways poses new and unexpected risks. In “Autonomous Weapons: The False Promise of Civilian Protection,” Branka Marijan opines that AI will likely not surpass human judgment for many decades, if ever, suggesting that there need to be regulations mandating a certain level of human control over weapon systems. The export of weapon systems to states willing to deploy them on a looser chain-of-command leash should be monitored…(More)”.

The Socio-Legal Lab: An Experiential Approach to Research on Law in Action


Guide by Siddharth Peter de Souza and Lisa Hahn: “..interactive workbook for socio-legal research projects. It employs the idea of a “lab” as a space for interactive and experiential learning. As an introductory book, it addresses researchers of all levels who are beginning to explore interdisciplinary research on law and are looking for guidance on how to do so. Likewise, the book can be used by teachers and peer groups to experiment with teaching and thinking about law in action through lab-based learning…

The book covers themes and questions that may arise during a socio-legal research project. This starts with examining what research and interdisciplinarity mean and in which forms they can be practiced. After an overview of the research process, we will discuss how research in action is often unpredictable and messy. Thus, the practical and ethical challenges of doing research will be discussed along with processes of knowledge production and assumptions that we have as researchers. 

Conducting a socio-legal research project further requires an overview of the theoretical landscape. We will introduce general debates about the nature, functions, and effects of law in society. Further, common dichotomies in socio-legal research such as “law” and “the social” or “qualitative” and “quantitative” research will be explored, along with suggested ways on how to bridge them. 

Turning to the application side of socio-legal research, the book delves deeper into questions of data on law and society, where to collect it and how to deal with it in a reflexive manner. It discusses different methods of qualitative socio-legal research and offers ways in which they can be experienced through exercises and simulations. In the research process, generating research results is followed by publishing and communicating them. We will explore different ways to ensure the outreach and impact of one’s research by communicating results through journals, blogs or social media. Finally, the book also discusses academia as a social space and the value of creating and using networks and peer groups for mutual support.

Overall, the workbook is designed to accompany and inspire researchers on their way through a socio-legal research project and to empower the reader into thinking more creatively about their methods, while at the same time demystifying them…(More)”.

OECD Good Practice Principles for Public Service Design and Delivery in the Digital Age


OECD Report: “The digital age provides great opportunities to transform how public services are designed and delivered. The OECD Good Practice Principles for Service Design and Delivery in the Digital Age provide a clear, actionable and comprehensive set of objectives for the high-quality digital transformation of public services. Reflecting insights gathered from across OECD member countries, these nine principles are arranged under three pillars of “Build accessible, ethical and equitable public services that prioritise user needs, rather than government needs”; “Deliver with impact, at scale and with pace”; and “Be accountable and transparent in the design and delivery of public services to reinforce and strengthen public trust”. The principles are advisory rather than prescriptive, allowing for local interpretation and implementation. They should also be considered in conjunction with wider OECD work to equip governments in harnessing the potential of digital technology and data to improve outcomes for all…(More)”.

Machine Learning in Public Policy: The Perils and the Promise of Interpretability


Report by Evan D. Peet, Brian G. Vegetabile, Matthew Cefalu, Joseph D. Pane, Cheryl L. Damberg: “Machine learning (ML) can have a significant impact on public policy by modeling complex relationships and augmenting human decisionmaking. However, overconfidence in results and incorrectly interpreted algorithms can lead to peril, such as the perpetuation of structural inequities. In this Perspective, the authors give an overview of ML and discuss the importance of its interpretability. In addition, they offer the following recommendations, which will help policymakers develop trustworthy, transparent, and accountable information that leads to more-objective and more-equitable policy decisions: (1) improve data through coordinated investments; (2) approach ML expecting interpretability, and be critical; and (3) leverage interpretable ML to understand policy values and predict policy impacts…(More)”.