WHO, Germany launch new global hub for pandemic and epidemic intelligence

Curated on Posted on by Stefaan Verhulst

Press Release: “The World Health Organization (WHO) and the Federal Republic of Germany will establish a new global hub for pandemic and epidemic intelligence, data, surveillance and analytics innovation. The Hub, based in Berlin and working with partners around the world, will lead innovations in data analytics across the largest network of global data to predict, prevent, detect prepare for and respond to pandemic and epidemic risks worldwide.

H.E. German Federal Chancellor Dr Angela Merkel said: “The current COVID-19 pandemic has taught us that we can only fight pandemics and epidemics together. The new WHO Hub will be a global platform for pandemic prevention, bringing together various governmental, academic and private sector institutions. I am delighted that WHO chose Berlin as its location and invite partners from all around the world to contribute to the WHO Hub.”

The WHO Hub for Pandemic and Epidemic Intelligence is part of WHO’s Health Emergencies Programme and will be a new collaboration of countries and partners worldwide, driving innovations to increase availability and linkage of diverse data; develop tools and predictive models for risk analysis; and to monitor disease control measures, community acceptance and infodemics. Critically, the WHO Hub will support the work of public health experts and policy-makers in all countries with insights so they can take rapid decisions to prevent and respond to future public health emergencies.

“We need to identify pandemic and epidemic risks as quickly as possible, wherever they occur in the world. For that aim, we need to strengthen the global early warning surveillance system with improved collection of health-related data and inter-disciplinary risk analysis,” said Jens Spahn, German Minister of Health. “Germany has consistently been committed to support WHO’s work in preparing for and responding to health emergencies, and the WHO Hub is a concrete initiative that will make the world safer.”

Working with partners globally, the WHO Hub will drive a scale-up in innovation for existing forecasting and early warning capacities in WHO and Member States. At the same time, the WHO Hub will accelerate global collaborations across public and private sector organizations, academia, and international partner networks. It will help them to collaborate and co-create the necessary tools for managing and analyzing data for early warning surveillance. It will also promote greater access to data and information….(More)”.

The Delusions of Crowds: Why People Go Mad in Groups

Curated on Posted on by Stefaan Verhulst

Book by William J. Bernstein: “…Inspired by Charles Mackay’s 19th-century classic Memoirs of Extraordinary Popular Delusions and the Madness of Crowds, Bernstein engages with mass delusion with the same curiosity and passion, but armed with the latest scientific research that explains the biological, evolutionary, and psychosocial roots of human irrationality. Bernstein tells the stories of dramatic religious and financial mania in western society over the last 500 years—from the Anabaptist Madness that afflicted the Low Countries in the 1530s to the dangerous End-Times beliefs that animate ISIS and pervade today’s polarized America; and from the South Sea Bubble to the Enron scandal and dot com bubbles of recent years. Through Bernstein’s supple prose, the participants are as colorful as their motivation, invariably “the desire to improve one’s well-being in this life or the next.”

As revealing about human nature as they are historically significant, Bernstein’s chronicles reveal the huge cost and alarming implications of mass mania: for example, belief in dispensationalist End-Times has over decades profoundly affected U.S. Middle East policy. Bernstein observes that if we can absorb the history and biology of mass delusion, we can recognize it more readily in our own time, and avoid its frequently dire impact….(More)”.

Mapping the United Nations Fundamental Principles of Official Statistics against new and big data sources

Curated on Posted on by Stefaan Verhulst

Paper by Dominik Rozkrut, Olga Świerkot-Strużewska, and Gemma Van Halderen: “Never has there been a more exciting time to be an official statistician. The data revolution is responding to the demands of the CoVID-19 pandemic and a complex sustainable development agenda to improve how data is produced and used, to close data gaps to prevent discrimination, to build capacity and data literacy, to modernize data collection systems and to liberate data to promote transparency and accountability. But can all data be liberated in the production and communication of official statistics? This paper explores the UN Fundamental Principles of Official Statistics in the context of eight new and big data sources. The paper concludes each data source can be used for the production of official statistics in adherence with the Fundamental Principles and argues these data sources should be used if National Statistical Systems are to adhere to the first Fundamental Principle of compiling and making available official statistics that honor citizen’s entitlement to public information….(More)”.

Better Law for a Better World: New Approaches to Law Practice and Education

Curated on Posted on by Stefaan Verhulst

Book by Liz Curran: “How as a society can we find ways of ensuring the people who are the most vulnerable or have little voice can avail themselves of the protection in law to improve their social, cultural, health and economic outcomes as befits civilised society?

Better Law for a Better World answers this question by looking at innovative practices and developments emerging within law practice and education and shares the skills and techniques that could lead to confidence in the law and its ability to respond. Using recent research from Australia, practice initiatives and information, the book breaks down ways for law students, legal educators and law practitioners (including judicial officers, law administrators, legislators and policy makers) to enhance access to justice and improve outcomes through new approaches to lawyering. These can include: Multi-Disciplinary Practice (including health justice partnerships); integrated justice practice; restorative practice; empowerment modes (community & professional development and policy skills); client-centred approaches and collaborative interdisciplinary practice informed by practical experience. The book contains critical information on what such practice might look like and the elements that will be required in the development of the essential skills and criteria for such practice. It seeks to open up a dialogue about how we can make the law better. This includes making the community more central to the operation of the law and improving client-centred practice so that the Rule of Law can deliver on its claims to serve, protect and ensure equality before the law. It explores practical ways that emerging lawyers can be trained differently to ensure improved communication, collaboration, problem solving, partnership and interpersonal skills. The book explores the challenges of such work. It also gives suggestions on how to reduce professional barriers and variations in practice to effectively, humanely and efficiently make a difference in people’s lives….(More)”.

Building on a year of open data: progress and promise

Curated on Posted on by Stefaan Verhulst

Jennifer Yokoyama at Microsoft: “…The biggest takeaway from our work this past year – and the one thing I hope any reader of this post will take away – is that data collaboration is a spectrum. From the presence (or absence) of data to how open that data is to the trust level of the collaboration participants, these factors may necessarily lead to different configurations and different goals, but they can all lead to more open data and innovative insights and discoveries.

Here are a few other lessons we have learned over the last year:

  1. Principles set the foundation for stakeholder collaboration: When we launched the Open Data Campaign, we adopted five principles that guide our contributions and commitments to trusted data collaborations: Open, Usable, Empowering, Secure and Private. These principles underpin our participation, but importantly, organizations can build on them to establish responsible ways to share and collaborate around their data. The London Data Commission, for example, established a set of data sharing principles for public- and private-sector organizations to ensure alignment and to guide the participating groups in how they share data.
  2. There is value in pilot projects: Traditionally, data collaborations with several stakeholders require time – often including a long runway for building the collaboration, plus the time needed to execute on the project and learn from it. However, our learnings show short-term projects that experiment and test data collaborations can provide valuable insights. The London Data Commission did exactly that with the launch of four short-term pilot projects. Due to the success of the pilots, the partners are exploring how they can be expanded upon.
  3. Open data doesn’t require new data: Identifying data to share does not always mean it must be newly shared data; sometimes the data was narrowly shared, but can be shared more broadly, made more accessible or analyzed for a different purpose. Microsoft’s environmental indicator data is an example of data that was already disclosed in certain venues, but was then made available to the Linux Foundation’s OS-Climate Initiative to be consumed through analytics, thereby extending its reach and impact…

To get started, we suggest that emerging data collaborations make use of the wealth of existing resources. When embarking on data collaborations, we leveraged many of the definitions, toolkits and guides from leading organizations in this space. As examples, resources such as the Open Data Institute’s Data Ethics Canvas are extremely useful as a framework to develop ethical guidance. Additionally, The GovLab’s Open Data Policy Lab and Executive Course on Data Stewardship, both supported by Microsoft, highlight important case studies, governance considerations and frameworks when sharing data. If you want to learn more about the exciting work our partners are doing, check out the latest posts from the Open Data Institute and GovLab…(More)”. See also Open Data Policy Lab.

The Paths to Digital Self-Determination – A Foundational Theoretical Framework

Curated on Posted on by Stefaan Verhulst

Paper by Nydia Remolina and Mark Findlay: “A deluge of data is giving rise to new understandings and experiences of society and economy as our digital footprint grows steadily. Are data subjects able to determine themselves in this data-driven society? The emerging debates about autonomy and communal responsibility in the context of data access or protection, highlight a pressing imperative to re-imagine the ‘self’ in the digital space. Empowerment, autonomy, sovereignty, human centricity, are all terms often associated with the notion of digital self-determination in current policy language. More academics, industry experts, policymakers, regulators are now advocating self-determination in a data-driven world. The attitudes to self-determination range from alienating data as property through to broad considerations of communal access and enrichment. Digital self-determination is a complex notion to be viewed from different perspectives and in unique spaces, re-shaping what we understand as self-determination in the non-digital world. This paper explores the notion of digital self-determination by presenting a foundational theoretical framework based on pre-existent self-determination theories and exploring the implications of the digital society in the determination of the self. Only by better appreciating and critically framing the discussion of digital self-determination, is it possible to engage in trustworthy data spaces, and ensure ethical human-centric approaches when living in a data driven society….(More)”.

Artificial Intelligence in Migration: Its Positive and Negative Implications

Curated on Posted on by Stefaan Verhulst

Article by Priya Dialani: “Research and development in new technologies for migration management are rapidly increasing. To quote certain migration examples, big data was used to predict population movements in the Mediterranean, AI lie detectors used at the European border, and the recent one is the government of Canada using automated decision-making in immigration and refugee applications. Artificial intelligence in migration is helping countries to manage international migration.

Every corner of the world is encountering an unprecedented number of challenging migration crises. As an increasing number of people are interacting with immigration and refugee determination systems, nations are taking a stab at artificial intelligence. AI in global immigration is helping countries to automate a plethora of decisions that are made almost daily as people want to cross borders and look for new homes.

AI projects in migration management can help in predicting the next migration crisis with better accuracy. Artificial intelligence can predict the movements of people migrating by taking into account different types of data such as WiFi positioning, Google Trends, etc. This data can further help the nations and government to be prepared more efficiently for mass migration. Governments can use AI algorithms to examine huge datasets and look for potential gaps in their reception facilities such as the absence of appropriate places for people or vulnerable unaccompanied children.

Recognizing such gaps can allow the government to alter their reception conditions as well as be prepared to comply with their legal obligations under international human rights law (IHRL).

AI applications can also help in changing the lives of asylum seekers and refugees. AI machine learning and optimized algorithms are helping in improving refugee integration. Annie MOORE (Matching Outcome Optimization for Refugee Empowerment) is one such project that matches refugees to communities where they can find the resources and environment as per their preferences and needs.

Asylum seekers or refugees most of the time lack access to lawyers and legal advice. A UK-based chatbot DoNotPay provides free legal advice to asylum seekers using intelligent algorithms. It also provides personalized legal support, which includes help through the UK asylum application process.

AI tech is not just helpful to the government but also to international organisations taking care of international migration. Some organizations are already leveraging machine learning in association with biometric technology. IOM has introduced the Big Data for Migration Alliance project, which intends to use different technologies in international migration….(More)”.

The Rise of Digital Repression: How Technology is Reshaping Power, Politics, and Resistance

Curated on Posted on by Stefaan Verhulst

Book by Steven Feldstein: “The world is undergoing a profound set of digital disruptions that are changing the nature of how governments counter dissent and assert control over their countries. While increasing numbers of people rely primarily or exclusively on online platforms, authoritarian regimes have concurrently developed a formidable array of technological capabilities to constrain and repress their citizens.

In The Rise of Digital Repression, Steven Feldstein documents how the emergence of advanced digital tools bring new dimensions to political repression. Presenting new field research from Thailand, the Philippines, and Ethiopia, he investigates the goals, motivations, and drivers of these digital tactics. Feldstein further highlights how governments pursue digital strategies based on a range of factors: ongoing levels of repression, political leadership, state capacity, and technological development. The international community, he argues, is already seeing glimpses of what the frontiers of repression look like. For instance, Chinese authorities have brought together mass surveillance, censorship, DNA collection, and artificial intelligence to enforce their directives in Xinjiang. As many of these trends go global, Feldstein shows how this has major implications for democracies and civil society activists around the world.

A compelling synthesis of how anti-democratic leaders harness powerful technology to advance their political objectives, The Rise of Digital Repression concludes by laying out innovative ideas and strategies for civil society and opposition movements to respond to the digital autocratic wave….(More)”.

Public policy for open innovation: Opening up to a new domain for research and practice

Curated on Posted on by Stefaan Verhulst

Introduction to Special Issue by Antonio Bob Santos et al: “Open Innovation (OI) emerged as one of the most important research topics in management and economics literature in the last decades, especially when understanding research and change phenomena (Martin 2012, 2019). The concept, originally advanced by Chesbrough (2003), reflects and articulates changes of the global learning economy emerging from the development of digital technologies, ubiquitous innovation, intellectual labour mobility, and the growth of markets for knowledge resources and processes. More recently, Chesbrough and Bogers (2014: 17) redefined OI as “a distributed innovation process based on purposively managed knowledge flows across organizational boundaries” in which the implied notion of the business model could apply to a multitude of organisations and assume a variety of forms (cf. Caraça et al., 2009; Zott et al., 2011). OI has been analysed in different dimensions, such as inside-out and outside-in knowledge flows, across levels of analysis (not only company level, but also individual and ecosystem level), and from different perspectives (such as regional/territorial and national/international) (Bogers et al., 2017; Dahlander and Gann, 2010; West et al., 2014).

OI is also a hot topic in actual business life, with a growing number of companies adopting a more fluid approach, namely what concerns to the knowledge valorisation and collaborative innovation practices. Research has accordingly also put a lot of attention on corporate aspects of OI with a particular focus on how to leverage external knowledge, management of OI networks, and the role of users and communities in OI (Randhawa et al., 2016; Vanhaverbeke et al., 2014; West and Bogers, 2014). Even though it may constitute an important boundary condition for OI practices, there has been a reasonably limited focus on the role of public policies in OI (Bogers et al., 2018; de Jong et al., 2010; Santos, 2016). Nevertheless, recent studies show that the adoption of OI can be stimulated through the existence of public policies favourable to a context of knowledge sharing, collaborative R&D and innovation, knowledge exploitation and valorisation, mobility and qualification of human resources or supporting innovative ideas (Beck et al., 2020; Masucci et al., 2020; Mina et al. 2014; etc.).

All-in-all, a more elaborate focus on the role of public policy in OI is merited, and this is what this special issue provides. Pro-OI innovation policy can be understood as a general posture and the deployment of a specific set of instruments that seek to keep learning processes distributed and knowledge transfers unhurdled, while ensuring self-intended behaviours do not compromise the expansion of effective opportunities for the broader societal constituents. In this special issue the papers extend the portfolio of insights in a variety of ways.

The papers included in this special issue illustrate the breadth of roles that public policy can play in promoting OI practices and in the possible initiatives and instruments that can be applied to this end. The papers also hint at some of the challenges facing public policy to strengthen OI, e.g. with a view of measuring desired OI activities and effects, dealing with local and contextual factors that affect OI-related outcomes, and selecting and reaching appropriate target-actors (SMEs, business accelerators, public research institutes, universities) and contexts (science parks, clusters, regions)with the potential to engage in OI practices but with little or no current practices to build on. We learn that there is great scope for further research to help policymakers navigate the landscape of possible OI-promoting policies and actions and in supporting the design and implementation of effective public policy for OI….(More)”.

Predicting social tipping and norm change in controlled experiments

Curated on Posted on by Stefaan Verhulst

Paper by James Andreoni, Nikos Nikiforakis, and Simon Siegenthaler: “Social tipping—instances of sudden change that upend social order—is rarely anticipated and usually understood only in hindsight. The ability to predict when societies will reach a tipping point has significant implications for welfare, especially when social norms are detrimental. In a large-scale laboratory experiment, we identify a model that accurately predicts social tipping and use it to address a long-standing puzzle: Why do norms sometimes persist when they are detrimental to social welfare? We show that beneficial norm change is often hindered by a desire to avoid the costs associated with transitioning to a new norm. We find that policies that help societies develop a common understanding of the benefits from change foster the abandonment of detrimental norms….(More)”.