The world after coronavirus

Curated on Posted on by Stefaan Verhulst

Yuval Noah Harari at the Financial Times: “Humankind is now facing a global crisis. Perhaps the biggest crisis of our generation. The decisions people and governments take in the next few weeks will probably shape the world for years to come. They will shape not just our healthcare systems but also our economy, politics and culture. We must act quickly and decisively. We should also take into account the long-term consequences of our actions.

When choosing between alternatives, we should ask ourselves not only how to overcome the immediate threat, but also what kind of world we will inhabit once the storm passes. Yes, the storm will pass, humankind will survive, most of us will still be alive — but we will inhabit a different world.  Many short-term emergency measures will become a fixture of life. That is the nature of emergencies. They fast-forward historical processes.

Decisions that in normal times could take years of deliberation are passed in a matter of hours. Immature and even dangerous technologies are pressed into service, because the risks of doing nothing are bigger. Entire countries serve as guinea-pigs in large-scale social experiments. What happens when everybody works from home and communicates only at a distance? What happens when entire schools and universities go online? In normal times, governments, businesses and educational boards would never agree to conduct such experiments. But these aren’t normal times. 

In this time of crisis, we face two particularly important choices. The first is between totalitarian surveillance and citizen empowerment. The second is between nationalist isolation and global solidarity. 

Under-the-skin surveillance

In order to stop the epidemic, entire populations need to comply with certain guidelines. There are two main ways of achieving this. One method is for the government to monitor people, and punish those who break the rules. Today, for the first time in human history, technology makes it possible to monitor everyone all the time. Fifty years ago, the KGB couldn’t follow 240m Soviet citizens 24 hours a day, nor could the KGB hope to effectively process all the information gathered. The KGB relied on human agents and analysts, and it just couldn’t place a human agent to follow every citizen. But now governments can rely on ubiquitous sensors and powerful algorithms instead of flesh-and-blood spooks. 

In their battle against the coronavirus epidemic several governments have already deployed the new surveillance tools. The most notable case is China. By closely monitoring people’s smartphones, making use of hundreds of millions of face-recognising cameras, and obliging people to check and report their body temperature and medical condition, the Chinese authorities can not only quickly identify suspected coronavirus carriers, but also track their movements and identify anyone they came into contact with. A range of mobile apps warn citizens about their proximity to infected patients…

If I could track my own medical condition 24 hours a day, I would learn not only whether I have become a health hazard to other people, but also which habits contribute to my health. And if I could access and analyse reliable statistics on the spread of coronavirus, I would be able to judge whether the government is telling me the truth and whether it is adopting the right policies to combat the epidemic. Whenever people talk about surveillance, remember that the same surveillance technology can usually be used not only by governments to monitor individuals — but also by individuals to monitor governments. 

The coronavirus epidemic is thus a major test of citizenship….(More)”.

Statement of the EDPB Chair on the processing of personal data in the context of the COVID-19 outbreak

Curated on Posted on by Stefaan Verhulst

European Data Protection Board: “Governments, public and private organisations throughout Europe are taking measures to contain and mitigate COVID-19. This can involve the processing of different types of personal data.  

Andrea Jelinek, Chair of the European Data Protection Board (EDPB), said: “Data protection rules (such as GDPR) do not hinder measures taken in the fight against the coronavirus pandemic. However, I would like to underline that, even in these exceptional times, the data controller must ensure the protection of the personal data of the data subjects. Therefore, a number of considerations should be taken into account to guarantee the lawful processing of personal data.”

The GDPR is a broad legislation and also provides for the rules to apply to the processing of personal data in a context such as the one relating to COVID-19. Indeed, the GDPR provides for the legal grounds to enable the employers and the competent public health authorities to process personal data in the context of epidemics, without the need to obtain the consent of the data subject. This applies for instance when the processing of personal data is necessary for the employers for reasons of public interest in the area of public health or to protect vital interests (Art. 6 and 9 of the GDPR) or to comply with another legal obligation.

For the processing of electronic communication data, such as mobile location data, additional rules apply. The national laws implementing the ePrivacy Directive provide for the principle that the location data can only be used by the operator when they are made anonymous, or with the consent of the individuals. The public authorities should first aim for the processing of location data in an anonymous way (i.e. processing data aggregated in a way that it cannot be reversed to personal data). This could enable to generate reports on the concentration of mobile devices at a certain location (“cartography”).  

When it is not possible to only process anonymous data, Art. 15 of the ePrivacy Directive enables the member states to introduce legislative measures pursuing national security and public security *. This emergency legislation is possible under the condition that it constitutes a necessary, appropriate and proportionate measure within a democratic society. If such measures are introduced, a Member State is obliged to put in place adequate safeguards, such as granting individuals the right to judicial remedy….(More)”.

International Humanitarian and Development Aid and Big Data Governance

Curated on Posted on by Stefaan Verhulst

Chapter by Andrej Zwitter: “Modern technology and innovations constantly transform the world. This also applies to humanitarian action and development aid, for example: humanitarian drones, crowd sourcing of information, or the utility of Big Data in crisis analytics and humanitarian intelligence. The acceleration of modernization in these adjacent fields can in part be attributed to new partnerships between aid agencies and new private stakeholders that increasingly become active, such as individual crisis mappers, mobile telecommunication companies, or technological SMEs.

These partnerships, however, must be described as simultaneously beneficial as well as problematic. Many private actors do not subscribe to the humanitarian principles (humanity, impartiality, independence, and neutrality), which govern UN and NGO operations, or are not even aware of them. Their interests are not solely humanitarian, but may include entrepreneurial agendas. The unregulated use of data in humanitarian intelligence has already caused negative consequences such as the exposure of sensitive data about aid agencies and of victims of disasters.

This chapter investigates the emergent governance trends around data innovation in the humanitarian and development field. It takes a look at the ways in which the field tries to regulate itself and the utility of the humanitarian principles for Big Data analytics and data-driven innovation. It will argue that it is crucially necessary to formulate principles for data governance in the humanitarian context in order to ensure the safeguarding of beneficiaries that are particularly vulnerable. In order to do that, the chapter proposes to reinterpret the humanitarian principles to accommodate the new reality of datafication of different aspects of society…(More)”.

Rheomesa. A New Global System for Catastrophe Prevention, Response & Recovery

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Paper by Andrew Doss, Jonas Bedford-Strohm and Leanne Erdberg Steadman: “This paper identifies three structural vacuums in catastrophe governance today that allow for the greatest risks humanity faces to be externalized from decision-making. To mitigate the impact of these risks, The Rheomesa (“fluid table”) provides (1) a deliberative decision-making process between currently siloed entities in various sectors managing the outcome of catastrophes, including government, the private sector, NGOs, IGOs, and hybrid entities, with (2) a prospective, long-term accountability and incentive mechanism that (3) comprehensively addresses the three interdependent tasks societies face surrounding catastrophes – prevention, response, and recovery….(More)”.

The State of Open Humanitarian Data

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Report by Centre for Humanitarian Data: “The goal of this report is to increase awareness of the data available for humanitarian response activities and to highlight what is missing, as measured through OCHA’s Humanitarian Data Exchange (HDX) platform. We want to recognize the valuable and long-standing contributions of data-sharing organizations. We also want to be more targeted in our outreach on what data is required to understand crises so that new actors might be compelled to join the platform. Data is not an end in itself but a critical ingredient to the analysis that informs decision making. With nearly 168 million people in need of humanitarian assistance in 2020 — the highest figure in decades — there is no time, or data, to lose…(More)”.

Data Protection in the Humanitarian Sector – A Blockchain Approach

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Report by Andrej Verity and Irene Solaiman: “Data collection and storage are becoming increasingly digital. In the humanitarian sector, data motivates action, informing organizations who then determine priorities and resource allocation in crises.

“Humanitarians are dependent on technology and on the Internet. When life-saving aid isn’t delivered on time and to the right beneficiaries, people can die.” -Brookings

In the age of information and cyber warfare, humanitarian organizations must take measures to protect civilians, especially those in critical and vulnerable positions.

“Data privacy and ensuring protection from harm, including the provision of data security, are therefore fundamentally linked—and neither can be realized without the other.” -The Signal Code

Information in the wrong hands can risk lives or even force aid organizations to shut down. For example, in 2009, Sudan expelled over a dozen international nongovernmental organizations (NGOs) that were deemed key to maintaining a lifeline to 4.7 million people in western Darfur. The expulsion occurred after the Sudanese Government collected Internet-accessible information that made leadership fear international criminal charges. Responsible data protection is a crucial component of cybersecurity. As technology develops, so do threats and data vulnerabilities. Emerging technologies such as blockchain provide further security to sensitive information and overall data storage. Still, with new technologies come considerations for implementation…(More)”.

Responsible Data for Children

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New Site and Report by UNICEF and The GovLab: “RD4C seeks to build awareness regarding the need for special attention to data issues affecting children—especially in this age of changing technology and data linkage; and to engage with governments, communities, and development actors to put the best interests of children and a child rights approach at the center of our data activities. The right data in the right hands at the right time can significantly improve outcomes for children. The challenge is to understand the potential risks and ensure that the collection, analysis and use of data on children does not undermine these benefits.

Drawing upon field-based research and established good practice, RD4C aims to highlight and support best practice data responsibility; identify challenges and develop practical tools to assist practitioners in evaluating and addressing them; and encourage a broader discussion on actionable principles, insights, and approaches for responsible data management.

We are finally getting better at predicting organized conflict

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Tate Ryan-Mosley at MIT Technology Review: “People have been trying to predict conflict for hundreds, if not thousands, of years. But it’s hard, largely because scientists can’t agree on its nature or how it arises. The critical factor could be something as apparently innocuous as a booming population or a bad year for crops. Other times a spark ignites a powder keg, as with the assassination of Archduke Franz Ferdinand of Austria in the run-up to World War I.

Political scientists and mathematicians have come up with a slew of different methods for forecasting the next outbreak of violence—but no single model properly captures how conflict behaves. A study published in 2011 by the Peace Research Institute Oslo used a single model to run global conflict forecasts from 2010 to 2050. It estimated a less than .05% chance of violence in Syria. Humanitarian organizations, which could have been better prepared had the predictions been more accurate, were caught flat-footed by the outbreak of Syria’s civil war in March 2011. It has since displaced some 13 million people.

Bundling individual models to maximize their strengths and weed out weakness has resulted in big improvements. The first public ensemble model, the Early Warning Project, launched in 2013 to forecast new instances of mass killing. Run by researchers at the US Holocaust Museum and Dartmouth College, it claims 80% accuracy in its predictions.

Improvements in data gathering, translation, and machine learning have further advanced the field. A newer model called ViEWS, built by researchers at Uppsala University, provides a huge boost in granularity. Focusing on conflict in Africa, it offers monthly predictive readouts on multiple regions within a given state. Its threshold for violence is a single death.

Some researchers say there are private—and in some cases, classified—predictive models that are likely far better than anything public. Worries that making predictions public could undermine diplomacy or change the outcome of world events are not unfounded. But that is precisely the point. Public models are good enough to help direct aid to where it is needed and alert those most vulnerable to seek safety. Properly used, they could change things for the better, and save lives in the process….(More)”.

CROWD4EMS: a Crowdsourcing Platform for Gathering and Geolocating Social Media Content in Disaster Response

Curated on Posted on by Stefaan Verhulst

Paper by Ravi Shankar et al” Increase in access to mobile phone devices and social media networks has changed the way people report and respond to disasters. Community-driven initiatives such as Stand By Task Force (SBTF) or GISCorps have shown great potential by crowdsourcing the acquisition, analysis, and geolocation of social media data for disaster responders. These initiatives face two main challenges: (1) most of social media content such as photos and videos are not geolocated, thus preventing the information to be used by emergency responders, and (2) they lack tools to manage volunteers contributions and aggregate them in order to ensure high quality and reliable results. This paper illustrates the use of a crowdsourcing platform that combines automatic methods for gathering information from social media and crowdsourcing techniques, in order to manage and aggregate volunteers contributions. High precision geolocation is achieved by combining data mining techniques for estimating the location of photos and videos from social media, and crowdsourcing for the validation and/or improvement of the estimated location.

The evaluation of the proposed approach is carried out using data related to the Amatrice Earthquake in 2016, coming from Flickr, Twitter and Youtube. A common data set is analyzed and geolocated by both the volunteers using the proposed platform and a group of experts. Data quality and data reliability is assessed by comparing volunteers versus experts results. Final results are shown in a web map service providing a global view of the information social media provided about the Amatrice Earthquake event…(More)”.

Five Ethical Principles for Humanitarian Innovation

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Peter Batali, Ajoma Christopher & Katie Drew in the Stanford Social Innovation Review: “…Based on this experience, UNHCR and CTEN developed a pragmatic, refugee-led, “good enough” approach to experimentation in humanitarian contexts. We believe a wide range of organizations, including grassroots community organizations and big-tech multinationals, can apply this approach to ensure that the people they aim to help hold the reigns of the experimentation process.

1. Collaborate Authentically and Build Intentional Partnerships

Resource and information asymmetry are inherent in the humanitarian system. Refugees have long been constructed as “‘victims”’ in humanitarian response, waiting for “salvation” from heroic humanitarians. Researcher Matthew Zagor describes this construct as follows: “The genuine refugee … is the passive, coerced, patient refugee, the one waiting in the queue—the victim, anticipating our redemptive touch, defined by the very passivity which in our gaze both dehumanizes them, in that they lack all autonomy in our eyes, and romanticizes them as worthy in their potentiality.”

Such power dynamics make authentic collaboration challenging….

2. Avoid Technocratic Language

Communication can divide us or bring us together. Using exclusive or “expert” terminology (terms like “ideation,” “accelerator,” and “design thinking”) or language that reinforces power dynamics or assigns an outsider role (such as “experimenting on”) can alienate community participants. Organizations should aim to use inclusive language than everyone understands, as well as set a positive and realistic tone. Communication should focus on the need to co-develop solutions with the community, and the role that testing or trying something new can play….

3. Don’t Assume Caution Is Best

Research tells us that we feel more regret over actions that lead to negative outcomes than we do over inactions that lead to the same or worse outcomes. As a result, we tend to perceive and weigh action and inaction unequally. So while humanitarian organizations frequently consider the implications of our actions and the possible negative outcome for communities, we don’t always consider the implications of doing nothing. Is it ethical to continue an activity that we know isn’t as effective as it could be, when testing small and learning fast could reap real benefits? In some cases, taking a risk might, in fact, be the least risky path of action. We need to always ask ourselves, “Is it really ethical to do nothing?”…

4. Choose Experiment Participants Based on Values

Many humanitarian efforts identify participants based on their societal role, vulnerability, or other selection criteria. However, these methods often lead to challenges related to incentivization—the need to provide things like tea, transportation, or cash payments to keep participants engaged. Organizations should instead consider identifying participants who demonstrate the values they hope to promote—such as collaboration, transparency, inclusivity, or curiosity. These community members are well-poised to promote inclusivity, model positive behaviors, and engage participants across the diversity of your community….

5. Monitor Community Feedback and Adapt

While most humanitarian agencies know they need to listen and adapt after establishing communication channels, the process remains notoriously challenging. One reason is that community members don’t always share their feedback on experimentation formally; feedback sometimes comes from informal channels or even rumors. Yet consistent, real-time feedback is essential to experimentation. Listening is the pressure valve in humanitarian experimentation; it allows organizations to adjust or stop an experiment if the community flags a negative outcome….(More)”.