The Refugee Identity

Curated on Posted on by Stefaan Verhulst

Medium essay byPaul Currion: “From Article 6 of the UN Declaration of Human Rights (“Everyone has the right to recognition everywhere as a person before the law” ) to Sustainable Development Goal 16.9 (“By 2030, provide legal identity for all, including birth registration”) to the formation of the ID2020 Alliance (whose fourth goal is to “Enable more efficient and effective delivery of development and humanitarian aid), identity has been central to the modern project of development.

Discussion of identity within the aid sector is embedded in a much larger set of political, social, economic, legal and technical discussions at a national and global level. This review will not address that larger set of discussions, but will instead focus specifically on humanitarian aid, and more specifically refugees, and more specifically still on refugee camps as a location in which identity provision is both critical and contested. It is the first output of a DFID-funded research project examining data requirements for service delivery (by UN agencies and NGOs) within refugee camps.

Given how central the issue of identity is for refugees, there is surprisingly little literature about how identity provision is implemented in the context of refugee camps.1 This essay introduces some of the critical issues relating to identity (particularly in the context of the digitisation of aid) and explores how they relate to the research project. It is accompanied by a bibliography for those who are interested in exploring the issue further.,,,(More)”.

Is Distributed Ledger Technology Built for Personal Data?

Curated on Posted on by Stefaan Verhulst

Paper by Henry Chang: “Some of the appealing characteristics of distributed ledger technology (DLT), which blockchain is a type of, include guaranteed integrity, disintermediation and distributed resilience. These characteristics give rise to the possible consequences of immutability, unclear ownership, universal accessibility and trans-border storage. These consequences have the potential to contravene data protection principles of Purpose Specification, Use Limitation, Data Quality, Individual Participation and Trans-Border Data Flow. This paper endeavors to clarify the various types of DLTs, how they work, why they exhibit the depicted characteristics and the consequences. Using the universal privacy principles developed by the Organisation of Economic Cooperation and Development (OECD), this paper then describes how each of the consequence causes concerns for privacy protection and how attempts are being made to address them in the design and implementation of various applications of blockchain and DLT, and indicates where further research and best-practice developments lie….(More)”.

Technology Landscape for Digital Identification

Curated on Posted on by Stefaan Verhulst

World Bank Report: “Robust, inclusive, and responsible identification systems can increase access to finance, healthcare, education, and other critical services and benefits. Identification systems are also key to improving efficiency and enabling innovation for public- and private-sector services, such as greater efficiency in the delivery of social safety nets and facilitating the development of digital economies. However, the World Bank estimates that more than 1.1 billion individuals do not have official proof of their identity.10 New technologies provide countries with the opportunity to leapfrog paper-based systems and rapidly establish a robust identification infrastructure. As a result, the countries are increasingly adopting nationwide digital identification (ID) programs and leveraging them in other sectors.

Whether a country is enhancing existing ID systems or implementing new systems from the ground up, technology choices are critical to the success of digital identification systems. A number of new technologies are emerging to enable various aspects of ID lifecycle. For some of these technologies, no large-scale studies have been done; for others, current speculation makes objective evaluations difficult.

This report is a first attempt to develop a comprehensive overview of the current technology landscape for digital identification. It is intended to serve as a framework for understanding the myriad options and considerations of technology in this rapidly advancing agenda and in no way is intended to provide advice on specific technologies, particularly given there are a number of other considerations and country contexts which need to be considered. This report also does not advocate the use of a certain technology from a particular vendor for any particular application.

While some technologies are relatively easy to use and affordable, others are costly or so complex that using them on a large scale presents daunting challenges. This report provides practitioners with an overview of various technologies and advancements that are especially relevant for digital identification systems. It highlights key benefits and challenges associated with each technology. It also provides a framework for assessing each technology on multiple criteria, including length of time it has been in use, its ease of integration with legacy and future systems, and its interoperability with other technologies. The practitioners and stakeholders who read this are reminded to bear in mind that the technologies associated with ID systems are rapidly evolving, and that this report, prepared in early 2018, is a snapshot in time. Therefore, technology limitations and challenges highlighted in this report today may not be applicable in the years to come….(More)”

How to Make A.I. That’s Good for People

Curated on Posted on by Stefaan Verhulst

Fei-Fei Li in the New York Times: “For a field that was not well known outside of academia a decade ago, artificial intelligence has grown dizzyingly fast. Tech companies from Silicon Valley to Beijing are betting everything on it, venture capitalists are pouring billions into research and development, and start-ups are being created on what seems like a daily basis. If our era is the next Industrial Revolution, as many claim, A.I. is surely one of its driving forces.

It is an especially exciting time for a researcher like me. When I was a graduate student in computer science in the early 2000s, computers were barely able to detect sharp edges in photographs, let alone recognize something as loosely defined as a human face. But thanks to the growth of big data, advances in algorithms like neural networks and an abundance of powerful computer hardware, something momentous has occurred: A.I. has gone from an academic niche to the leading differentiator in a wide range of industries, including manufacturing, health care, transportation and retail.

I worry, however, that enthusiasm for A.I. is preventing us from reckoning with its looming effects on society. Despite its name, there is nothing “artificial” about this technology — it is made by humans, intended to behave like humans and affects humans. So if we want it to play a positive role in tomorrow’s world, it must be guided by human concerns.

I call this approach “human-centered A.I.” It consists of three goals that can help responsibly guide the development of intelligent machines.

First, A.I. needs to reflect more of the depth that characterizes our own intelligence….

No technology is more reflective of its creators than A.I. It has been said that there are no “machine” values at all, in fact; machine values arehuman values. A human-centered approach to A.I. means these machines don’t have to be our competitors, but partners in securing our well-being. However autonomous our technology becomes, its impact on the world — for better or worse — will always be our responsibility….(More).

NASA’s Asteroid Grand Challenge: Strategy, results, and lessons learned

Curated on Posted on by Stefaan Verhulst

Jennifer L. Gustetic et al in Space Policy: “Beginning in 2012, NASA utilized a strategic process to identify broad societal questions, or grand challenges, that are well suited to the aerospace sector and align with national priorities. This effort generated NASA’s first grand challenge, the Asteroid Grand Challenge (AGC), a large-scale effort using multi-disciplinary collaborations and innovative engagement mechanisms focused on finding and addressing asteroid threats to human populations. In April 2010, President Barack Obama announced a mission to send humans to an asteroid by 2025. This resulted in the agency’s Asteroid Redirect Mission (ARM) to leverage and maximize existing robotic and human efforts to capture and reroute an asteroid, with the goal of eventual human exploration. The AGC, initiated in 2013, complemented ARM by expanding public participation, partnerships, and other approaches to find, understand, and overcome these potentially harmful asteroids.

This paper describes a selection of AGC activities implemented from 2013 to 2017 and their results, excluding those conducted by NASA’s Near-Earth Object Observations Program and other organizations. The strategic development of the initiative is outlined as well as initial successes, strengths, and weaknesses resulting from the first four years of AGC activities and approaches. Finally, we describe lesson learned and areas for continued work and study. The AGC lessons learned and strategies could inform the work of other agencies and organizations seeking to conduct a global scientific investigation with matrixed organizational support, multiple strategic partners, and numerous internal and external open innovation approaches and audiences….(More)”.

 

Data Science Landscape

Curated on Posted on by Stefaan Verhulst

Book edited by Usha Mujoo Munshi and Neeta Verma: “The edited volume deals with different contours of data science with special reference to data management for the research innovation landscape. The data is becoming pervasive in all spheres of human, economic and development activity. In this context, it is important to take stock of what is being done in the data management area and begin to prioritize, consider and formulate adoption of a formal data management system including citation protocols for use by research communities in different disciplines and also address various technical research issues. The volume, thus, focuses on some of these issues drawing typical examples from various domains….

In all, there are 21 chapters (with 21st Chapter addressing four different core aspects) written by eminent researchers in the field which deal with key issues of S&T, institutional, financial, sustainability, legal, IPR, data protocols, community norms and others, that need attention related to data management practices and protocols, coordinate area activities, and promote common practices and standards of the research community globally. In addition to the aspects touched above, the national / international perspectives of data and its various contours have also been portrayed through case studies in this volume. …(More)”.

Trustworthy data will transform the world

Curated on Posted on by Stefaan Verhulst

John Thornhill at the Financial Times: “The internet’s original sin was identified as early as 1993 in a New Yorker cartoon. “On the internet, nobody knows you’re a dog,” the caption ran beneath an illustration of a pooch at a keyboard. That anonymity has brought some benefits. But it has also created myriad problems, injecting distrust into the digital world. If you do not know the provenance and integrity of information and data, how can you trust their veracity?

That has led to many of the scourges of our times, such as cyber crime, identity theft and fake news. In his Alan Turing Institute lecture in London last week, the American computer scientist Sandy Pentland outlined the massive gains that could result from trusted data.

The MIT professor argued that the explosion of such information would give us the capability to understand our world in far more detail than ever before. Most of what we know in the fields of sociology, psychology, political science and medicine is derived from tiny experiments in controlled environments. But the data revolution enables us to observe behaviour as it happens at mass scale in the real world. That feedback could provide invaluable evidence about which theories are most valid and which policies and products work best.

The promise is that we make soft social science harder and more predictive. That, in turn, could lead to better organisations, fairer government, and more effective monitoring of our progress towards achieving collective ambitions, such as the UN’s sustainable development goals. To take one small example, Mr Pentland illustrated the strong correlation between connectivity and wealth. By studying the telephone records of 100,000 users in south-east Asia, researchers have plotted social connectivity against income. The conclusion: “The more diverse your connections, the more money you have.” This is not necessarily a causal relationship but it does have a strong causal element, he suggested.

Similar studies of European cities have shown an almost total segregation between groups of different socio-economic status. That lack of connectivity has to be addressed if our politics is not to descend further into a meaningless dialogue.

Data give us a new way to measure progress.

For years, the Open Data movement has been working to create public data sets that can better inform decision making. This worldwide movement is prising open anonymised public data sets, such as transport records, so that they can be used by academics, entrepreneurs and civil society groups. However, much of the most valuable data is held by private entities, notably the consumer tech companies, telecoms operators, retailers and banks. “The big win would be to include private data as a public good,” Mr Pentland said….(More)”.

Mobile Data Collection Toolkit

Curated on Posted on by Stefaan Verhulst

Guide for the use of MDC in the humanitarian and development field: “This webpage aims at sharing documentation produced jointly by Terre des hommes (Tdh) and CartONG to help humanitarians and development actors use Mobile Data Collection (MDC)more efficiently in the field.

You will find tutorials and training material concerning all the phases of MDC, from thinking through the prerequisites of using MDC to the preparation of your forms and tools and the analysis of your data.

In addition to the MDC documentation you can also find a “Starter Kit” for data protection in humanitarian and development operations, as well as “Data Visualization” material, in the Analysis page,  produced to help organizations to better visualize the results of their data analyses.

These were made for Terre des hommes staff but are shared “as-is” as they could be useful for other NGOs. …(More)”.

Digitalization, Collective Intelligence, and Entrepreneurship in the Care Sector

Curated on Posted on by Stefaan Verhulst

Chapter by Erik Lakomaa in Managing Digital Transformation edited by Per Andersson, Staffan Movin, Magnus Mähring, Robin Teigland, and Karl Wennberg: “Parallel to the formal private or public (health) care organisations in Europe, a number of community-driven care projects have emerged. They may supplement the formal organisations by reducing costs or provide care to groups that, for some reason, do not have access to the formal sector. Drawing upon the Ostromian theory of commons and on previous theory and research on open software development (which share some of the characteristics of “open care”), I use historical cases of community-driven care to examine the prospects for such projects to help remedy the cost crisis in the care sector. I explore under which institutional settings “open care” is likely to emerge and when open care projects have potential to scale. It is found that open care is more likely to emerge and prosper when it builds upon existing organisational structures: where the participants do not need to create new hierarchies or governance structures, and where they share common values…(More)”.

Global Fishing Watch And The Power Of Data To Understand Our Natural World

Curated on Posted on by Stefaan Verhulst

Kalev Leetaru at Forbes: “A year and a half ago I wrote about the public debut of the Global Fishing Watch project as a showcase of what becomes possible when massive datasets are made accessible to the general public through easy-to-use interfaces that allow them to explore the planet they inhabit. At the time I noted how the project drove home the divide between the “glittering technological innovation of Silicon Valley and the technological dark ages of the development community” and what becomes possible when technologists and development organizations come together to apply incredible technology not for commercial gain, but rather to save the world itself. Continuing those efforts, last week Global Fishing Watch launched what it describes as the “the first ever dataset of global industrial fishing activities (all countries, all gears),” making the entire dataset freely accessible to seed new scientific, activist, governmental, journalistic and citizen understanding of the state of global fishing.

The Global Fishing Watch project stands as a powerful model for data-driven development work done right and hopefully, the rise of notable efforts like it will eventually catalyze the broader development community to emerge from the stone age of technology and more openly embrace the technological revolution. While it has a very long way to go, there are signs of hope for the development community as pockets of innovation begin to infuse the power of data-driven decision making and situational awareness into everything from disaster response to proactive planning to shaping legislative action.

Bringing technologists and development organizations together is not always that easy and the most creative solutions aren’t always to be found among the “usual suspects.” Open data and open challenges built upon them offer the potential for organizations to reach beyond the usual communities they interact with and identify innovative new approaches to the grand challenges of their fields. Just last month a collaboration of the World Bank, WeRobotics and OpenAerialMap launched a data challenge to apply deep learning to assess aerial imagery in the immediate aftermath of disasters to determine the impact to food producing trees and to road networks. By launching the effort as an open AI challenge, the goal is to reach the broader AI and open development communities at the forefront of creative and novel algorithmic approaches….(More)”.