Migration Data Portal

Curated on Posted on by Stefaan Verhulst

New portal managed and developed by IOM’s Global Migration Data Analysis Centre (GMDAC)“…aims to serve as a unique access point to timely, comprehensive migration statistics and reliable information about migration data globally. The site is designed to help policy makers, national statistics officers, journalists and the general public interested in the field of migration to navigate the increasingly complex landscape of international migration data, currently scattered across different organisations and agencies.

Especially in critical times, such as those faced today, it is essential to ensure that responses to migration are based on sound facts and accurate analysis. By making the evidence about migration issues accessible and easy to understand, the Portal aims to contribute to a more informed public debate….

The five main sections of the Portal are designed to help you quickly and easily find the data and information you need.

  • DATA – Our interactive world map visualizes international, publicly-available and internationally comparable migration data.
  • THEMES – Thematic overviews explain how various aspects of migration are measured, what are the data sources, their strengths and weaknesses and provide context and analysis of key migration data.
  • TOOLS – Migration data tools are regularly added to help you find the right tools, guidelines and manuals on how to collect, interpret and disseminate migration data.
  • Sustainable Development Goals (SDGs) and the Global Compact on Migration (GCM) – Migration Data, the SDGs and the new Global Compact on Migration (GCM) – Reviews the migration-related targets in the SDGs, how they are defined and measured, and provides information on the new GCM and the migration data needs to support its implementation.
  • BLOG – Our blog and the Talking Migration Data video series provide a place for the migration data community to share their opinion on new developments and policy, new data or methods….(More)”.

Accountability of AI Under the Law: The Role of Explanation

Curated on Posted on by Stefaan Verhulst

Paper by Finale Doshi-Velez and Mason Kortz: “The ubiquity of systems using artificial intelligence or “AI” has brought increasing attention to how those systems should be regulated. The choice of how to regulate AI systems will require care. AI systems have the potential to synthesize large amounts of data, allowing for greater levels of personalization and precision than ever before—applications range from clinical decision support to autonomous driving and predictive policing. That said, our AIs continue to lag in common sense reasoning [McCarthy, 1960], and thus there exist legitimate concerns about the intentional and unintentional negative consequences of AI systems [Bostrom, 2003, Amodei et al., 2016, Sculley et al., 2014]. How can we take advantage of what AI systems have to offer, while also holding them accountable?

In this work, we focus on one tool: explanation. Questions about a legal right to explanation from AI systems was recently debated in the EU General Data Protection Regulation [Goodman and Flaxman, 2016, Wachter et al., 2017a], and thus thinking carefully about when and how explanation from AI systems might improve accountability is timely. Good choices about when to demand explanation can help prevent negative consequences from AI systems, while poor choices may not only fail to hold AI systems accountable but also hamper the development of much-needed beneficial AI systems.

Below, we briefly review current societal, moral, and legal norms around explanation, and then focus on the different contexts under which explanation is currently required under the law. We find that there exists great variation around when explanation is demanded, but there also exist important consistencies: when demanding explanation from humans, what we typically want to know is whether and how certain input factors affected the final decision or outcome.

These consistencies allow us to list the technical considerations that must be considered if we desired AI systems that could provide kinds of explanations that are currently required of humans under the law. Contrary to popular wisdom of AI systems as indecipherable black boxes, we find that this level of explanation should generally be technically feasible but may sometimes be practically onerous—there are certain aspects of explanation that may be simple for humans to provide but challenging for AI systems, and vice versa. As an interdisciplinary team of legal scholars, computer scientists, and cognitive scientists, we recommend that for the present, AI systems can and should be held to a similar standard of explanation as humans currently are; in the future we may wish to hold an AI to a different standard….(More)”

From #Resistance to #Reimagining governance

Curated on Posted on by Stefaan Verhulst

Stefaan G. Verhulst in Open Democracy: “…There is no doubt that #Resistance (and its associated movements) holds genuine transformative potential. But for the change it brings to be meaningful (and positive), we need to ask the question: What kind of government do we really want?

Working to maintain the status quo or simply returning to, for instance, a pre-Trump reality cannot provide for the change we need to counter the decline in trust, the rise of populism and the complex social, economic and cultural problems we face. We need a clear articulation of alternatives.  Without such an articulation, there is a danger of a certain hollowness and dispersion of energies. The call for #Resistance requires a more concrete –and ultimately more productive – program that is concerned not just with rejecting or tearing down, but with building up new institutions and governance processes. What’s needed, in short, is not simply #Resistance.

Below, I suggest six shifts that can help us reimagine governance for the twenty-first century. Several of these shifts are enabled by recent technological changes (e.g., the advent of big data, blockchain and collective intelligence) as well as other emerging methods such as design thinking, behavioral economics, and agile development.

Some of the shifts I suggest have been experimented with, but they have often been developed in an ad hoc manner without a full understanding of how they could make a more systemic impact. Part of the purpose of this paper is to begin the process of a more systematic enquiry; the following amounts to a preliminary outline or blueprint for reimagined governance for the twenty-first century.

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  • Shift 1: from gatekeeper to platform…
  • Shift 2: from inward to user-and-problem orientation…
  • Shift 3: from closed to open…
  • Shift 4: from deliberation to collaboration and co-creation…
  • Shift 5: from ideology to evidence-based…
  • Shift 6: from centralized to distributed… (More)

Code and Clay, Data and Dirt: Five Thousand Years of Urban Media

Curated on Posted on by Stefaan Verhulst

Book by Shannon Mattern: “For years, pundits have trumpeted the earthshattering changes that big data and smart networks will soon bring to our cities. But what if cities have long been built for intelligence, maybe for millennia? In Code and Clay, Data and Dirt Shannon Mattern advances the provocative argument that our urban spaces have been “smart” and mediated for thousands of years.

Offering powerful new ways of thinking about our cities, Code and Clay, Data and Dirt goes far beyond the standard historical concepts of origins, development, revolutions, and the accomplishments of an elite few. Mattern shows that in their architecture, laws, street layouts, and civic knowledge—and through technologies including the telephone, telegraph, radio, printing, writing, and even the human voice—cities have long negotiated a rich exchange between analog and digital, code and clay, data and dirt, ether and ore.

Mattern’s vivid prose takes readers through a historically and geographically broad range of stories, scenes, and locations, synthesizing a new narrative for our urban spaces. Taking media archaeology to the city’s streets, Code and Clay, Data and Dirt reveals new ways to write our urban, media, and cultural histories….(More)”.

Business Models For Sustainable Research Data Repositories

Curated on Posted on by Stefaan Verhulst

OECD Report: “In 2007, the OECD Principles and Guidelines for Access to Research Data from Public Funding were published and in the intervening period there has been an increasing emphasis on open science. At the same time, the quantity and breadth of research data has massively expanded. So called “Big Data” is no longer limited to areas such as particle physics and astronomy, but is ubiquitous across almost all fields of research. This is generating exciting new opportunities, but also challenges.

The promise of open research data is that they will not only accelerate scientific discovery and improve reproducibility, but they will also speed up innovation and improve citizen engagement with research. In short, they will benefit society as a whole. However, for the benefits of open science and open research data to be realised, these data need to be carefully and sustainably managed so that they can be understood and used by both present and future generations of researchers.

Data repositories – based in local and national research institutions and international bodies – are where the long-term stewardship of research data takes place and hence they are the foundation of open science. Yet good data stewardship is costly and research budgets are limited. So, the development of sustainable business models for research data repositories needs to be a high priority in all countries. Surprisingly, perhaps, little systematic analysis has been done on income streams, costs, value propositions, and business models for data repositories, and that is the gap this report attempts to address, from a science policy perspective…..

This project was designed to take up the challenge and to contribute to a better understanding of how research data repositories are funded, and what developments are occurring in their funding. Central questions included:

  • How are data repositories currently funded, and what are the key revenue sources?
  • What innovative revenue sources are available to data repositories?
  • How do revenue sources fit together into sustainable business models?
  • What incentives for, and means of, optimising costs are available?
  • What revenue sources and business models are most acceptable to key stakeholders?…(More)”

Understanding Design Thinking, Lean, and Agile

Curated on Posted on by Stefaan Verhulst

Free ebook by Jonny Schneider: “Highly touted methodologies, such as Agile, Lean, and Design Thinking, leave many organizations bamboozled by an unprecedented array of processes, tools, and methods for digital product development. Many teams meet their peril trying to make sense of these options. How do the methods fit together to achieve the right outcome? What’s the best approach for your circumstances?

In this insightful report, Jonny Schneider from ThoughtWorks shows you how to diagnose your situation, understand where you need more insight to move forward, and then choose from a range of tactics that can move your team closer to clarity.

Blindly applying any model, framework, or method seldom delivers the desired result. Agile began as a better answer for delivering software. Lean focuses on product success. And Design Thinking is an approach for exploring opportunities and problems to solve. This report shows you how to evaluate your situation before committing to one, two, or all three of these techniques.

  • Understand how design thinking, the lean movement, and agile software development can make a difference
  • Define your beliefs and assumptions as well as your strategy
  • Diagnose the current condition and explore possible futures
  • Decide what to learn, and how to learn it, through fast research and experimentation
  • Decentralize decisions with purpose-driven, collaborative teams
  • Prioritize and measure value by responding to customer demand…(More)”

There’s more to evidence-based policies than data: why it matters for healthcare

Curated on Posted on by Stefaan Verhulst

 at The Conversation: “The big question is: how can countries strengthen their health systems to deliver accessible, affordable and equitable care when they are often under-financed and governed in complex ways?

One answer lies in governments developing policies and programmes that are informed by evidence of what works or doesn’t. This should include what we would call “traditional data”, but should also include a broader definition of evidence. This would mean including, for example, information from citizens and stakeholders as well as programme evaluations. In this way, policies can be made more relevant for the people they affect.

Globally there is an increasing appreciation for this sort of policymaking that relies of a broader definition of evidence. Countries such as South Africa, Ghana and Thailand provide good examples.

What is evidence?

Using evidence to inform the development of health care has grown out of the use of science to choose the best decisions. It is based on data being collected in a methodical way. This approach is useful but it can’t always be neatly applied to policymaking. There are several reasons for this.

The first is that there are many different types of evidence. Evidence is more than data, even though the terms are often used to mean the same thing. For example, there is statistical and administrative data, research evidence, citizen and stakeholder information as well as programme evaluations.

The challenge is that some of these are valued more than others. More often than not, statistical data is more valued in policymaking. But both researchers and policymakers must acknowledge that for policies to be sound and comprehensive, different phases of policymaking process would require different types of evidence.

Secondly, data-as-evidence is only one input into policymaking. Policymakers face a long list of pressures they must respond to, including time, resources, political obligations and unplanned events.

Researchers may push technically excellent solutions designed in research environments. But policymakers may have other priorities in mind: are the solutions being put to them practical and affordable?Policymakers also face the limitations of having to balance various constituents while straddling the constraints of the bureaucracies they work in.

Researchers must recognise that policymakers themselves are a source of evidence of what works or doesn’t. They are able to draw on their own experiences, those of their constituents, history and their contextual knowledge of the terrain.

What this boils down to is that for policies that are based on evidence to be effective, fewer ‘push/pull’ models of evidence need to be used. Instead the models where evidence is jointly fashioned should be employed.

This means that policymakers, researchers and other key actors (like health managers or communities) must come together as soon as a problem is identified. They must first understand each other’s ideas of evidence and come to a joint conclusion of what evidence would be appropriate for the solution.

In South Africa, for example, the Department of Environmental Affairshas developed a four-phase process to policymaking. In the first phase, researchers and policymakers come together to set the agenda and agree on the needed solution. Their joint decision is then reviewed before research is undertaken and interpreted together….(More)”.

Transitioning Towards a Knowledge Society: Qatar as a Case Study

Curated on Posted on by Stefaan Verhulst

Book by Julia Gremm, Julia Barth, Kaja J. Fietkiewicz and Wolfgang G. Stock: “The book offers a critical evaluation of Qatar’s path from oil- and gas-based industries to a knowledge-based economy. This book gives basic information about the region and the country, including the geographic and demographic data, the culture, the politics and the economy, the health care conditions and the education system. It introduces the concepts of knowledge society and knowledge-based development and adds factual details about Qatar by interpreting indicators of the development status. Subsequently, the research methods that underlie the study are described, which offers information on the eGovernment study analyzing the government-citizen relationship, higher education institutions and systems, its students and the students’ way into the labor market. This book has an audience with economists, sociologists, political scientists, geographers, information scientists and other researchers on the knowledge society, but also all researchers and practitioners interested in the Arab Oil States and their future….(More)”.

Blockchain: Unpacking the disruptive potential of blockchain technology for human development.

Curated on Posted on by Stefaan Verhulst

IDRC white paper: “In the scramble to harness new technologies to propel innovation around the world, artificial intelligence, robotics, machine learning, and blockchain technologies are being explored and deployed in a wide variety of contexts globally.

Although blockchain is one of the most hyped of these new technologies, it is also perhaps the least understood. Blockchain is the distributed ledger — a database that is shared across multiple sites or institutions to furnish a secure and transparent record of events occurring during the provision of a service or contract — that supports cryptocurrencies (digital assets designed to work as mediums of exchange).

Blockchain is now underpinning applications such as land registries and identity services, but as its popularity grows, its relevance in addressing socio-economic gaps and supporting development targets like the globally-recognized UN Sustainable Development Goals is critical to unpack. Moreover, for countries in the global South that want to be more than just end users or consumers, the complex infrastructure requirements and operating costs of blockchain could prove challenging. For the purposes of real development, we need to not only understand how blockchain is workable, but also who is able to harness it to foster social inclusion and promote democratic governance.

This white paper explores the potential of blockchain technology to support human development. It provides a non-technical overview, illustrates a range of applications, and offers a series of conclusions and recommendations for additional research and potential development programming….(More)”.

Decoding Data Use: What evidence do world leaders want to achieve their goals?

Curated on Posted on by Stefaan Verhulst

Paper by Samantha Custer, Takaaki Masaki, and Carolyn Iwicki: “Information is “never the hero”, but it plays a supporting role in how leaders allocate scarce resources and accelerate development in their communities. Even in low- and middle-income countries, decision-makers have ample choices in sourcing evidence from a growing field of domestic and international data providers. However, more information is not necessarily better if it misses the mark for what leaders need to monitor their country’s progress. Claims that information is the “world’s most valuable resource” and calls for a “data revolution” will ring hollow if we can’t decode what leaders actually use — and why.

In a new report, Decoding Data Use: How leaders source data and use it to accelerate development, AidData reveals what 3500 leaders from 126 countries have to say about the types of data or analysis they use, from what sources, and for which purposes in the context of their work.  We analyze responses to AidData’s 2017 Listening to Leaders (LTL) Survey to offer insights to help funders, producers, advocates, and infomediaries of development data understand how to position themselves for greater impact….(more)”.