Data Dissemination in the Digital Age

Curated on Posted on by Stefaan Verhulst

Report by PARIS21 and Open Data Watch: “…a first account of the state of data portals in national statistical offices.

Data portals form a critical link between producers and users of data; and they facilitate the use of data in evidence-based decision making. National statistical offices, supported by their international partners, have embraced data portals as a way to disseminate official data.

However, data portals need to be designed and implemented in a sustainable manner to be beneficial to end users. Currently, there is a lack of common principles and guidelines as to how these data portals should be set up and managed to guide institutions.

This report proposes a holistic method to evaluate data portals and proposes recommendations to improve their use and function…(More)”.

The World Uncertainty Index

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Paper by Hites Ahir, Nicholas Bloom & Davide Furceri: “We construct the World Uncertainty Index (WUI) for an unbalanced panel of 143 individual countries on a quarterly basis from 1952. This is the frequency of the word “uncertainty” in the quarterly Economist Intelligence Unit country reports. Globally, the Index spikes around major events like the Gulf War, the Euro debt crisis, the Brexit vote and the COVID pandemic. The level of uncertainty is higher in developing countries but is more synchronized across advanced economies with their tighter trade and financial linkages. In a panel vector autoregressive setting we find that innovations in the WUI foreshadow significant declines in output. This effect is larger and more persistent in countries with lower institutional quality, and in sectors with greater financial constraints…(More)”.

Advancing Digital Agency: The Power of Data Intermediaries

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World Economic Forum Report: “With the integration of screenless technology into everyday life, the data ecosystem is growing increasingly complicated. New ambient data collection methods bring many benefits, but they also have the potential to amplify mistrust between people and technology.

In this Insight Report, the World Economic Forum’s Taskforce on Data Intermediaries explores the potential to outsource human decision points to an agent acting on an individual’s behalf, in the form of a data intermediary.

The opportunities and risks of such a new approach are explored, representing one of many new policy anchors through and around which individuals may navigate new data ecosystem models. Levers of action for both the public and private sectors are suggested to ensure a future-proof digital policy environment that allows for the seamless and trusted movement of data between people and the technology that serves them…(More)”.

Relational Artificial Intelligence

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Paper by Virginia Dignum: “The impact of Artificial Intelligence does not depend only on fundamental research and technological developments, but for a large part on how these systems are introduced into society and used in everyday situations. Even though AI is traditionally associated with rational decision-making, understanding and shaping the societal impact of AI in all its facets requires a relational perspective. A rational approach to AI, where computational algorithms drive decision-making independent of human intervention, insights and emotions, has shown to result in bias and exclusion, laying bare societal vulnerabilities and insecurities. A relational approach, that focus on the relational nature of things, is needed to deal with the ethical, legal, societal, cultural, and environmental implications of AI. A relational approach to AI recognises that objective and rational reasoning cannot does not always result in the ‘right’ way to proceed because what is ‘right’ depends on the dynamics of the situation in which the decision is taken, and that rather than solving ethical problems the focus of design and use of AI must be on asking the ethical question. In this position paper, I start with a general discussion of current conceptualisations of AI followed by an overview of existing approaches to governance and responsible development and use of AI. Then, I reflect over what should be the bases of a social paradigm for AI and how this should be embedded in relational, feminist and non-Western philosophies, in particular the Ubuntu philosophy….(More)”.

Global Cooperation on Digital Governance and the Geoeconomics of New Technologies in a Multi-polar World

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A special collection of papers by the Centre for International Governance Innovation (CIGI) and King’s College London (KCL) resulting from: “… a virtual conference as part of KCL’s Project for Peaceful Competition. It brought together an intellectually and geographically diverse group of experts to discuss the geoeconomics of new digital technologies and the prospects for governance of the technologies in a multi-polar world. The papers prepared for discussion at the conference are collected in this series. An introduction summarizes (in heavily abbreviated form) the principal analytical conclusions emerging from the conference, together with the main policy recommendations put forward by participants….(More)”.

Technology is revolutionizing how intelligence is gathered and analyzed – and opening a window onto Russian military activity around Ukraine

Curated on Posted on by Stefaan Verhulst

Craig Nazareth at The Conversation: “…Through information captured by commercial companies and individuals, the realities of Russia’s military posturing are accessible to anyone via internet search or news feed. Commercial imaging companies are posting up-to-the-minute, geographically precise images of Russia’s military forces. Several news agencies are regularly monitoring and reporting on the situation. TikTok users are posting video of Russian military equipment on rail cars allegedly on their way to augment forces already in position around Ukraine. And internet sleuths are tracking this flow of information.

This democratization of intelligence collection in most cases is a boon for intelligence professionals. Government analysts are filling the need for intelligence assessments using information sourced from across the internet instead of primarily relying on classified systems or expensive sensors high in the sky or arrayed on the planet.

However, sifting through terabytes of publicly available data for relevant information is difficult. Knowing that much of the data could be intentionally manipulated to deceive complicates the task.

Enter the practice of open-source intelligence. The U.S. director of national intelligence defines Open-Source Intelligence, or OSINT, as the collection, evaluation and analysis of publicly available information. The information sources include news reports, social media posts, YouTube videos and satellite imagery from commercial satellite operators.

OSINT communities and government agencies have developed best practices for OSINT, and there are numerous free tools. Analysts can use the tools to develop network charts of, for example, criminal organizations by scouring publicly available financial records for criminal activity.

Private investigators are using OSINT methods to support law enforcement, corporate and government needs. Armchair sleuths have used OSINT to expose corruption and criminal activity to authorities. In short, the majority of intelligence needs can be met through OSINT…

Even with OSINT best practices and tools, OSINT contributes to the information overload intelligence analysts have to contend with. The intelligence analyst is typically in a reactive mode trying to make sense of a constant stream of ambiguous raw data and information.

Machine learning, a set of techniques that allows computers to identify patterns in large amounts of data, is proving invaluable for processing OSINT information, particularly photos and videos. Computers are much faster at sifting through large datasets, so adopting machine learning tools and techniques to optimize the OSINT process is a necessity.

Identifying patterns makes it possible for computers to evaluate information for deception and credibility and predict future trends. For example, machine learning can be used to help determine whether information was produced by a human or by a bot or other computer program and whether a piece of data is authentic or fraudulent…(More)”.

How privacy’s past may shape its future

Curated on Posted on by Stefaan Verhulst

Essay by Alessandro Acquisti, Laura Brandimarte and Jeff Hancock: “Continued expansion of human activities into digital realms gives rise to concerns about digital privacy and its invasions, often expressed in terms of data rights and internet surveillance. It may thus be tempting to construe privacy as a modern phenomenon—something our ancestors lacked and technological innovation and urban growth made possible. Research from history, anthropology, and ethnography suggests otherwise. The evidence for peoples seeking to manage the boundaries of private and public spans time and space, social class, and degree of technological sophistication. Privacy—not merely hiding of data, but the selective opening and closing of the self to others—appears to be both culturally specific and culturally universal. But what could explain the simultaneous universality and diversity of a human drive for privacy? An account of the evolutionary roots of privacy may offer an answer and teach us about privacy’s digital future and how to manage it….(More)”.

A Taxonomy for AI / Data for Good

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Paper by Jake Porway: “There is huge potential for AI and data science to play a productive role in advancing social impact. However, the field of “AI for good” and  “data for good” is not only overshadowed by the public conversations about the risks rampant data misuse can pose to civil society, it is also a fractured and disconnected space without a single shared vision. One of the biggest issues preventing AI for Good from becoming an established field is a lack of clarity. “Data” and “AI” are treated like they’re well-defined terms, but they are stand-ins for a huge set of different – and sometimes competing – outcomes, outputs, and activities. The terms “AI for Good” and “Data for Good” is as unhelpful as saying “Wood for Good”. We would laugh at a term as vague as “Wood for Good”, which would lump together activities as different as building houses to burning wood in cook stoves to making paper, combining architecture with carpentry, forestry with fuel. However, we are content to say “AI for Good”, and its related phrases “we need to use our data better” or “we need to be data-driven”, when data is arguably even more general than something like wood. 

One way to cut through this fog is to be far more clear about what a given AI-for-good initiative seeks to achieve, and by what means. To that end, we’ve created a taxonomy, a family tree of AI-and-Data-for-Good initiatives, that groups initiatives based on their goals and strategies. This taxonomy came about as a result of studying and classifying over 600 initiatives labeled as “AI for good” or “data for good” publicly (you can read more about the methodology here). At the highest level, the taxonomy identifies six major branches of AI and data for good activities, which will help field builders, funders, and nonprofits better understand the distinctions in this space. Within each branch, you’ll see sub-branches that further subdivide initiatives, which we hope will aid collaboration for the groups within those branches and help funders make more strategic funding decisions.

Below you’ll find a landscape map of a subset of initiatives in the AI and Data for Good space, categorized into those six main branches we observed. Before we dive into describing each branch, here are a few caveats on how to interpret this work: 

  • We are focused on initiatives that are enabling and advancing the field of Data for Good, not trying to catalog every data science project every nonprofit or company is doing (though that would be an interesting landscape to see as well). These initiatives are those focused on advancing the field of using data and AI for good.
  • We chose to categorize initiatives, not organizations. It would be impossible to classify “Microsoft”, when their activities span funding through Microsoft Philanthropies, creating open satellite imagery through Microsoft AI for Earth, providing infrastructure through nonprofit licenses of Microsoft Azure, and so on. Therefore you may see organizations appear multiple times across the landscape.
  • The current database of organizations is minuscule – it is nowhere near exhaustive. We have only mapped enough initiatives to show the results for feedback, but we encourage you to recommend other initiatives you know of but don’t see here with this form.
  • While we are incredibly privileged to have advisors contributing to this project from countries like Brazil, Nigeria, and Nepal, the initiative still skew Western…(More)”.

Direct democracy and equality: a global perspective

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Paper by Anna Krämling et al: “Direct democracy is seen as a potential cure to the malaise of representative democracy. It is increasingly used worldwide. However, research on the effects of direct democracy on important indicators like socio-economic, legal, and political equality is scarce, and mainly limited to Europe and the US. The global perspective is missing. This article starts to close this gap. It presents descriptive findings on direct democratic votes at the national level in the (partly) free countries of the Global South and Oceania between 1990 and 2015. It performs the first comparative analysis of direct democracy on these continents. Contradicting concerns that direct democracy may be a threat to equality, we found more bills aimed at increasing equality. Likewise, these votes produced more pro- than contra-equality outputs. This held for all continents as well as for all dimensions of equality….(More)”.

Free Speech: A History from Socrates to Social Media

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Book by Jacob Mchangama: A global history of free speech, from the ancient world to today. Hailed as the “first freedom,” free speech is the bedrock of democracy. But it is a challenging principle, subject to erosion in times of upheaval. Today, in democracies and authoritarian states around the world, it is on the retreat.

In Free Speech, Jacob Mchangama traces the riveting legal, political, and cultural history of this idea. Through captivating stories of free speech’s many defenders—from the ancient Athenian orator Demosthenes and the ninth-century freethinker al-Rāzī, to the anti-lynching crusader Ida B. Wells and modern-day digital activists—Mchangama reveals how the free exchange of ideas underlies all intellectual achievement and has enabled the advancement of both freedom and equality worldwide. Yet the desire to restrict speech, too, is a constant, and he explores how even its champions can be led down this path when the rise of new and contrarian voices challenge power and privilege of all stripes.

Meticulously researched and deeply humane, Free Speech demonstrates how much we have gained from this principle—and how much we stand to lose without it…(More)”.