AI Global Surveillance Technology

Curated on Posted on by Stefaan Verhulst

Carnegie Endowment: “Artificial intelligence (AI) technology is rapidly proliferating around the world. A growing number of states are deploying advanced AI surveillance tools to monitor, track, and surveil citizens to accomplish a range of policy objectives—some lawful, others that violate human rights, and many of which fall into a murky middle ground.

In order to appropriately address the effects of this technology, it is important to first understand where these tools are being deployed and how they are being used.

To provide greater clarity, Carnegie presents an AI Global Surveillance (AIGS) Index—representing one of the first research efforts of its kind. The index compiles empirical data on AI surveillance use for 176 countries around the world. It does not distinguish between legitimate and unlawful uses of AI surveillance. Rather, the purpose of the research is to show how new surveillance capabilities are transforming the ability of governments to monitor and track individuals or systems. It specifically asks:

  • Which countries are adopting AI surveillance technology?
  • What specific types of AI surveillance are governments deploying?
  • Which countries and companies are supplying this technology?

Learn more about our findings and how AI surveillance technology is spreading rapidly around the globe….(More)”.

Real-time flu tracking. By monitoring social media, scientists can monitor outbreaks as they happen.

Curated on Posted on by Stefaan Verhulst

Charles Schmidt at Nature: “Conventional influenza surveillance describes outbreaks of flu that have already happened. It is based on reports from doctors, and produces data that take weeks to process — often leaving the health authorities to chase the virus around, rather than get on top of it.

But every day, thousands of unwell people pour details of their symptoms and, perhaps unknowingly, locations into search engines and social media, creating a trove of real-time flu data. If such data could be used to monitor flu outbreaks as they happen and to make accurate predictions about its spread, that could transform public-health surveillance.

Powerful computational tools such as machine learning and a growing diversity of data streams — not just search queries and social media, but also cloud-based electronic health records and human mobility patterns inferred from census information — are making it increasingly possible to monitor the spread of flu through the population by following its digital signal. Now, models that track flu in real time and forecast flu trends are making inroads into public-health practice.

“We’re becoming much more comfortable with how these models perform,” says Matthew Biggerstaff, an epidemiologist who works on flu preparedness at the US Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia.

In 2013–14, the CDC launched the FluSight Network, a website informed by digital modelling that predicts the timing, peak and short-term intensity of the flu season in ten regions of the United States and across the whole country. According to Biggerstaff, flu forecasting helps responders to plan ahead, so they can be ready with vaccinations and communication strategies to limit the effects of the virus. Encouraged by progress in the field, the CDC announced in January 2019 that it will spend US$17.5 million to create a network of influenza-forecasting centres of excellence, each tasked with improving the accuracy and communication of real-time forecasts.

The CDC is leading the way on digital flu surveillance, but health agencies elsewhere are following suit. “We’ve been working to develop and apply these models with collaborators using a range of data sources,” says Richard Pebody, a consultant epidemiologist at Public Health England in London. The capacity to predict flu trajectories two to three weeks in advance, Pebody says, “will be very valuable for health-service planning.”…(More)”.

The Art of Values-Based Innovation for Humanitarian Action

Curated on Posted on by Stefaan Verhulst

Chris Earney & Aarathi Krishnan at SSIR: “Contrary to popular belief, innovation isn’t new to the humanitarian sector. Organizations like the Red Cross and Red Crescent have a long history of innovating in communities around the world. Humanitarians have worked both on a global scale—for example, to innovate financing and develop the Humanitarian Code of Conduct—and on a local level—to reduce urban fire risks in informal settlements in Kenya, for instance, and improve waste management to reduce flood risks in Indonesia.

Even in its more-bureaucratic image more than 50 years ago, the United Nations commissioned a report to better understand the role that innovation, science, and technology could play in advancing human rights and development. Titled the “Sussex Manifesto,” the report outlined how to reshape and reorganize the role of innovation and technology so that it was more relevant, equitable, and accessible to the humanitarian and development sectors. Although those who commissioned the manifesto ultimately deemed it too ambitious for its era, the effort nevertheless reflects the UN’s longstanding interest in understanding how far-reaching ideas can elicit fundamental and needed progress. It challenged the humanitarian system to be explicit about its values and understand how those values could lead to radical actions for the betterment of humanity.

Since then, 27 UN organizations have formed teams dedicated to supporting innovation. Today, the aspiration to innovate extends to NGOs and donor communities, and has led to myriad approaches to brainstorming, design thinking, co-creation, and other activities developed to support novelty.

However, in the face of a more-globalized, -connected, and -complex world, we need to, more than ever, position innovation as a bold and courageous way of doing things. It’s common for people to demote innovation as a process that tinkers around the edges of organizations, but we need to think about innovation as a tool for changing the way systems work and our practices so that they better serve communities. This matters, because humanitarian needs are only going to grow, and the resources available to us likely won’t match that need. When the values that underpin our attitudes and behaviors as humanitarians drive innovation, we can better focus our efforts and create more impact with less—and we’re going to have to…(More)”.

Experimental Innovation Policy

Curated on Posted on by Stefaan Verhulst

Paper by Albert Bravo-Biosca: “Experimental approaches are increasingly being adopted across many policy fields, but innovation policy has been lagging. This paper reviews the case for policy experimentation in this field, describes the different types of experiments that can be undertaken, discusses some of the unique challenges to the use of experimental approaches in innovation policy, and summarizes some of the emerging lessons, with a focus on randomized trials. The paper concludes describing how at the Innovation Growth Lab we have been working with governments across the OECD to help them overcome the barriers to policy experimentation in order to make their policies more impactful….(More)”.

The promise and peril of a digital ecosystem for the planet

Curated on Posted on by Stefaan Verhulst

Blog post by Jillian Campbell and David E Jensen: “A range of frontier and digital technologies have dramatically boosted the ways in which we can monitor the health of our planet. And sustain our future on it (Figure 1).

Figure 1. A range of frontier an digital technologies can be combined to monitor our planet and the sustainable use of natural resources (1)

If we can leverage this technology effectively, we will be able to assess and predict risks, increase transparency and accountability in the management of natural resources and inform markets as well as consumer choice. These actions are all required if we are to stand a better chance of achieving the Sustainable Development Goals (SDGs).

However, for this vision to become a reality, public and private sector actors must take deliberate action and collaborate to build a global digital ecosystem for the planet — one consisting of data, infrastructure, rapid analytics, and real-time insights. We are now at a pivotal moment in the history of our stewardship of this planet. A “tipping point” of sorts. And in order to guide the political action which is required to counter the speed, scope and severity of the environmental and climate crises, we must acquire and deploy these data sets and frontier technologies. Doing so can fundamentally change our economic trajectory and underpin a sustainable future.

This article shows how such a global digital ecosystem for the planet can be achieved — as well as what we risk if we do not take decisive action within the next 12 months….(More)”.

Guide to Mobile Data Analytics in Refugee Scenarios

Curated on Posted on by Stefaan Verhulst

Book edited Albert Ali Salah, Alex Pentland, Bruno Lepri and Emmanuel Letouzé: “After the start of the Syrian Civil War in 2011–12, increasing numbers of civilians sought refuge in neighboring countries. By May 2017, Turkey had received over 3 million refugees — the largest r efugee population in the world. Some lived in government-run camps near the Syrian border, but many have moved to cities looking for work and better living conditions. They faced problems of integration, income, welfare, employment, health, education, language, social tension, and discrimination. In order to develop sound policies to solve these interlinked problems, a good understanding of refugee dynamics is necessary.

This book summarizes the most important findings of the Data for Refugees (D4R) Challenge, which was a non-profit project initiated to improve the conditions of the Syrian refugees in Turkey by providing a database for the scientific community to enable research on urgent problems concerning refugees. The database, based on anonymized mobile call detail records (CDRs) of phone calls and SMS messages of one million Turk Telekom customers, indicates the broad activity and mobility patterns of refugees and citizens in Turkey for the year 1 January to 31 December 2017. Over 100 teams from around the globe applied to take part in the challenge, and 61 teams were granted access to the data.

This book describes the challenge, and presents selected and revised project reports on the five major themes: unemployment, health, education, social integration, and safety, respectively. These are complemented by additional invited chapters describing related projects from international governmental organizations, technological infrastructure, as well as ethical aspects. The last chapter includes policy recommendations, based on the lessons learned.

The book will serve as a guideline for creating innovative data-centered collaborations between industry, academia, government, and non-profit humanitarian agencies to deal with complex problems in refugee scenarios. It illustrates the possibilities of big data analytics in coping with refugee crises and humanitarian responses, by showcasing innovative approaches drawing on multiple data sources, information visualization, pattern analysis, and statistical analysis.It will also provide researchers and students working with mobility data with an excellent coverage across data science, economics, sociology, urban computing, education, migration studies, and more….(More)”.

Weaponized Interdependence: How Global Economic Networks Shape State Coercion

Curated on Posted on by Stefaan Verhulst

Henry Farrell and Abraham L. Newman in International Security: “Liberals claim that globalization has led to fragmentation and decentralized networks of power relations. This does not explain how states increasingly “weaponize interdependence” by leveraging global networks of informational and financial exchange for strategic advantage. The theoretical literature on network topography shows how standard models predict that many networks grow asymmetrically so that some nodes are far more connected than others. This model nicely describes several key global economic networks, centering on the United States and a few other states. Highly asymmetric networks allow states with (1) effective jurisdiction over the central economic nodes and (2) appropriate domestic institutions and norms to weaponize these structural advantages for coercive ends. In particular, two mechanisms can be identified. First, states can employ the “panopticon effect” to gather strategically valuable information. Second, they can employ the “chokepoint effect” to deny network access to adversaries. Tests of the plausibility of these arguments across two extended case studies that provide variation both in the extent of U.S. jurisdiction and in the presence of domestic institutions—the SWIFT financial messaging system and the internet—confirm the framework’s expectations. A better understanding of the policy implications of the use and potential overuse of these tools, as well as the response strategies of targeted states, will recast scholarly debates on the relationship between economic globalization and state coercion….(More)”

#Kremlin: Using Hashtags to Analyze Russian Disinformation Strategy and Dissemination on Twitter

Curated on Posted on by Stefaan Verhulst

Paper by Sarah Oates, and John Gray: “Reports of Russian interference in U.S. elections have raised grave concerns about the spread of foreign disinformation on social media sites, but there is little detailed analysis that links traditional political communication theory to social media analytics. As a result, it is difficult for researchers and analysts to gauge the nature or level of the threat that is disseminated via social media. This paper leverages both social science and data science by using traditional content analysis and Twitter analytics to trace how key aspects of Russian strategic narratives were distributed via #skripal, #mh17, #Donetsk, and #russophobia in late 2018.

This work will define how key Russian international communicative goals are expressed through strategic narratives, describe how to find hashtags that reflect those narratives, and analyze user activity around the hashtags. This tests both how Twitter amplifies specific information goals of the Russians as well as the relative success (or failure) of particular hashtags to spread those messages effectively. This research uses Mentionmapp, a system co-developed by one of the authors (Gray) that employs network analytics and machine intelligence to identify the behavior of Twitter users as well as generate profiles of users via posting history and connections. This study demonstrates how political communication theory can be used to frame the study of social media; how to relate knowledge of Russian strategic priorities to labels on social media such as Twitter hashtags; and to test this approach by examining a set of Russian propaganda narratives as they are represented by hashtags. Our research finds that some Twitter users are consistently active across multiple Kremlin-linked hashtags, suggesting that knowledge of these hashtags is an important way to identify Russian propaganda online influencers. More broadly, we suggest that Twitter dichotomies such as bot/human or troll/citizen should be used with caution and analysis should instead address the nuances in Twitter use that reflect varying levels of engagement or even awareness in spreading foreign disinformation online….(More)”.

Is Privacy and Personal Data Set to Become the New Intellectual Property?

Curated on Posted on by Stefaan Verhulst

Paper by Leon Trakman, Robert Walters, and Bruno Zeller: “A pressing concern today is whether the rationale underlying the protection of personal data is itself a meaningful foundation for according intellectual property (IP) rights in personal data to data subjects. In particular, are there particular technological attributes about the collection, use and processing of personal data on the Internet, and global access to that data, that provide a strong justification to extend IP rights to data subjects? A central issue in so determining is whether data subjects need the protection of such rights in a technological revolution in which they are increasingly exposed to the use and abuse of their personal data. A further question is how IP law can provide them with the requisite protection of their private space, or whether other means of protecting personal data, such as through general contract rights, render IP protections redundant, or at least, less necessary. This paper maintains that lawmakers often fail to distinguish between general property and IP protection of personal data; that IP protection encompasses important attributes of both property and contract law; and that laws that implement IP protection in light of its sui generis attributes are more fitting means of protecting personal data than the alternatives. The paper demonstrates that one of the benefits of providing IP rights in personal data goes some way to strengthening data subjects’ control and protection over their personal data and strengthening data protection law more generally. It also argues for greater harmonization of IP law across jurisdictions to ensure that the protection of personal data becomes more coherent and internationally sustainable….(More)”.

Raw data won’t solve our problems — asking the right questions will

Curated on Posted on by Stefaan Verhulst

Stefaan G. Verhulst in apolitical: “If I had only one hour to save the world, I would spend fifty-five minutes defining the questions, and only five minutes finding the answers,” is a famous aphorism attributed to Albert Einstein.

Behind this quote is an important insight about human nature: Too often, we leap to answers without first pausing to examine our questions. We tout solutions without considering whether we are addressing real or relevant challenges or priorities. We advocate fixes for problems, or for aspects of society, that may not be broken at all.

This misordering of priorities is especially acute — and represents a missed opportunity — in our era of big data. Today’s data has enormous potential to solve important public challenges.

However, policymakers often fail to invest in defining the questions that matter, focusing mainly on the supply side of the data equation (“What data do we have or must have access to?”) rather than the demand side (“What is the core question and what data do we really need to answer it?” or “What data can or should we actually use to solve those problems that matter?”).

As such, data initiatives often provide marginal insights while at the same time generating unnecessary privacy risks by accessing and exploring data that may not in fact be needed at all in order to address the root of our most important societal problems.

A new science of questions

So what are the truly vexing questions that deserve attention and investment today? Toward what end should we strategically seek to leverage data and AI?

The truth is that policymakers and other stakeholders currently don’t have a good way of defining questions or identifying priorities, nor a clear framework to help us leverage the potential of data and data science toward the public good.

This is a situation we seek to remedy at The GovLab, an action research center based at New York University.

Our most recent project, the 100 Questions Initiative, seeks to begin developing a new science and practice of questions — one that identifies the most urgent questions in a participatory manner. Launched last month, the goal of this project is to develop a process that takes advantage of distributed and diverse expertise on a range of given topics or domains so as to identify and prioritize those questions that are high impact, novel and feasible.

Because we live in an age of data and much of our work focuses on the promises and perils of data, we seek to identify the 100 most pressing problems confronting the world that could be addressed by greater use of existing, often inaccessible, datasets through data collaboratives – new forms of cross-disciplinary collaboration beyond public-private partnerships focused on leveraging data for good….(More)”.