Cyberdiplomacy: Managing Security and Governance Online

Curated on Posted on by Stefaan Verhulst

Book by Shaun Riordan: “The world has been sleep-walking into cyber chaos. The spread of misinformation via social media and the theft of data and intellectual property, along with regular cyberattacks, threaten the fabric of modern societies. All the while, the Internet of Things increases the vulnerability of computer systems, including those controlling critical infrastructure. What can be done to tackle these problems? Does diplomacy offer ways of managing security and containing conflict online?

In this provocative book, Shaun Riordan shows how traditional diplomatic skills and mindsets can be combined with new technologies to bring order and enhance international cooperation. He explains what cyberdiplomacy means for diplomats, foreign services and corporations and explores how it can be applied to issues such as internet governance, cybersecurity, cybercrime and information warfare. Cyberspace, he argues, is too important to leave to technicians. Using the vital tools offered by cyberdiplomacy, we can reduce the escalation and proliferation of cyberconflicts by proactively promoting negotiation and collaboration online….(More)”.

Illuminating Big Data will leave governments in the dark

Curated on Posted on by Stefaan Verhulst

Robin Wigglesworth in the Financial Times: “Imagine a world where interminable waits for backward-looking, frequently-revised economic data seem as archaically quaint as floppy disks, beepers and a civil internet. This fantasy realm may be closer than you think.

The Bureau of Economic Analysis will soon publish its preliminary estimate for US economic growth in the first three months of the year, finally catching up on its regular schedule after a government shutdown paralysed the agency. But other data are still delayed, and the final official result for US gross domestic product won’t be available until July. Along the way there are likely to be many tweaks.

Collecting timely and accurate data are a Herculean task, especially for an economy as vast and varied as the US’s. But last week’s World Bank-International Monetary Fund’s annual spring meetings offered some clues on a brighter, more digital future for economic data.

The IMF hosted a series of seminars and discussions exploring how the hot new world of Big Data could be harnessed to produce more timely economic figures — and improve economic forecasts. Jiaxiong Yao, an IMF official in its African department, explained how it could use satellites to measure the intensity of night-time lights, and derive a real-time gauge of economic health.

“If a country gets brighter over time, it is growing. If it is getting darker then it probably needs an IMF programme,” he noted. Further sessions explored how the IMF could use machine learning — a popular field of artificial intelligence — to improve its influential but often faulty economic forecasts; and real-time shipping data to map global trade flows.

Sophisticated hedge funds have been mining some of these new “alternative” data sets for some time, but statistical agencies, central banks and multinational organisations such as the IMF and the World Bank are also starting to embrace the potential.

The amount of digital data around the world is already unimaginably vast. As more of our social and economic activity migrates online, the quantity and quality is going to increase exponentially. The potential is mind-boggling. Setting aside the obvious and thorny privacy issues, it is likely to lead to a revolution in the world of economic statistics. …

Yet the biggest issues are not the weaknesses of these new data sets — all statistics have inherent flaws — but their nature and location.

Firstly, it depends on the lax regulatory and personal attitudes towards personal data continuing, and there are signs of a (healthy) backlash brewing.

Secondly, almost all of this alternative data is being generated and stored in the private sector, not by government bodies such as the Bureau of Economic Analysis, Eurostat or the UK’s Office for National Statistics.

Public bodies are generally too poorly funded to buy or clean all this data themselves, meaning hedge funds will benefit from better economic data than the broader public. We might, in fact, need legislation mandating that statistical agencies receive free access to any aggregated private sector data sets that might be useful to their work.

That would ensure that our economic officials and policymakers don’t fly blind in an increasingly illuminated world….(More)”.

Digital Data for Development

Curated on Posted on by Stefaan Verhulst

LinkedIn: “The World Bank Group and LinkedIn share a commitment to helping workers around the world access opportunities that make good use of their talents and skills. The two organizations have come together to identify new ways that data from LinkedIn can help inform policymakers who seek to boost employment and grow their economies.

This site offers data and automated visuals of industries where LinkedIn data is comprehensive enough to provide an emerging picture. The data complements a wealth of official sources and can offer a more real-time view in some areas particularly for new, rapidly changing digital and technology industries.

The data shared in the first phase of this collaboration focuses on 100+ countries with at least 100,000 LinkedIn members each, distributed across 148 industries and 50,000 skills categories. In the near term, it will help World Bank Group teams and government partners pinpoint ways that developing countries could stimulate growth and expand opportunity, especially as disruptive technologies reshape the economic landscape. As LinkedIn’s membership and digital platforms continue to grow in developing countries, this collaboration will assess the possibility to expand the sectors and countries covered in the next annual update.

This site offers downloadable data, visualizations, and an expanding body of insights and joint research from the World Bank Group and LinkedIn. The data is being made accessible as a public good, though it will be most useful for policy analysts, economists, and researchers….(More)”.

Building Trust in Human Centric Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions: “Artificial intelligence (AI) has the potential to transform our world for the better: it can improve healthcare, reduce energy consumption, make cars safer, and enable farmers to use water and natural resources more efficiently. AI can be used to predict environmental and climate change, improve financial risk management and provides the tools to manufacture, with less waste, products tailored to our needs. AI can also help to detect fraud and cybersecurity threats, and enables law enforcement agencies to fight crime more efficiently.

AI can benefit the whole of society and the economy. It is a strategic technology that is now being developed and used at a rapid pace across the world. Nevertheless, AI also brings with it new challenges for the future of work, and raises legal and ethical questions.

To address these challenges and make the most of the opportunities which AI offers, the Commission published a European strategy in April 2018. The strategy places people at the centre of the development of AI — human-centric AI. It is a three-pronged approach to boost the EU’s technological and industrial capacity and AI uptake across the economy, prepare for socio-economic changes, and ensure an appropriate ethical and legal framework.

To deliver on the AI strategy, the Commission developed together with Member States a coordinated plan on AI, which it presented in December 2018, to create synergies, pool data — the raw material for many AI applications — and increase joint investments. The aim is to foster cross-border cooperation and mobilise all players to increase public and private investments to at least EUR 20 billion annually over the next decade.

The Commission doubled its investments in AI in Horizon 2020 and plans to invest EUR 1 billion annually from Horizon Europe and the Digital Europe Programme, in support notably of common data spaces in health, transport and manufacturing, and large experimentation facilities such as smart hospitals and infrastructures for automated vehicles and a strategic research agenda.

To implement such a common strategic research, innovation and deployment agenda the Commission has intensified its dialogue with all relevant stakeholders from industry, research institutes and public authorities. The new Digital Europe programme will also be crucial in helping to make AI available to small and medium-size enterprises across all Member States through digital innovation hubs, strengthened testing and experimentation facilities, data spaces and training programmes.

Building on its reputation for safe and high-quality products, Europe’s ethical approach to AI strengthens citizens’ trust in the digital development and aims at building a competitive advantage for European AI companies. The purpose of this Communication is to launch a comprehensive piloting phase involving stakeholders on the widest scale in order to test the practical implementation of ethical guidance for AI development and use…(More)”.

Unblocking the Bottlenecks and Making the Global Supply Chain Transparent: How Blockchain Technology Can Update Global Trade

Curated on Posted on by Stefaan Verhulst

Paper by Hanna C Norberg: “Blockchain technology is still in its infancy, but already it has begun to revolutionize global trade. Its lure is irresistible because of the simplicity with which it can replace the standard methods of documentation, smooth out logistics, increase transparency, speed up transactions, and ameliorate the planning and tracking of trade.

Blockchain essentially provides the supply chain with an unalterable ledger of verified transactions, and thus enables trust every step of the way through the trade process. Every stakeholder involved in that process – from producer to warehouse worker to shipper to financial institution to recipient at the final destination – can trust that the information contained in that indelible ledger is accurate. Fraud will no longer be an issue, middlemen can be eliminated, shipments tracked, quality control maintained to highest standards and consumers can make decisions based on more than the price. Blockchain dramatically reduces the amount of paperwork involved, along with the myriad of agents typically involved in the process, all of this resulting in soaring efficiencies. Making the most of this new technology, however, requires solid policy. Most people have only a vague idea of what blockchain is. There needs to be a basic understanding of what blockchain can and can’t do, and how it works in the economy and in trade. Once they become familiar with the technology, policy-makers must move on to thinking about what technological issues could be mitigated, solved or improved.

Governments need to explore blockchain’s potential through its use in public-sector projects that demonstrate its workings, its potential and its inevitable limitations. Although blockchain is not nearly as evolved now as the internet was in 2005, co-operation among all stakeholders on issues like taxonomy or policy guides on basic principles is crucial. Those stakeholders include government, industry, academia and civil society. All this must be done while keeping in mind the global nature of blockchain and that blockchain regulations need to be made in synch with regulations on other issues are adjacent to the technology, such as electronic signatures. However, work can be done in the global arena through international initiatives and organizations such as the ISO….(More)”.

Facebook’s AI team maps the whole population of Africa

Curated on Posted on by Stefaan Verhulst

Devin Coldewey at TechCrunch: “A new map of nearly all of Africa shows exactly where the continent’s 1.3 billion people live, down to the meter, which could help everyone from local governments to aid organizations. The map joins others like it from Facebook  created by running satellite imagery through a machine learning model.

It’s not exactly that there was some mystery about where people live, but the degree of precision matters. You may know that a million people live in a given region, and that about half are in the bigger city and another quarter in assorted towns. But that leaves hundreds of thousands only accounted for in the vaguest way.

Fortunately, you can always inspect satellite imagery and pick out the spots where small villages and isolated houses and communities are located. The only problem is that Africa is big. Really big. Manually labeling the satellite imagery even from a single mid-sized country like Gabon or Malawi would take a huge amount of time and effort. And for many applications of the data, such as coordinating the response to a natural disaster or distributing vaccinations, time lost is lives lost.

Better to get it all done at once then, right? That’s the idea behind Facebook’s Population Density Maps project, which had already mapped several countries over the last couple of years before the decision was made to take on the entire African continent….

“The maps from Facebook ensure we focus our volunteers’ time and resources on the places they’re most needed, improving the efficacy of our programs,” said Tyler Radford, executive director of the Humanitarian OpenStreetMap Team, one of the project’s partners.

The core idea is straightforward: Match census data (how many people live in a region) with structure data derived from satellite imagery to get a much better idea of where those people are located.

“With just the census data, the best you can do is assume that people live everywhere in the district – buildings, fields, and forests alike,” said Facebook engineer James Gill. “But once you know the building locations, you can skip the fields and forests and only allocate the population to the buildings. This gives you very detailed 30 meter by 30 meter population maps.”

That’s several times more accurate than any extant population map of this size. The analysis is done by a machine learning agent trained on OpenStreetMap data from all over the world, where people have labeled and outlined buildings and other features.

First the huge amount of Africa’s surface that obviously has no structure had to be removed from consideration, reducing the amount of space the team had to evaluate by a factor of a thousand or more. Then, using a region-specific algorithm (because things look a lot different in coastal Morocco than they do in central Chad), the model identifies patches that contain a building….(More)”.

Innovation Meets Citizen Science

Curated on Posted on by Stefaan Verhulst

Caroline Nickerson at SciStarter: “Citizen science has been around as long as science, but innovative approaches are opening doors to more and deeper forms of public participation.

Below, our editors spotlight a few projects that feature new approaches, novel research, or low-cost instruments. …

Colony B: Unravel the secrets of microscopic life! Colony B is a mobile gaming app developed at McGill University that enables you to contribute to research on microbes. Collect microbes and grow your colony in a fast-paced puzzle game that advances important scientific research.

AirCasting: AirCasting is an open-source, end-to-end solution for collecting, displaying, and sharing health and environmental data using your smartphone. The platform consists of wearable sensors, including a palm-sized air quality monitor called the AirBeam, that detect and report changes in your environment. (Android only.)

LingoBoingo: Getting computers to understand language requires large amounts of linguistic data and “correct” answers to language tasks (what researchers call “gold standard annotations”). Simply by playing language games online, you can help archive languages and create the linguistic data used by researchers to improve language technologies. These games are in English, French, and a new “multi-lingual” category.

TreeSnap: Help our nation’s trees and protect human health in the process. Invasive diseases and pests threaten the health of America’s forests. With the TreeSnap app, you can record the location and health of particular tree species–those unharmed by diseases that have wiped out other species. Scientists then use the collected information to locate candidates for genetic sequencing and breeding programs. Tag trees you find in your community, on your property, or out in the wild to help scientists understand forest health….(More)”.

Ethics guidelines for trustworthy AI

Curated on Posted on by Stefaan Verhulst

European Commission: “Following the publication of the draft ethics guidelines in December 2018 to which more than 500 comments were received, the independent expert group presents today their ethics guidelines for trustworthy artificial intelligence.

Trustworthy AI should respect all applicable laws and regulations, as well as a series of requirements; specific assessment lists aim to help verify the application of each of the key requirements:

  • Human agency and oversight: AI systems should enable equitable societies by supporting human agency and fundamental rights, and not decrease, limit or misguide human autonomy.
  • Robustness and safety: Trustworthy AI requires algorithms to be secure, reliable and robust enough to deal with errors or inconsistencies during all life cycle phases of AI systems.
  • Privacy and data governance: Citizens should have full control over their own data, while data concerning them will not be used to harm or discriminate against them.
  • Transparency: The traceability of AI systems should be ensured.
  • Diversity, non-discrimination and fairness: AI systems should consider the whole range of human abilities, skills and requirements, and ensure accessibility.
  • Societal and environmental well-being: AI systems should be used to enhance positive social change and enhance sustainability and ecological responsibility.
  • Accountability: Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes.

In summer 2019, the Commission will launch a pilot phase involving a wide range of stakeholders. Already today, companies, public administrations and organisations can sign up to the European AI Alliance and receive a notification when the pilot starts.

Following the pilot phase, in early 2020, the AI expert group will review the assessment lists for the key requirements, building on the feedback received. Building on this review, the Commission will evaluate the outcome and propose any next steps….(More)”.

Platform Surveillance

Curated on Posted on by Stefaan Verhulst

Editorial by David Murakami Wood and Torin Monahan of Special Issue of Surveillance and Society: “This editorial introduces this special responsive issue on “platform surveillance.” We develop the term platform surveillance to account for the manifold and often insidious ways that digital platforms fundamentally transform social practices and relations, recasting them as surveillant exchanges whose coordination must be technologically mediated and therefore made exploitable as data. In the process, digital platforms become dominant social structures in their own right, subordinating other institutions, conjuring or sedimenting social divisions and inequalities, and setting the terms upon which individuals, organizations, and governments interact.

Emergent forms of platform capitalism portend new governmentalities, as they gradually draw existing institutions into alignment or harmonization with the logics of platform surveillance while also engendering subjectivities (e.g., the gig-economy worker) that support those logics. Because surveillance is essential to the operations of digital platforms, because it structures the forms of governance and capital that emerge, the field of surveillance studies is uniquely positioned to investigate and theorize these phenomena….(More)”.

Responsible Data Governance of Neuroscience Big Data

Curated on Posted on by Stefaan Verhulst

Paper by B. Tyr Fothergill et al: “Current discussions of the ethical aspects of big data are shaped by concerns regarding the social consequences of both the widespread adoption of machine learning and the ways in which biases in data can be replicated and perpetuated. We instead focus here on the ethical issues arising from the use of big data in international neuroscience collaborations.

Neuroscience innovation relies upon neuroinformatics, large-scale data collection and analysis enabled by novel and emergent technologies. Each step of this work involves aspects of ethics, ranging from concerns for adherence to informed consent or animal protection principles and issues of data re-use at the stage of data collection, to data protection and privacy during data processing and analysis, and issues of attribution and intellectual property at the data-sharing and publication stages.

Significant dilemmas and challenges with far-reaching implications are also inherent, including reconciling the ethical imperative for openness and validation with data protection compliance, and considering future innovation trajectories or the potential for misuse of research results. Furthermore, these issues are subject to local interpretations within different ethical cultures applying diverse legal systems emphasising different aspects. Neuroscience big data require a concerted approach to research across boundaries, wherein ethical aspects are integrated within a transparent, dialogical data governance process. We address this by developing the concept of ‘responsible data governance’, applying the principles of Responsible Research and Innovation (RRI) to the challenges presented by governance of neuroscience big data in the Human Brain Project (HBP)….(More)”.