Build digital democracy

Curated on Posted on by Stefaan Verhulst

Dirk Helbing & Evangelos Pournaras in Nature: “Fridges, coffee machines, toothbrushes, phones and smart devices are all now equipped with communicating sensors. In ten years, 150 billion ‘things’ will connect with each other and with billions of people. The ‘Internet of Things’ will generate data volumes that double every 12 hours rather than every 12 months, as is the case now.

Blinded by information, we need ‘digital sunglasses’. Whoever builds the filters to monetize this information determines what we see — Google and Facebook, for example. Many choices that people consider their own are already determined by algorithms. Such remote control weakens responsible, self-determined decision-making and thus society too.

The European Court of Justice’s ruling on 6 October that countries and companies must comply with European data-protection laws when transferring data outside the European Union demonstrates that a new digital paradigm is overdue. To ensure that no government, company or person with sole control of digital filters can manipulate our decisions, we need information systems that are transparent, trustworthy and user-controlled. Each of us must be able to choose, modify and build our own tools for winnowing information.

With this in mind, our research team at the Swiss Federal Institute of Technology in Zurich (ETH Zurich), alongside international partners, has started to create a distributed, privacy-preserving ‘digital nervous system’ called Nervousnet. Nervousnet uses the sensor networks that make up the Internet of Things, including those in smartphones, to measure the world around us and to build a collective ‘data commons’. The many challenges ahead will be best solved using an open, participatory platform, an approach that has proved successful for projects such as Wikipedia and the open-source operating system Linux.

A wise king?

The science of human decision-making is far from understood. Yet our habits, routines and social interactions are surprisingly predictable. Our behaviour is increasingly steered by personalized advertisements and search results, recommendation systems and emotion-tracking technologies. Thousands of pieces of metadata have been collected about every one of us (seego.nature.com/stoqsu). Companies and governments can increasingly manipulate our decisions, behaviour and feelings1.

Many policymakers believe that personal data may be used to ‘nudge’ people to make healthier and environmentally friendly decisions. Yet the same technology may also promote nationalism, fuel hate against minorities or skew election outcomes2 if ethical scrutiny, transparency and democratic control are lacking — as they are in most private companies and institutions that use ‘big data’. The combination of nudging with big data about everyone’s behaviour, feelings and interests (‘big nudging’, if you will) could eventually create close to totalitarian power.

Countries have long experimented with using data to run their societies. In the 1970s, Chilean President Salvador Allende created computer networks to optimize industrial productivity3. Today, Singapore considers itself a data-driven ‘social laboratory’4 and other countries seem keen to copy this model.

The Chinese government has begun rating the behaviour of its citizens5. Loans, jobs and travel visas will depend on an individual’s ‘citizen score’, their web history and political opinion. Meanwhile, Baidu — the Chinese equivalent of Google — is joining forces with the military for the ‘China brain project’, using ‘deep learning’ artificial-intelligence algorithms to predict the behaviour of people on the basis of their Internet activity6.

The intentions may be good: it is hoped that big data can improve governance by overcoming irrationality and partisan interests. But the situation also evokes the warning of the eighteenth-century philosopher Immanuel Kant, that the “sovereign acting … to make the people happy according to his notions … becomes a despot”. It is for this reason that the US Declaration of Independence emphasizes the pursuit of happiness of individuals.

Ruling like a ‘benevolent dictator’ or ‘wise king’ cannot work because there is no way to determine a single metric or goal that a leader should maximize. Should it be gross domestic product per capita or sustainability, power or peace, average life span or happiness, or something else?

Better is pluralism. It hedges risks, promotes innovation, collective intelligence and well-being. Approaching complex problems from varied perspectives also helps people to cope with rare and extreme events that are costly for society — such as natural disasters, blackouts or financial meltdowns.

Centralized, top-down control of data has various flaws. First, it will inevitably become corrupted or hacked by extremists or criminals. Second, owing to limitations in data-transmission rates and processing power, top-down solutions often fail to address local needs. Third, manipulating the search for information and intervening in individual choices undermines ‘collective intelligence’7. Fourth, personalized information creates ‘filter bubbles’8. People are exposed less to other opinions, which can increase polarization and conflict9.

Fifth, reducing pluralism is as bad as losing biodiversity, because our economies and societies are like ecosystems with millions of interdependencies. Historically, a reduction in diversity has often led to political instability, collapse or war. Finally, by altering the cultural cues that guide peoples’ decisions, everyday decision-making is disrupted, which undermines rather than bolsters social stability and order.

Big data should be used to solve the world’s problems, not for illegitimate manipulation. But the assumption that ‘more data equals more knowledge, power and success’ does not hold. Although we have never had so much information, we face ever more global threats, including climate change, unstable peace and socio-economic fragility, and political satisfaction is low worldwide. About 50% of today’s jobs will be lost in the next two decades as computers and robots take over tasks. But will we see the macroeconomic benefits that would justify such large-scale ‘creative destruction’? And how can we reinvent half of our economy?

The digital revolution will mainly benefit countries that achieve a ‘win–win–win’ situation for business, politics and citizens alike10. To mobilize the ideas, skills and resources of all, we must build information systems capable of bringing diverse knowledge and ideas together. Online deliberation platforms and reconfigurable networks of smart human minds and artificially intelligent systems can now be used to produce collective intelligence that can cope with the diverse and complex challenges surrounding us….(More)” See Nervousnet project

Introducing Government as a Platform

Curated on Posted on by Stefaan Verhulst

Peter Williams, Jan Gravesen and Trinette Brownhill in Government Executive: “Governments around the world are facing competitive pressures and expectations from their constituents that are prompting them to innovate and dissolve age-old structures. Many governments have introduced a digital strategy in which at least one of the goals is aimed at bringing their organizations closer to citizens and businesses.

To achieve this, ideally IT and data in government would not be constrained by the different functional towers that make up the organization, as is often the case. They would not be constrained by complex, monolithic application design philosophies and lengthy implementation cycles, nor would development be constrained by the assumption that all activity has to be executed by the government itself.

Instead, applications would be created rapidly and cheaply, and modules would be shared as reusable blocks of code and integrated data. It would be relatively straightforward to integrate data from multiple departments to enable a focus on the complex needs of, say, a single parent who is diabetic and a student. Delivery would be facilitated in the manner best required, or preferred, by the citizen. Third parties would also be able to access these modules of code and data to build higher value government services that multiple agencies would then buy into. The code would run on a cloud infrastructure that maximizes the efficiency in which processing resources are used.

GaaP an organized set of ideas and principles that allows organizations to approach these ideals. It allows governments to institute more efficient sharing of IT resources as well as unlock data and functionality via application programming interfaces to allow third parties to build higher value citizen services. In doing so, security plays a crucial role protecting the privacy of constituents and enterprise assets.

We see increasingly well-established examples of GaaP services in many parts of the world. The notion has significantly influenced strategic thinking in the UK, Australia, Denmark, Canada and Singapore. In particular, it has evolved in a deliberate way in the UK’s Government Data Services, building on the Blairite notion of “joined up government”; in Australia’s e-government strategy and its myGov program; and as a significant influencer in Singapore’s entire approach to building its “smarter nation” infrastructure.

Collaborative Government

GaaP assumes a transformational shift in efficiency, effectiveness and transparency, in which agencies move toward a collaborative government and away from today’s siloed approach. That collaboration may be among agencies, but also with other entities (nongovernmental organizations, the private sector, citizens, etc.).

GaaP’s focus on collaboration enables public agencies to move away from their traditional towered approach to IT and increasingly make use of shared and composable services offered by a common – usually a virtualized, cloud-enabled – platform. This leads to more efficient use of development resources, platforms and IT support. We are seeing examples of this already with a group of townships in New York state and also with two large Spanish cities that are embarking on this approach.

While efficient resource and service sharing is central to the idea of GaaP, it is not sufficient. The idea is that GaaP must allow app developers, irrespective of whether they are citizens, private organizations or other public agencies, to develop new value-added services using published government data and APIs. In this sense, the platform becomes a connecting layer between public agencies’ systems and data on the one hand, and private citizens, organizations and other public agencies on the other.

In its most fundamental form, GaaP is able to:

  • Consume data and government services from existing departmental systems.
  • Consume syndicated services from platform-as-a-service or software-as-a-service providers in the public marketplace.
  • Securely unlock these data and services and allow third parties –citizens, private organizations or other agencies – to combine services and data into higher-order services or more citizen-centric or business-centric services.

It is the openness, the secure interoperability, and the ability to compose new services on the basis of existing services and data that define the nature of the platform.

The Challenges

At one time, the challenge of creating a GaaP structure would have been technology: Today, it is governance….(More)”

How the USGS uses Twitter data to track earthquakes

Curated on Posted on by Stefaan Verhulst

Twitter Blog: “After the disastrous Sichuan earthquake in 2008, people turned to Twitter to share firsthand information about the earthquake. What amazed many was the impression that Twitter was faster at reporting the earthquake than the U.S. Geological Survey (USGS), the official government organization in charge of tracking such events.

This Twitter activity wasn’t a big surprise to the USGS. The USGS National Earthquake Information Center (NEIC) processes about 2,000 realtime earthquake sensors, with the majority based in the United States. That leaves a lot of empty space in the world with no sensors. On the other hand, there are hundreds of millions of people using Twitter who can report earthquakes. At first, the USGS staff was a bit skeptical that Twitter could be used as a detection system for earthquakes – but when they looked into it, they were surprised at the effectiveness of Twitter data for detection.

USGS staffers Paul Earle, a seismologist, and Michelle Guy, a software developer, teamed up to look at how Twitter data could be used for earthquake detection and verification. By using Twitter’s Public API, they decided to use the same time series event detection method they use when detecting earthquakes. This gave them a baseline for earthquake-related chatter, but they decided to dig in even further. They found that people Tweeting about actual earthquakes kept their Tweets really short, even just to ask, “earthquake?” Concluding that people who are experiencing earthquakes aren’t very chatty, they started filtering out Tweets with more than seven words. They also recognized that people sharing links or the size of the earthquake were significantly less likely to be offering firsthand reports, so they filtered out any Tweets sharing a link or a number. Ultimately, this filtered stream proved to be very significant at determining when earthquakes occurred globally.

USGS Modeling Twitter Data to Detect Earthquakes

While I was at the USGS office in Golden, Colo. interviewing Michelle and Paul, three earthquakes happened in a relatively short time. Using Twitter data, their system was able to pick up on an aftershock in Chile within one minute and 20 seconds – and it only took 14 Tweets from the filtered stream to trigger an email alert. The other two earthquakes, off Easter Island and Indonesia, weren’t picked up because they were not widely felt…..

The USGS monitors for earthquakes in many languages, and the words used can be a clue as to the magnitude and location of the earthquake. Chile has two words for earthquakes: terremotoand temblor; terremoto is used to indicate a bigger quake. This one in Chile started with people asking if it was a terremoto, but others realizing that it was a temblor.

As the USGS team notes, Twitter data augments their own detection work on felt earthquakes. If they’re getting reports of an earthquake in a populated area but no Tweets from there, that’s a good indicator to them that it’s a false alarm. It’s also very cost effective for the USGS, because they use Twitter’s Public API and open-source software such as Kibana and ElasticSearch to help determine when earthquakes occur….(More)”

Personalising data for development

Curated on Posted on by Stefaan Verhulst

Wolfgang Fengler and Homi Kharas in the Financial Times: “When world leaders meet this week for the UN’s general assembly to adopt the Sustainable Development Goals (SDGs), they will also call for a “data revolution”. In a world where almost everyone will soon have access to a mobile phone, where satellites will take high-definition pictures of the whole planet every three days, and where inputs from sensors and social media make up two thirds of the world’s new data, the opportunities to leverage this power for poverty reduction and sustainable development are enormous. We are also on the verge of major improvements in government administrative data and data gleaned from the activities of private companies and citizens, in big and small data sets.

But these opportunities are yet to materialize in any scale. In fact, despite the exponential growth in connectivity and the emergence of big data, policy making is rarely based on good data. Almost every report from development institutions starts with a disclaimer highlighting “severe data limitations”. Like castaways on an island, surrounded with water they cannot drink unless the salt is removed, today’s policy makers are in a sea of data that need to be refined and treated (simplified and aggregated) to make them “consumable”.

To make sense of big data, we used to depend on data scientists, computer engineers and mathematicians who would process requests one by one. But today, new programs and analytical solutions are putting big data at anyone’s fingertips. Tomorrow, it won’t be technical experts driving the data revolution but anyone operating a smartphone. Big data will become personal. We will be able to monitor and model social and economic developments faster, more reliably, more cheaply and on a far more granular scale. The data revolution will affect both the harvesting of data through new collection methods, and the processing of data through new aggregation and communication tools.

In practice, this means that data will become more actionable by becoming more personal, more timely and more understandable. Today, producing a poverty assessment and poverty map takes at least a year: it involves hundreds of enumerators, lengthy interviews and laborious data entry. In the future, thanks to hand-held connected devices, data collection and aggregation will happen in just a few weeks. Many more instances come to mind where new and higher-frequency data could generate development breakthroughs: monitoring teacher attendance, stocks and quality of pharmaceuticals, or environmental damage, for example…..

Despite vast opportunities, there are very few examples that have generated sufficient traction and scale to change policy and behaviour and create the feedback loops to further improve data quality. Two tools have personalised the abstract subjects of environmental degradation and demography (see table):

  • Monitoring forest fires. The World Resources Institute has launched Global Forest Watch, which enables users to monitor forest fires in near real time, and overlay relevant spatial information such as property boundaries and ownership data to be developed into a model to anticipate the impact on air quality in affected areas in Indonesia, Singapore and Malaysia.
  • Predicting your own life expectancy. The World Population Program developed a predictive tool – www.population.io – showing each person’s place in the distribution of world population and corresponding statistical life expectancy. In just a few months, this prototype attracted some 2m users who shared their results more than 25,000 times on social media. The traction of the tool resulted from making demography personal and converting an abstract subject matter into a question of individual ranking and life expectancy.

A new Global Partnership for Sustainable Development Data will be launched at the time of the UN General Assembly….(More)”

Give me location data, and I shall move the world

Curated on Posted on by Stefaan Verhulst

Marta Poblet at the Conversation: “Behind the success of the new wave of location based mobile apps taking hold around the world is digital mapping. Location data is core to popular ride-sharing services such as Uber and Lyft, but also to companies such as Amazon or Domino’s Pizza, which are testing drones for faster deliveries.

Last year, German delivery firm DHL launched its first “parcelcopter” to send medication to the island of Juist in the Northern Sea. In the humanitarian domain, drones are also being tested for disaster relief operations.

Better maps can help app-led companies gain a competitive edge, but it’s hard to produce them at a global scale. …

A flagship base map for the past ten years has been OpenStreetMap (OSM), also known as the “Wikipedia of mapping”. With more than two million registered users, OpenStreetMap aims to create a free map of the world. OSM volunteers have been particularly active in mapping disaster-affected areas such as Haiti, the Philippines or Nepal. A recent study reports how humanitarian response has been a driver of OSM’s evolution, “in part because open data and participatory ideals align with humanitarian work, but also because disasters are catalysts for organizational innovation”….

Intense competition for digital maps also flags the start of the self-driving car race. Google is already testing its prototypes outside Silicon Valley and Apple has been rumoured to work on a secret car project code named Titan.

Uber has partnered with Carnegie Mellon and Arizona Universities to work on vehicle safety and cheaper laser mapping systems. Tesla is also planning to make its electric cars self-driving.

Legal and ethical challenges are not to be underestimated either. Most countries impose strict limits on testing self-driving cars on public roads. Similar limitations apply to the use of civilian drones. And the ethics of fully autonomous cars is still in its infancy. Autonomous cars probably won’t be caught texting, but they will still be confronted with tough decisions when trying to avoid potential accidents. Current research engages engineers and philosophers to work on how to assist cars when making split-second decisions that can raise ethical dilemmas….(More)”

The digital revolution liberating Latin American people

Curated on Posted on by Stefaan Verhulst

Luis Alberto Moreno in the Financial Times: “Imagine a place where citizens can deal with the state entirely online, where all health records are electronic and the wait for emergency care is just seven minutes. Singapore? Switzerland? Try Colima, Mexico.

Pessimists fear the digital revolution will only widen social and economic disparities in the developing world — particularly in Latin America, the world’s most unequal region. But Colima, though small and relatively prosperous, shows how some of the region’s governments are harnessing these tools to modernise services, improve quality of life and share the benefits of technology more equitably.

In the past 10 years, this state of about 600,000 people has transformed the way government works, going completely digital. Its citizens can carry out 62 procedures online, from applying for permits to filing crime reports. No internet at home? Colima offers hundreds of free WiFi hotspots.

Colombia and Peru are taking broadband to remote corners of their rugged territories. Bogotá has subsidised the ex­pansion of its fibre optic network, which now links virtually every town in the country. Peru is expanding a programme that aims to bring WiFi to schools, hospitals and other public buildings in each of its 25 regions. The Colombian plan, Vive Digital, fosters internet adoption among all its citizens. Taxes on computers, tablets and smartphones have been scrapped. Low-income families have been given vouchers to sign up for broadband. In five years, the percentage of households connected to the internet jumped from 16 per cent to 50 per cent. Among small businesses it soared from 7 per cent to 61 per cent .

Inexpensive devices and ubiquitous WiFi, however, do not guarantee widespread usage. Diego Molano Vega, an architect of Vive Digital, found that many programs designed for customers in developed countries were ill suited to most Colombians. “There are no poor people in Silicon Valley,” he says. Latin American governments should use their purchasing power to push for development of digital services easily adopted by their citizens and businesses. Chile is a leader: it has digitised hundreds of trámites — bureaucratic procedures involving endless forms and queues. In a 4,300km-longcountry of mountains, deserts and forests, this enables access to all sorts of services through the internet. Entrepreneurs can now register businesses online for free in a single day.

In Chile, entrepreneurs can now register new businesses online for free in a single day…

Technology can be harnessed to boost equity in education. Brazil’s Mato Grosso do Sul state launched a free online service to prepare high school students for a tough national exam in which a good grade is a prerequisite for admission to federal universities. On average the results of the students who used the service were 31 per cent higher than those of their peers, prompting 10 other states to adopt the system.

Digital tools can also help raise competitiveness in business. Uruguay’s livestock information system keeps track of the country’s cattle. The publicly financed electronic registry ensures every beast can be traced, making it easier to monitor outbreaks of diseases….(More)”

 

Forging Trust Communities: How Technology Changes Politics

Curated on Posted on by Stefaan Verhulst

Book by Irene S. Wu: “Bloggers in India used social media and wikis to broadcast news and bring humanitarian aid to tsunami victims in South Asia. Terrorist groups like ISIS pour out messages and recruit new members on websites. The Internet is the new public square, bringing to politics a platform on which to create community at both the grassroots and bureaucratic level. Drawing on historical and contemporary case studies from more than ten countries, Irene S. Wu’s Forging Trust Communities argues that the Internet, and the technologies that predate it, catalyze political change by creating new opportunities for cooperation. The Internet does not simply enable faster and easier communication, but makes it possible for people around the world to interact closely, reciprocate favors, and build trust. The information and ideas exchanged by members of these cooperative communities become key sources of political power akin to military might and economic strength.

Wu illustrates the rich world history of citizens and leaders exercising political power through communications technology. People in nineteenth-century China, for example, used the telegraph and newspapers to mobilize against the emperor. In 1970, Taiwanese cable television gave voice to a political opposition demanding democracy. Both Qatar (in the 1990s) and Great Britain (in the 1930s) relied on public broadcasters to enhance their influence abroad. Additional case studies from Brazil, Egypt, the United States, Russia, India, the Philippines, and Tunisia reveal how various technologies function to create new political energy, enabling activists to challenge institutions while allowing governments to increase their power at home and abroad.

Forging Trust Communities demonstrates that the way people receive and share information through network communities reveals as much about their political identity as their socioeconomic class, ethnicity, or religion. Scholars and students in political science, public administration, international studies, sociology, and the history of science and technology will find this to be an insightful and indispensable work…(More)”

Selected Readings on Data Governance

Curated on Posted on by Jos Berens

Jos Berens (Centre for Innovation, Leiden University) and Stefaan G. Verhulst (GovLab)

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of data governance was originally published in 2015.

Context
The field of Data Collaboratives is premised on the idea that sharing and opening-up private sector datasets has great – and yet untapped – potential for promoting social good. At the same time, the potential of data collaboratives depends on the level of societal trust in the exchange, analysis and use of the data exchanged. Strong data governance frameworks are essential to ensure responsible data use. Without such governance regimes, the emergent data ecosystem will be hampered and the (perceived) risks will dominate the (perceived) benefits. Further, without adopting a human-centered approach to the design of data governance frameworks, including iterative prototyping and careful consideration of the experience, the responses may fail to be flexible and targeted to real needs.

Selected Readings List (in alphabetical order)

Annotated Selected Readings List (in alphabetical order)

Better Place Lab, “Privacy, Transparency and Trust.” Mozilla, 2015. Available from: http://www.betterplace-lab.org/privacy-report.

  • This report looks specifically at the risks involved in the social sector having access to datasets, and the main risks development organizations should focus on to develop a responsible data use practice.
  • Focusing on five specific countries (Brazil, China, Germany, India and Indonesia), the report displays specific country profiles, followed by a comparative analysis centering around the topics of privacy, transparency, online behavior and trust.
  • Some of the key findings mentioned are:
    • A general concern on the importance of privacy, with cultural differences influencing conception of what privacy is.
    • Cultural differences determining how transparency is perceived, and how much value is attached to achieving it.
    • To build trust, individuals need to feel a personal connection or get a personal recommendation – it is hard to build trust regarding automated processes.

Montjoye, Yves Alexandre de; Kendall, Jake and; Kerry, Cameron F. “Enabling Humanitarian Use of Mobile Phone Data.” The Brookings Institution, 2015. Available from: http://www.brookings.edu/research/papers/2014/11/12-enabling-humanitarian-use-mobile-phone-data.

  • Focussing in particular on mobile phone data, this paper explores ways of mitigating privacy harms involved in using call detail records for social good.
  • Key takeaways are the following recommendations for using data for social good:
    • Engaging companies, NGOs, researchers, privacy experts, and governments to agree on a set of best practices for new privacy-conscientious metadata sharing models.
    • Accepting that no framework for maximizing data for the public good will offer perfect protection for privacy, but there must be a balanced application of privacy concerns against the potential for social good.
    • Establishing systems and processes for recognizing trusted third-parties and systems to manage datasets, enable detailed audits, and control the use of data so as to combat the potential for data abuse and re-identification of anonymous data.
    • Simplifying the process among developing governments in regards to the collection and use of mobile phone metadata data for research and public good purposes.

Centre for Democracy and Technology, “Health Big Data in the Commercial Context.” Centre for Democracy and Technology, 2015. Available from: https://cdt.org/insight/health-big-data-in-the-commercial-context/.

  • Focusing particularly on the privacy issues related to using data generated by individuals, this paper explores the overlap in privacy questions this field has with other data uses.
  • The authors note that although the Health Insurance Portability and Accountability Act (HIPAA) has proven a successful approach in ensuring accountability for health data, most of these standards do not apply to developers of the new technologies used to collect these new data sets.
  • For non-HIPAA covered, customer facing technologies, the paper bases an alternative framework for consideration of privacy issues. The framework is based on the Fair Information Practice Principles, and three rounds of stakeholder consultations.

Center for Information Policy Leadership, “A Risk-based Approach to Privacy: Improving Effectiveness in Practice.” Centre for Information Policy Leadership, Hunton & Williams LLP, 2015. Available from: https://www.informationpolicycentre.com/uploads/5/7/1/0/57104281/white_paper_1-a_risk_based_approach_to_privacy_improving_effectiveness_in_practice.pdf.

  • This white paper is part of a project aiming to explain what is often referred to as a new, risk-based approach to privacy, and the development of a privacy risk framework and methodology.
  • With the pace of technological progress often outstripping the capabilities of privacy officers to keep up, this method aims to offer the ability to approach privacy matters in a structured way, assessing privacy implications from the perspective of possible negative impact on individuals.
  • With the intended outcomes of the project being “materials to help policy-makers and legislators to identify desired outcomes and shape rules for the future which are more effective and less burdensome”, insights from this paper might also feed into the development of innovative governance mechanisms aimed specifically at preventing individual harm.

Centre for Information Policy Leadership, “Data Governance for the Evolving Digital Market Place”, Centre for Information Policy Leadership, Hunton & Williams LLP, 2011. Available from: http://www.huntonfiles.com/files/webupload/CIPL_Centre_Accountability_Data_Governance_Paper_2011.pdf.

  • This paper argues that as a result of the proliferation of large scale data analytics, new models governing data inferred from society will shift responsibility to the side of organizations deriving and creating value from that data.
  • It is noted that, with the reality of the challenge corporations face of enabling agile and innovative data use “In exchange for increased corporate responsibility, accountability [and the governance models it mandates, ed.] allows for more flexible use of data.”
  • Proposed as a means to shift responsibility to the side of data-users, the accountability principle has been researched by a worldwide group of policymakers. Tailing the history of the accountability principle, the paper argues that it “(…) requires that companies implement programs that foster compliance with data protection principles, and be able to describe how those programs provide the required protections for individuals.”
  • The following essential elements of accountability are listed:
    • Organisation commitment to accountability and adoption of internal policies consistent with external criteria
    • Mechanisms to put privacy policies into effect, including tools, training and education
    • Systems for internal, ongoing oversight and assurance reviews and external verification
    • Transparency and mechanisms for individual participation
    • Means of remediation and external enforcement

Crawford, Kate; Schulz, Jason. “Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harm.” NYU School of Law, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2325784&download=yes.

  • Considering the privacy implications of large-scale analysis of numerous data sources, this paper proposes the implementation of a ‘procedural data due process’ mechanism to arm data subjects against potential privacy intrusions.
  • The authors acknowledge that some privacy protection structures already know similar mechanisms. However, due to the “inherent analytical assumptions and methodological biases” of big data systems, the authors argue for a more rigorous framework.

Letouze, Emmanuel, and; Vinck, Patrick. “The Ethics and Politics of Call Data Analytics”, DataPop Alliance, 2015. Available from: http://static1.squarespace.com/static/531a2b4be4b009ca7e474c05/t/54b97f82e4b0ff9569874fe9/1421442946517/WhitePaperCDRsEthicFrameworkDec10-2014Draft-2.pdf.

  • Focusing on the use of Call Detail Records (CDRs) for social good in development contexts, this whitepaper explores both the potential of these datasets – in part by detailing recent successful efforts in the space – and political and ethical constraints to their use.
  • Drawing from the Menlo Report Ethical Principles Guiding ICT Research, the paper explores how these principles might be unpacked to inform an ethics framework for the analysis of CDRs.

Data for Development External Ethics Panel, “Report of the External Ethics Review Panel.” Orange, 2015. Available from: http://www.d4d.orange.com/fr/content/download/43823/426571/version/2/file/D4D_Challenge_DEEP_Report_IBE.pdf.

  • This report presents the findings of the external expert panel overseeing the Orange Data for Development Challenge.
  • Several types of issues faced by the panel are described, along with the various ways in which the panel dealt with those issues.

Federal Trade Commission Staff Report, “Mobile Privacy Disclosures: Building Trust Through Transparency.” Federal Trade Commission, 2013. Available from: www.ftc.gov/os/2013/02/130201mobileprivacyreport.pdf.

  • This report looks at ways to address privacy concerns regarding mobile phone data use. Specific advise is provided for the following actors:
    • Platforms, or operating systems providers
    • App developers
    • Advertising networks and other third parties
    • App developer trade associations, along with academics, usability experts and privacy researchers

Mirani, Leo. “How to use mobile phone data for good without invading anyone’s privacy.” Quartz, 2015. Available from: http://qz.com/398257/how-to-use-mobile-phone-data-for-good-without-invading-anyones-privacy/.

  • This paper considers the privacy implications of using call detail records for social good, and ways to mitigate risks of privacy intrusion.
  • Taking example of the Orange D4D challenge and the anonymization strategy that was employed there, the paper describes how classic ‘anonymization’ is often not enough. The paper then lists further measures that can be taken to ensure adequate privacy protection.

Bernholz, Lucy. “Several Examples of Digital Ethics and Proposed Practices” Stanford Ethics of Data conference, 2014, Available from: http://www.scribd.com/doc/237527226/Several-Examples-of-Digital-Ethics-and-Proposed-Practices.

  • This list of readings prepared for Stanford’s Ethics of Data conference lists some of the leading available literature regarding ethical data use.

Abrams, Martin. “A Unified Ethical Frame for Big Data Analysis.” The Information Accountability Foundation, 2014. Available from: http://www.privacyconference2014.org/media/17388/Plenary5-Martin-Abrams-Ethics-Fundamental-Rights-and-BigData.pdf.

  • Going beyond privacy, this paper discusses the following elements as central to developing a broad framework for data analysis:
    • Beneficial
    • Progressive
    • Sustainable
    • Respectful
    • Fair

Lane, Julia; Stodden, Victoria; Bender, Stefan, and; Nissenbaum, Helen, “Privacy, Big Data and the Public Good”, Cambridge University Press, 2014. Available from: http://www.dataprivacybook.org.

  • This book treats the privacy issues surrounding the use of big data for promoting the public good.
  • The questions being asked include the following:
    • What are the ethical and legal requirements for scientists and government officials seeking to serve the public good without harming individual citizens?
    • What are the rules of engagement?
    • What are the best ways to provide access while protecting confidentiality?
    • Are there reasonable mechanisms to compensate citizens for privacy loss?

Richards, Neil M, and; King, Jonathan H. “Big Data Ethics”. Wake Forest Law Review, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2384174.

  • This paper describes the growing impact of big data analytics on society, and argues that because of this impact, a set of ethical principles to guide data use is called for.
  • The four proposed themes are: privacy, confidentiality, transparency and identity.
  • Finally, the paper discusses how big data can be integrated into society, going into multiple facets of this integration, including the law, roles of institutions and ethical principles.

OECD, “OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data”. Available from: http://www.oecd.org/sti/ieconomy/oecdguidelinesontheprotectionofprivacyandtransborderflowsofpersonaldata.htm.

  • A globally used set of principles to inform thought about handling personal data, the OECD privacy guidelines serve as one the leading standards for informing privacy policies and data governance structures.
  • The basic principles of national application are the following:
    • Collection Limitation Principle
    • Data Quality Principle
    • Purpose Specification Principle
    • Use Limitation Principle
    • Security Safeguards Principle
    • Openness Principle
    • Individual Participation Principle
    • Accountability Principle

The White House Big Data and Privacy Working Group, “Big Data: Seizing Opportunities, Preserving Values”, White House, 2015. Available from: https://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_5.1.14_final_print.pdf.

  • Documenting the findings of the White House big data and privacy working group, this report lists i.a. the following key recommendations regarding data governance:
    • Bringing greater transparency to the data services industry
    • Stimulating international conversation on big data, with multiple stakeholders
    • With regard to educational data: ensuring data is used for the purpose it is collected for
    • Paying attention to the potential for big data to facilitate discrimination, and expanding technical understanding to stop discrimination

William Hoffman, “Pathways for Progress” World Economic Forum, 2015. Available from: http://www3.weforum.org/docs/WEFUSA_DataDrivenDevelopment_Report2015.pdf.

  • This paper treats i.a. the lack of well-defined and balanced governance mechanisms as one of the key obstacles preventing particularly corporate sector data from being shared in a controlled space.
  • An approach that balances the benefits against the risks of large scale data usage in a development context, building trust among all stake holders in the data ecosystem, is viewed as key.
  • Furthermore, this whitepaper notes that new governance models are required not just by the growing amount of data and analytical capacity, and more refined methods for analysis. The current “super-structure” of information flows between institutions is also seen as one of the key reasons to develop alternatives to the current – outdated – approaches to data governance.

Five Headlines from a Big Month for the Data Revolution

Curated on Posted on by Stefaan Verhulst

Sarah T. Lucas at Post2015.org: “If the history of the data revolution were written today, it would include three major dates. May 2013, when theHigh Level Panel on the Post-2015 Development Agenda first coined the phrase “data revolution.” November 2014, when the UN Secretary-General’s Independent Expert Advisory Group (IEAG) set a vision for it. And April 2015, when five headliner stories pushed the data revolution from great idea to a concrete roadmap for action.

The April 2015 Data Revolution Headlines

1. The African Data Consensus puts Africa in the lead on bringing the data revolution to the regional level. TheAfrica Data Consensus (ADC) envisions “a profound shift in the way that data is harnessed to impact on development decision-making, with a particular emphasis on building a culture of usage.” The ADC finds consensus across 15 “data communities”—ranging from open data to official statistics to geospatial data, and is endorsed by Africa’s ministers of finance. The ADC gets top billing in my book, as the first contribution that truly reflects a large diversity of voices and creates a political hook for action. (Stay tuned for a blog from my colleague Rachel Quint on the ADC).

2. The Sustainable Development Solutions Network (SDSN) gets our minds (and wallets) around the data needed to measure the SDGs. The SDSN Needs Assessment for SDG Monitoring and Statistical Capacity Development maps the investments needed to improve official statistics. My favorite parts are the clear typology of data (see pg. 12), and that the authors are very open about the methods, assumptions, and leaps of faith they had to take in the costing exercise. They also start an important discussion about how advances in information and communications technology, satellite imagery, and other new technologies have the potential to expand coverage, increase analytic capacity, and reduce the cost of data systems.

3. The Overseas Development Institute (ODI) calls on us to find the “missing millions.” ODI’s The Data Revolution: Finding the Missing Millions presents the stark reality of data gaps and what they mean for understanding and addressing development challenges. The authors highlight that even that most fundamental of measures—of poverty levels—could be understated by as much as a quarter. And that’s just the beginning. The report also pushes us to think beyond the costs of data, and focus on how much good data can save. With examples of data lowering the cost of doing government business, the authors remind us to think about data as an investment with real economic and social returns.

4. Paris21 offers a roadmap for putting national statistic offices (NSOs) at the heart of the data revolution.Paris21’s Roadmap for a Country-Led Data Revolution does not mince words. It calls on the data revolution to “turn a vicious cycle of [NSO] underperformance and inadequate resources into a virtuous one where increased demand leads to improved performance and an increase in resources and capacity.” It makes the case for why NSOs are central and need more support, while also pushing them to modernize, innovate, and open up. The roadmap gets my vote for best design. This ain’t your grandfather’s statistics report!

5. The Cartagena Data Festival features real-live data heroes and fosters new partnerships. The Festival featured data innovators (such as terra-i using satellite data to track deforestation), NSOs on the leading edge of modernization and reform (such as Colombia and the Philippines), traditional actors using old data in new ways (such as the Inter-American Development Bank’s fantastic energy database), groups focused on citizen-generated data (such as The Data Shift and UN My World), private firms working with big data for social good (such asTelefónica), and many others—all reminding us that the data revolution is well underway and will not be stopped. Most importantly, it brought these actors together in one place. You could see the sparks flying as folks learned from each other and hatched plans together. The Festival gets my vote for best conference of a lifetime, with the perfect blend of substantive sessions, intense debate, learning, inspiration, new connections, and a lot of fun. (Stay tuned for a post from my colleague Kristen Stelljes and me for more on Cartagena).

This month full of headlines leaves no room for doubt—momentum is building fast on the data revolution. And just in time.

With the Financing for Development (FFD) conference in Addis Ababa in July, the agreement of Sustainable Development Goals in New York in September, and the Climate Summit in Paris in December, this is a big political year for global development. Data revolutionaries must seize this moment to push past vision, past roadmaps, to actual action and results…..(More)”

New surveys reveal dynamism, challenges of open data-driven businesses in developing countries

Curated on Posted on by Stefaan Verhulst

Alla Morrison at World Bank Open Data blog: “Was there a class of entrepreneurs emerging to take advantage of the economic possibilities offered by open data, were investors keen to back such companies, were governments tuned to and responsive to the demands of such companies, and what were some of the key financing challenges and opportunities in emerging markets? As we began our work on the concept of an Open Fund, we partnered with Ennovent (India), MDIF (East Asia and Latin America) and Digital Data Divide (Africa) to conduct short market surveys to answer these questions, with a focus on trying to understand whether a financing gap truly existed in these markets. The studies were fairly quick (4-6 weeks) and reached only a small number of companies (193 in India, 70 in Latin America, 63 in South East Asia, and 41 in Africa – and not everybody responded) but the findings were fairly consistent.

  • Open data is still a very nascent concept in emerging markets. and there’s only a small class of entrepreneurs/investors that is aware of the economic possibilities; there’s a lot of work to do in the ‘enabling environment’
    • In many regions the distinction between open data, big data, and private sector generated/scraped/collected data was blurry at best among entrepreneurs and investors (some of our findings consequently are better indicators of  data-driven rather than open data-driven businesses)
  • There’s a small but growing number of open data-driven companies in all the markets we surveyed and these companies target a wide range of consumers/users and are active in multiple sectors
    • A large percentage of identified companies operate in sectors with high social impact – health and wellness, environment, agriculture, transport. For instance, in India, after excluding business analytics companies, a third of data companies seeking financing are in healthcare and a fifth in food and agriculture, and some of them have the low-income population or the rural segment of India as an intended beneficiary segment. In Latin America, the number of companies in business services, research and analytics was closely followed by health, environment and agriculture. In Southeast Asia, business, consumer services, and transport came out in the lead.
    • We found the highest number of companies in Latin America and Asia with the following countries leading the way – Mexico, Chile, and Brazil, with Colombia and Argentina closely behind in Latin America; and India, Indonesia, Philippines, and Malaysia in Asia
  • An actionable pipeline of data-driven companies exists in Latin America and in Asia
    • We heard demand for different kinds of financing (equity, debt, working capital) but the majority of the need was for equity and quasi-equity in amounts ranging from $100,000 to $5 million USD, with averages of between $2 and $3 million USD depending on the region.
  • There’s a significant financing gap in all the markets
    • The investment sizes required, while they range up to several million dollars, are generally small. Analysis of more than 300 data companies in Latin America and Asia indicates a total estimated need for financing of more than $400 million
  • Venture capitals generally don’t recognize data as a separate sector and club data-driven companies with their standard information communication technology (ICT) investments
    • Interviews with founders suggest that moving beyond seed stage is particularly difficult for data-driven startups. While many companies are able to cobble together an initial seed round augmented by bootstrapping to get their idea off the ground, they face a great deal of difficulty when trying to raise a second, larger seed round or Series A investment.
    • From the perspective of startups, investors favor banal e-commerce (e.g., according toTech in Asia, out of the $645 million in technology investments made public across the region in 2013, 92% were related to fashion and online retail) or consumer service startups and ignore open data-focused startups even if they have a strong business model and solid key performance indicators. The space is ripe for a long-term investor with a generous risk appetite and multiple bottom line goals.
  • Poor data quality was the number one issue these companies reported.
    • Companies reported significant waste and inefficiency in accessing/scraping/cleaning data.

The analysis below borrows heavily from the work done by the partners. We should of course mention that the findings are provisional and should not be considered authoritative (please see the section on methodology for more details)….(More).”