We are finally getting better at predicting organized conflict

Curated on Posted on by Stefaan Verhulst

Tate Ryan-Mosley at MIT Technology Review: “People have been trying to predict conflict for hundreds, if not thousands, of years. But it’s hard, largely because scientists can’t agree on its nature or how it arises. The critical factor could be something as apparently innocuous as a booming population or a bad year for crops. Other times a spark ignites a powder keg, as with the assassination of Archduke Franz Ferdinand of Austria in the run-up to World War I.

Political scientists and mathematicians have come up with a slew of different methods for forecasting the next outbreak of violence—but no single model properly captures how conflict behaves. A study published in 2011 by the Peace Research Institute Oslo used a single model to run global conflict forecasts from 2010 to 2050. It estimated a less than .05% chance of violence in Syria. Humanitarian organizations, which could have been better prepared had the predictions been more accurate, were caught flat-footed by the outbreak of Syria’s civil war in March 2011. It has since displaced some 13 million people.

Bundling individual models to maximize their strengths and weed out weakness has resulted in big improvements. The first public ensemble model, the Early Warning Project, launched in 2013 to forecast new instances of mass killing. Run by researchers at the US Holocaust Museum and Dartmouth College, it claims 80% accuracy in its predictions.

Improvements in data gathering, translation, and machine learning have further advanced the field. A newer model called ViEWS, built by researchers at Uppsala University, provides a huge boost in granularity. Focusing on conflict in Africa, it offers monthly predictive readouts on multiple regions within a given state. Its threshold for violence is a single death.

Some researchers say there are private—and in some cases, classified—predictive models that are likely far better than anything public. Worries that making predictions public could undermine diplomacy or change the outcome of world events are not unfounded. But that is precisely the point. Public models are good enough to help direct aid to where it is needed and alert those most vulnerable to seek safety. Properly used, they could change things for the better, and save lives in the process….(More)”.

Handbook of Research on Politics in the Computer Age

Curated on Posted on by Stefaan Verhulst

Book edited by Ashu M. G. Solo: “Technology and particularly the Internet have caused many changes in the realm of politics. Aspects of engineering, computer science, mathematics, or natural science can be applied to politics. Politicians and candidates use their own websites and social network profiles to get their message out. Revolutions in many countries in the Middle East and North Africa have started in large part due to social networking websites such as Facebook and Twitter. Social networking has also played a role in protests and riots in numerous countries. The mainstream media no longer has a monopoly on political commentary as anybody can set up a blog or post a video online. Now, political activists can network together online.

The Handbook of Research on Politics in the Computer Age is a pivotal reference source that serves to increase the understanding of methods for politics in the computer age, the effectiveness of these methods, and tools for analyzing these methods. The book includes research chapters on different aspects of politics with information technology, engineering, computer science, or math, from 27 researchers at 20 universities and research organizations in Belgium, Brazil, Cape Verde, Egypt, Finland, France, Hungary, Italy, Mexico, Nigeria, Norway, Portugal, and the United States of America. Highlighting topics such as online campaigning and fake news, the prospective audience includes, but is not limited to, researchers, political and public policy analysts, political scientists, engineers, computer scientists, political campaign managers and staff, politicians and their staff, political operatives, professors, students, and individuals working in the fields of politics, e-politics, e-government, new media and communication studies, and Internet marketing….(More)”.

We Need a Fourth Branch of Government

Curated on Posted on by Stefaan Verhulst

George A. Papandreou at The New York Times: “In ancient times, politics was born of the belief that we can be masters of our own fate, and democracy became a continuing, innovative project to guarantee people a say in public decisions.

Today, however, we live in a paradox. Humanity has created vast wealth and technological know-how that could contribute to solutions for the global common good, yet immense numbers of people are disempowered, marginalized and suffering from a deep sense of insecurity. Working together, we have the ability to reshape the world as we know it. Unfortunately, that power rests in the hands of only a few.

The marginalization we see today is rooted in the globalization promoted by policy models such as the Washington Consensus, which distanced politics and governance from economic power. Companies in the financial, pharmaceutical, agricultural, oil and tech industries are no longer governed by the laws of a single state — they live in a separate global stratosphere, one regulated to suit their interests.

The consequences of all this are huge disparities in wealth and power. There is, for example, an overconcentration of money in media and politics, due to lobbying and outright corruption. And in many countries, democratic institutions have been captured and the will of the people has been compromised….

We could embrace reactive politics, elect authoritarian leaders, build walls, and promote isolationism and racism. This path offers a simple yet illusory way to “take back control,” but in fact accomplishes the opposite: It gives up control to power-hungry demagogues who divide us, weaken civil society and feed us dead-end solutions.

But rather than embrace those false promises, let us instead reinvent and deepen democratic institutions, in order to empower people, tame global capitalism, eliminate inequality and assert control over our international techno-society.

From my experience, an important step toward these goals would be to create a fourth branch of government.

This new deliberative branch, in which all citizens — the “demos” — could participate, would sit alongside the executive, legislative and judicial branches. All laws and decisions would first go through an e-deliberation process before being debated in our city halls, parliaments or congresses.

Inspired by the agora of ideas and debate in ancient Athens, I set up as prime minister a rudimentary “wiki-law” process for deliberating issues online before laws are voted on. Trusting collective wisdom brought insightful and invaluable responses.

In contrast to how social media works today, a similar platform could develop transparent algorithms that use artificial intelligence to promote wholesome debate and informed dialogue while fairly aggregating citizens’ positions to promote consensus building. All who participate in this public e-agora would appear under their true identities — real voices, not bots. Eponymous, not anonymous.

To facilitate debate, forums of professionals could give informed opinions on issues of the day. Public television, newspapers, radio and podcasts could enlighten the conversation. Schools would be encouraged to participate. So-called deliberative polling (again inspired by ancient Athens and developed for modern society by James Fishkin at Stanford University) could improve decision-making by leveraging sustained dialogue among polling participants and experts to produce more informed public opinion. The concept was used by the Citizens’ Assembly in Ireland from 2016 to 2018, a riveting exercise in deliberative democracy that produced breakthroughs on seemingly intractable issues such as abortion.

Today, we are on the verge of momentous global changes, in robotics, A.I., the climate and more. The world’s citizens must debate the ethical implications of our increasingly godlike technological powers….(More)”

Why policy networks don’t work (the way we think they do)

Curated on Posted on by Stefaan Verhulst

Blog by James Georgalakis: “Is it who you know or what you know? The literature on evidence uptake and the role of communities of experts mobilised at times of crisis convinced me that a useful approach would be to map the social network that emerged around the UK-led mission to Sierra Leone so it could be quantitatively analysed. Despite the well-deserved plaudits for my colleagues at IDS and their partners in the London School of Hygiene and Tropical Medicine, the UK Department for International Development (DFID), the Wellcome Trust and elsewhere, I was curious to know why they had still met real resistance to some of their policy advice. This included the provision of home care kits for victims of the virus who could not access government or NGO run Ebola Treatment Units (ETUs).

It seemed unlikely these challenges were related to poor communications. The timely provision of accessible research knowledge by the Ebola Response Anthropology Platform has been one of the most celebrated aspects of the mobilisation of anthropological expertise. This approach is now being replicated in the current Ebola response in the Democratic Republic of Congo (DRC).  Perhaps the answer was in the network itself. This was certainly indicated by some of the accounts of the crisis by those directly involved.

Social network analysis

I started by identifying the most important looking policy interactions that took place between March 2014, prior to the UK assuming leadership of the Sierra Leone international response and mid-2016, when West Africa was finally declared Ebola free. They had to be central to the efforts to coordinate the UK response and harness the use of evidence. I then looked for documents related to these events, a mixture of committee minutes, reports and correspondence , that could confirm who was an active participant in each. This analysis of secondary sources related to eight separate policy processes and produced a list of 129 individuals. However, I later removed a large UK conference that took place in early 2016 at which learning from the crisis was shared.  It appeared that most delegates had no significant involvement in giving policy advice during the crisis. This reduced the network to 77….(More)”.

Risk identification and management for the research use of government administrative data

Curated on Posted on by Stefaan Verhulst

Paper by Elizabeth Shepherd, Anna Sexton, Oliver Duke-Williams, and Alexandra Eveleigh: “Government administrative data have enormous potential for public and individual benefit through improved educational and health services to citizens, medical research, environmental and climate interventions and exploitation of scarce energy resources. Administrative data is usually “collected primarily for administrative (not research) purposes by government departments and other organizations for the purposes of registration, transaction and record keeping, during the delivery of a service” such as health care, vehicle licensing, tax and social security systems (https://esrc.ukri.org/funding/guidance-for-applicants/research-ethics/useful-resources/key-terms-glossary/). Administrative data are usually distinguished from data collected for statistical use such as the census. Unlike administrative records, they do not provide evidence of activities and generally lack metadata and context relating to provenance. Administrative data, unlike open data, are not routinely made open or accessible, but access can be provided only on request to named researchers for specified research projects through research access protocols that often take months to negotiate and are subject to significant constraints around re-use such as the use of safe havens. Researchers seldom make use of freedom of information or access to information protocols to access such data because they need specific datasets and particular levels of granularity and an ability to re-process data, which are not made generally available. This study draws on research undertaken by the authors as part of the Administrative Data Research Centre in England (ADRC-E). The research examined perspectives on the sharing, linking and re-use (secondary use) of administrative data in England, viewed through three analytical themes: trust, consent and risk. This study presents the analysis of the identification and management of risk in the research use of government administrative data and presents a risk framework. Risk management (i.e. coordinated activities that allow organizations to control risks, Lemieux, 2010) enables us to think about the balance between risk and benefit for the public good and for other stakeholders. Mitigating activities or management mechanisms used to control the identified risks depend on the resources available to implement the options, on the risk appetite or tolerance of the community and on the cost and likely effectiveness of the mitigation. Mitigation and risk do not work in isolation and should be holistically viewed by keeping the whole information infrastructure in balance across the administrative data system and between multiple stakeholders.

This study seeks to establish a clearer picture of risk with regard to government administrative data in England. It identifies and categorizes the risks arising from the research use of government administrative data. It identifies mitigating risk management activities, linked to five key stakeholder communities and discusses the locus of responsibility for risk management actions. The identification of the risks and of mitigation strategies is derived from the viewpoints of the interviewees and associated documentation; therefore, they reflect their lived experience. The five stakeholder groups identified from the data are as follows: individual researchers; employers of researchers; wider research community; data creators and providers and data subjects and the broader public. The primary sections of the study, following the methodology and research context, set out the seven identified types of risk events in the research use of administrative data, present a stakeholder mapping of the communities in this research affected by the risks and discuss the findings related to managing and mitigating the risks identified. The conclusion presents the elements of a new risk framework to inform future actions by the government data community and enable researchers to exploit the power of administrative data for public good….(More)”.

Index: Secondary Uses of Personal Data

Curated on Posted on by Michelle Winowatan

By Alexandra Shaw, Andrew Zahuranec, Andrew Young, Stefaan Verhulst

The Living Library Index–inspired by the Harper’s Index–provides important statistics and highlights global trends in governance innovation. This installment focuses on public perceptions regarding secondary uses of personal data (or the re-use of data initially collected for a different purpose). It provides a summary of societal perspectives toward personal data usage, sharing, and control. It is not meant to be comprehensive–rather, it intends to illustrate conflicting, and often confusing, attitudes toward the re-use of personal data. 

Please share any additional, illustrative statistics on data, or other issues at the nexus of technology and governance, with us at info@thelivinglib.org

Data ownership and control 

  • Percentage of Americans who say it is “very important” they control information collected about them: 74% – 2016
  • Americans who think that today’s privacy laws are not good enough at protecting people’s privacy online: 68% – 2016
  • Americans who say they have “a lot” of control over how companies collect and use their information: 9% – 2015
  • In a survey of 507 online shoppers, the number of respondents who indicated they don’t want brands tracking their location: 62% – 2015
  • In a survey of 507 online shoppers, the amount who “prefer offers that are targeted to where they are and what they are doing:” 60% – 2015 
  • Number of surveyed American consumers willing to provide data to corporations under the following conditions: 
    • “Data about my social concerns to better connect me with non-profit organizations that advance those causes:” 19% – 2018
    • “Data about my DNA to help me uncover any hereditary illnesses:” 21% – 2018
    • “Data about my interests and hobbies to receive relevant information and offers from online sellers:” 32% – 2018
    • “Data about my location to help me find the fastest route to my destination:” 40% – 2018
    • “My email address to receive exclusive offers from my favorite brands:”  56% – 2018  

Consumer Attitudes 

  • Academic study participants willing to donate personal data to research if it could lead to public good: 60% – 2014
  • Academic study participants willing to share personal data for research purposes in the interest of public good: 25% – 2014
  • Percentage who expect companies to “treat [them] like an individual, not as a member of some segment like ‘millennials’ or ‘suburban mothers:’” 74% – 2018 
    • Percentage who believe that brands should understand a “consumer’s individual situation (e.g. marital status, age, location, etc.)” when they’re being marketed to: 70% – 2018 Number who are “more annoyed” by companies now compared to 5 years ago: 40% – 2018Percentage worried their data is shared across companies without their permission: 88% – 2018Amount worried about a brand’s ability to track their behavior while on the brand’s website, app, or neither: 75% – 2018 
  • Consumers globally who expect brands to anticipate needs before they arise: 33%  – 2018 
  • Surveyed residents of the United Kingdom who identify as:
    • “Data pragmatists” willing to share personal data “under the right circumstances:” 58% – 2017
    • “Fundamentalists,” who would not share personal data for better services: 24% – 2017
    • Respondents who think data sharing is part of participating in the modern economy: 62% – 2018
    • Respondents who believe that data sharing benefits enterprises more than consumers: 75% – 2018
    • People who want more control over their data that enterprises collect: 84% – 2018
    • Percentage “unconcerned” about personal data protection: 18% – 2018
  • Percentage of Americans who think that government should do more to regulate large technology companies: 55% – 2018
  • Registered American voters who trust broadband companies with personal data “a great deal” or “a fair amount”: 43% – 2017
  • Americans who report experiencing a major data breach: 64% – 2017
  • Number of Americans who believe that their personal data is less secure than it was 5 years ago: 49% – 2019
  • Amount of surveyed American citizens who consider trust in a company an important factor for sharing data: 54% – 2018

Convenience

Microsoft’s 2015 Consumer Data Value Exchange Report attempts to understand consumer attitudes on the exchange of personal data across the global markets of Australia, Brazil, Canada, Colombia, Egypt, Germany, Kenya, Mexico, Nigeria, Spain, South Africa, United Kingdom and the United States. From their survey of 16,500 users, they find:

  • The most popular incentives for sharing data are: 
    • Cash rewards: 64% – 2015
    • Significant discounts: 49% – 2015
    • Streamlined processes: 29% – 2015
    • New ideas: 28% – 2015
  • Respondents who would prefer to see more ads to get new services: 34% – 2015
  • Respondents willing to share search terms for a service that enabled fewer steps to get things done: 70% – 2015 
  • Respondents willing to share activity data for such an improvement: 82% – 2015
  • Respondents willing to share their gender for “a service that inspires something new based on others like them:” 79% – 2015

A 2015 Pew Research Center survey presented Americans with several data-sharing scenarios related to convenience. Participants could respond: “acceptable,” “it depends,” or “not acceptable” to the following scenarios: 

  • Share health information to get access to personal health records and arrange appointments more easily:
    • Acceptable: 52% – 2015
    • It depends: 20% – 2015
    • Not acceptable: 26% – 2015
  • Share data for discounted auto insurance rates: 
    • Acceptable: 37% – 2015
    • It depends: 16% – 2015
    • Not acceptable: 45% – 2015
  • Share data for free social media services: 
    • Acceptable: 33% – 2015
    • It depends: 15% – 2015
    • Not acceptable: 51% – 2015
  • Share data on smart thermostats for cheaper energy bills: 
    • Acceptable: 33% – 2015
    • It depends: 15% – 2015
    • Not acceptable: 51% – 2015

Other Studies

  • Surveyed banking and insurance customers who would exchange personal data for:
    • Targeted auto insurance premiums: 64% – 2019
    • Better life insurance premiums for healthy lifestyle choices: 52% – 2019 
  • Surveyed banking and insurance customers willing to share data specifically related to income, location and lifestyle habits to: 
    • Secure faster loan approvals: 81.3% – 2019
    • Lower the chances of injury or loss: 79.7% – 2019 
    • Receive discounts on non-insurance products or services: 74.6% – 2019
    • Receive text alerts related to banking account activity: 59.8% – 2019 
    • Get saving advice based on spending patterns: 56.6% – 2019
  • In a survey of over 7,000 members of the public around the globe, respondents indicated:
    • They thought “smartphone and tablet apps used for navigation, chat, and news that can access your contacts, photos, and browsing history” is “creepy;” 16% – 2016
    • Emailing a friend about a trip to Paris and receiving advertisements for hotels, restaurants and excursions in Paris is “creepy:” 32% – 2016
    • A free fitness-tracking device that monitors your well-being and sends a monthly report to you and your employer is “creepy:” 45% – 2016
    • A telematics device that allows emergency services to track your vehicle is “creepy:” 78% – 2016
  • The number of British residents who do not want to work with virtual agents of any kind: 48% – 2017
  • Americans who disagree that “if companies give me a discount, it is a fair exchange for them to collect information about me without my knowing”: 91% – 2015

Data Brokers, Intermediaries, and Third Parties 

  • Americans who consider it acceptable for a grocery store to offer a free loyalty card in exchange for selling their shopping data to third parties: 47% – 2016
  • Number of people who know that “searches, site visits and purchases” are reviewed without consent:  55% – 2015
  • The number of people in 1991 who wanted companies to ask them for permission first before collecting their personal information and selling that data to intermediaries: 93% – 1991
    • Number of Americans who “would be very concerned if the company at which their data were stored sold it to another party:” 90% – 2008
    • Percentage of Americans who think it’s unacceptable for their grocery store to share their shopping data with third parties in exchange for a free loyalty card: 32% – 2016
  • Percentage of Americans who think that government needs to do more to regulate advertisers: 64% – 2016
    • Number of Americans who “want to have control over what marketers can learn about” them online: 84% – 2015
    • Percentage of Americans who think they have no power over marketers to figure out what they’re learning about them: 58% – 2015
  • Registered American voters who are “somewhat uncomfortable” or “very uncomfortable” with companies like Internet service providers or websites using personal data to recommend stories, articles, or videos:  56% – 2017
  • Registered American voters who are “somewhat uncomfortable” or “very uncomfortable” with companies like Internet service providers or websites selling their personal information to third parties for advertising purposes: 64% – 2017

Personal Health Data

The Robert Wood Johnson Foundation’s 2014 Health Data Exploration Project Report analyzes attitudes about personal health data (PHD). PHD is self-tracking data related to health that is traceable through wearable devices and sensors. The three major stakeholder groups involved in using PHD for public good are users, companies that track the users’ data, and researchers. 

  • Overall Respondents:
    • Percentage who believe anonymity is “very” or “extremely” important: 67% – 2014
    • Percentage who “probably would” or “definitely would” share their personal data with researchers: 78% – 2014
    • Percentage who believe that they own—or should own—all the data about them, even when it is indirectly collected: 54% – 2014
    • Percentage who think they share or ought to share ownership with the company: 30% – 2014
    • Percentage who think companies alone own or should own all the data about them: 4% – 2014
    • Percentage for whom data ownership “is not something I care about”: 13% – 2014
    • Percentage who indicated they wanted to own their data: 75% – 2014 
    • Percentage who would share data only if “privacy were assured:” 68% – 2014
    • People who would supply data regardless of privacy or compensation: 27% – 2014
      • Percentage of participants who mentioned privacy, anonymity, or confidentiality when asked under what conditions they would share their data:  63% – 2014
      • Percentage who would be “more” or “much more” likely to share data for compensation: 56% – 2014
      • Percentage who indicated compensation would make no difference: 38% – 2014
      • Amount opposed to commercial  or profit-making use of their data: 13% – 2014
    • Percentage of people who would only share personal health data with a guarantee of:
      • Privacy: 57% – 2014
      • Anonymization: 90% – 2014
  • Surveyed Researchers: 
    • Percentage who agree or strongly agree that self-tracking data would help provide more insights in their research: 89% – 2014
    • Percentage who say PHD could answer questions that other data sources could not: 95% – 2014
    • Percentage who have used public datasets: 57% – 2014
    • Percentage who have paid for data for research: 19% – 2014
    • Percentage who have used self-tracking data before for research purposes: 46% – 2014
    • Percentage who have worked with application, device, or social media companies: 23% – 2014
    • Percentage who “somewhat disagree” or “strongly disagree” there are barriers that cannot be overcome to using self-tracking data in their research: 82% – 2014 

SOURCES: 

“2019 Accenture Global Financial Services Consumer Study: Discover the Patterns in Personality”, Accenture, 2019. 

“Americans’ Views About Data Collection and Security”, Pew Research Center, 2015. 

“Data Donation: Sharing Personal Data for Public Good?”, ResearchGate, 2014.

“Data privacy: What the consumer really thinks,” Acxiom, 2018.

“Exclusive: Public wants Big Tech regulated”, Axios, 2018.

“Consumer data value exchange,” Microsoft, 2015.

“Crossing the Line: Staying on the right side of consumer privacy,” KPMG International Cooperative, 2016.

“How do you feel about the government sharing our personal data? – livechat”, The Guardian, 2017. 

“Personal data for public good: using health information in medical research”, The Academy of Medical Sciences, 2006. 

“Personal Data for the Public Good: New Opportunities to Enrich Understanding of Individual and Population Health”, Robert Wood Johnson Foundation, Health Data Exploration Project, Calit2, UC Irvine and UC San Diego, 2014. 

“Pew Internet and American Life Project: Cloud Computing Raises Privacy Concerns”, Pew Research Center, 2008. 

“Poll: Little Trust That Tech Giants Will Keep Personal Data Private”, Morning Consult & Politico, 2017. 

“Privacy and Information Sharing”, Pew Research Center, 2016. 

“Privacy, Data and the Consumer: What US Thinks About Sharing Data”, MarTech Advisor, 2018. 

“Public Opinion on Privacy”, Electronic Privacy Information Center, 2019. 

“Selligent Marketing Cloud Study Finds Consumer Expectations and Marketer Challenges are Rising in Tandem”, Selligent Marketing Cloud, 2018. 

“The Data-Sharing Disconnect: The Impact of Context, Consumer Trust, and Relevance in Retail Marketing,” Boxever, 2015. 

“Microsoft Research reveals understanding gap in the brand-consumer data exchange,” Microsoft Research, 2015.

“Survey: 58% will share personal data under the right circumstances”, Marketing Land: Third Door Media, 2019. 

“The state of privacy in post-Snowden America”, Pew Research Center, 2016. 

The Tradeoff Fallacy: How Marketers Are Misrepresenting American Consumers And Opening Them Up to Exploitation”, University of Pennsylvania, 2015.

Great Policy Successes

Curated on Posted on by Stefaan Verhulst

Book by Mallory Compton and Edited by Paul ‘t Hart: “With so much media and political criticism of their shortcomings and failures, it is easy to overlook the fact that many governments work pretty well much of the time. Great Policy Successes turns the spotlight on instances of public policy that are remarkably successful. It develops a framework for identifying and assessing policy successes, paying attention not just to their programmatic outcomes but also to the quality of the processes by which policies are designed and delivered, the level of support and legitimacy they attain, and the extent to which successful performance endures over time. The bulk of the book is then devoted to 15 detailed case studies of striking policy successes from around the world, including Singapore’s public health system, Copenhagen and Melbourne’s rise from stilted backwaters to the highly liveable and dynamic urban centres they are today, Brazil’s Bolsa Familia poverty relief scheme, the US’s GI Bill, and Germany’s breakthrough labour market reforms of the 2000s. Each case is set in context, its main actors are introduced, key events and decisions are described, the assessment framework is applied to gauge the nature and level of its success, key contributing factors to success are identified, and potential lessons and future challenges are identified. Purposefully avoiding the kind of heavy theorizing that characterizes many accounts of public policy processes, each case is written in an accessible and narrative style ideally suited for classroom use in conjunction with mainstream textbooks on public policy design, implementation, and evaluation….(More)”.

GovChain

Curated on Posted on by Stefaan Verhulst

Introduction to Report by Tom Rodden: “This report addresses the most discussed digital technologies of the last few years. There has been considerable debate about the potential benefits and threats that arise from the use of Distributed Ledger Technologies. What is clear from these debates is that blockchain is an important technology that has the potential to transform a range of sectors. The importance of Distributed Ledger Technology was identified and discussed in a 2016 report produced by Sir Mark Walport, the UK Government’s Chief Scientific Adviser at the time.

The report provided recommendations for the use of blockchain to meet national needs, and to ensure the UK’s competitiveness in the global arena. The report outlined the need for a broad response that spanned the public and private sector, whilst also recognising the need for leadership in the development and deployment of blockchain technologies.

This report provides an update and reflection on the use of blockchain technologies by Governments and Public Sector bodies around the world. Much has happened since 2016 and this report provides a reminder of the importance of Distributed Ledger Technologies for the public sector, and the various orientations of blockchains adopted across the globe. The team have mapped the various regulatory and policy responses to blockchain, and cryptocurrencies more broadly. This mapping not only reveals a varying degree of friendliness towards blockchain, it also highlights the challenges involved in implementing Distributed Ledger Technology systems in the public sector.

Distributed Ledger Technologies are an important technology for the public sector, albeit there exists a number of policy implications. If we are to show leadership in the use of blockchain and its application it is imperative that we are aware of both its benefits and limitations; and the issues that need to be addressed to ensure we gain value from the use of Distributed Ledger Technologies. This report captures the public sector experiences of blockchain technologies across the globe, and also documents the issues raised and the various responses. This is a hugely informative and useful document for those who seek to make use of blockchains in the public sector….(More)”.

Towards “Government as a Platform”? Preliminary Lessons from Australia, the United Kingdom and the United States

Curated on Posted on by Stefaan Verhulst

Paper by J. Ramon Gil‐Garcia, Paul Henman, and Martha Alicia Avila‐Maravilla: “In the last two decades, Internet portals have been used by governments around the world as part of very diverse strategies from service provision to citizen engagement. Several authors propose that there is an evolution of digital government reflected in the functionality and sophistication of these portals and other technologies. More recently, scholars and practitioners are proposing different conceptualizations of “government as a platform” and, for some, this could be the next stage of digital government. However, it is not clear what are the main differences between a sophisticated Internet portal and a platform. Therefore, based on an analysis of three of the most advanced national portals, this ongoing research paper explores to what extent these digital efforts clearly represent the basic characteristics of platforms. So, this paper explores questions such as: (1) to what extent current national portals reflect the characteristics of what has been called “government as a platform?; and (2) Are current national portals evolving towards “government as a platform”?…(More)”.

What statistics can and can’t tell us about ourselves

Curated on Posted on by Stefaan Verhulst

Hannah Fry at The New Yorker: “Harold Eddleston, a seventy-seven-year-old from Greater Manchester, was still reeling from a cancer diagnosis he had been given that week when, on a Saturday morning in February, 1998, he received the worst possible news. He would have to face the future alone: his beloved wife had died unexpectedly, from a heart attack.

Eddleston’s daughter, concerned for his health, called their family doctor, a well-respected local man named Harold Shipman. He came to the house, sat with her father, held his hand, and spoke to him tenderly. Pushed for a prognosis as he left, Shipman replied portentously, “I wouldn’t buy him any Easter eggs.” By Wednesday, Eddleston was dead; Dr. Shipman had murdered him.

Harold Shipman was one of the most prolific serial killers in history. In a twenty-three-year career as a mild-mannered and well-liked family doctor, he injected at least two hundred and fifteen of his patients with lethal doses of opiates. He was finally arrested in September, 1998, six months after Eddleston’s death.

David Spiegelhalter, the author of an important and comprehensive new book, “The Art of Statistics” (Basic), was one of the statisticians tasked by the ensuing public inquiry to establish whether the mortality rate of Shipman’s patients should have aroused suspicion earlier. Then a biostatistician at Cambridge, Spiegelhalter found that Shipman’s excess mortality—the number of his older patients who had died in the course of his career over the number that would be expected of an average doctor’s—was a hundred and seventy-four women and forty-nine men at the time of his arrest. The total closely matched the number of victims confirmed by the inquiry….

In 1825, the French Ministry of Justice ordered the creation of a national collection of crime records. It seems to have been the first of its kind anywhere in the world—the statistics of every arrest and conviction in the country, broken down by region, assembled and ready for analysis. It’s the kind of data set we take for granted now, but at the time it was extraordinarily novel. This was an early instance of Big Data—the first time that mathematical analysis had been applied in earnest to the messy and unpredictable realm of human behavior.

Or maybe not so unpredictable. In the early eighteen-thirties, a Belgian astronomer and mathematician named Adolphe Quetelet analyzed the numbers and discovered a remarkable pattern. The crime records were startlingly consistent. Year after year, irrespective of the actions of courts and prisons, the number of murders, rapes, and robberies reached almost exactly the same total. There is a “terrifying exactitude with which crimes reproduce themselves,” Quetelet said. “We know in advance how many individuals will dirty their hands with the blood of others. How many will be forgers, how many poisoners.”

To Quetelet, the evidence suggested that there was something deeper to discover. He developed the idea of a “Social Physics,” and began to explore the possibility that human lives, like planets, had an underlying mechanistic trajectory. There’s something unsettling in the idea that, amid the vagaries of choice, chance, and circumstance, mathematics can tell us something about what it is to be human. Yet Quetelet’s overarching findings still stand: at some level, human life can be quantified and predicted. We can now forecast, with remarkable accuracy, the number of women in Germany who will choose to have a baby each year, the number of car accidents in Canada, the number of plane crashes across the Southern Hemisphere, even the number of people who will visit a New York City emergency room on a Friday evening….(More)”