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Selected Readings on Blockchain and Identity

Curated on October 5, 2017September 4, 2019 by Stefaan Verhulst

By Hannah Pierce and Stefaan Verhulst

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 blockchain and identity was originally published in 2017.

The potential of blockchain and other distributed ledger technologies to create positive social change has inspired enthusiasm, broad experimentation, and some skepticism. In this edition of the Selected Readings series, we explore and curate the literature on blockchain and how it impacts identity as a means to access services and rights. (In a previous edition we considered the Potential of Blockchain for Transforming Governance).

Introduction

In 2008, an unknown source calling itself Satoshi Nakamoto released a paper named Bitcoin: A Peer-to-Peer Electronic Cash System which introduced Blockchain. Blockchain is a novel technology that uses a distributed ledger to record transactions and ensure compliance. Blockchain and other Distributed Ledger technologies (DLTs) rely on an ability to act as a vast, transparent, and secure public database.

Distributed ledger technologies (DLTs) have disruptive potential beyond innovation in products, services, revenue streams and operating systems within industry. By providing transparency and accountability in new and distributed ways, DLTs have the potential to positively empower underserved populations in myriad ways, including providing a means for establishing a trusted digital identity.

Consider the potential of DLTs for 2.4 billion people worldwide, about 1.5 billion of whom are over the age of 14, who are unable to prove identity to the satisfaction of authorities and other organizations – often excluding them from property ownership, free movement, and social protection as a result. At the same time, transition to a DLT led system of ID management involves various risks, that if not understood and mitigated properly, could harm potential beneficiaries.

Annotated Selected Reading List

Governance

Cuomo, Jerry, Richard Nash, Veena Pureswaran, Alan Thurlow, Dave Zaharchuk. “Building trust in government: Exploring the potential of blockchains.” IBM Institute for Business Value. January 2017.

This paper from the IBM Institute for Business Value culls findings from surveys conducted with over 200 government leaders in 16 countries regarding their experiences and expectations for blockchain technology. The report also identifies “Trailblazers”, or governments that expect to have blockchain technology in place by the end of the year, and details the views and approaches that these early adopters are taking to ensure the success of blockchain in governance. These Trailblazers also believe that there will be high yields from utilizing blockchain in identity management and that citizen services, such as voting, tax collection and land registration, will become increasingly dependent upon decentralized and secure identity management systems. Additionally, some of the Trailblazers are exploring blockchain application in borderless services, like cross-province or state tax collection, because the technology removes the need for intermediaries like notaries or lawyers to verify identities and the authenticity of transactions.

Mattila, Juri. “The Blockchain Phenomenon: The Disruptive Potential of Distributed Consensus Architectures.” Berkeley Roundtable on the International Economy. May 2016.

This working paper gives a clear introduction to blockchain terminology, architecture, challenges, applications (including use cases), and implications for digital trust, disintermediation, democratizing the supply chain, an automated economy, and the reconfiguration of regulatory capacity. As far as identification management is concerned, Mattila argues that blockchain can remove the need to go through a trusted third party (such as a bank) to verify identity online. This could strengthen the security of personal data, as the move from a centralized intermediary to a decentralized network lowers the risk of a mass data security breach. In addition, using blockchain technology for identity verification allows for a more standardized documentation of identity which can be used across platforms and services. In light of these potential capabilities, Mattila addresses the disruptive power of blockchain technology on intermediary businesses and regulating bodies.

Identity Management Applications

Allen, Christopher. “The Path to Self-Sovereign Identity.” Coindesk. April 27, 2016.

In this Coindesk article, author Christopher Allen lays out the history of digital identities, then explains a concept of a “self-sovereign” identity, where trust is enabled without compromising individual privacy. His ten principles for self-sovereign identity (Existence, Control, Access, Transparency, Persistence, Portability, Interoperability, Consent, Minimization, and Protection) lend themselves to blockchain technology for administration. Although there are actors making moves toward the establishment of self-sovereign identity, there are a few challenges that face the widespread implementation of these tenets, including legal risks, confidentiality issues, immature technology, and a reluctance to change established processes.

Jacobovitz, Ori. “Blockchain for Identity Management.” Department of Computer Science, Ben-Gurion University. December 11, 2016.

This technical report discusses advantages of blockchain technology in managing and authenticating identities online, such as the ability for individuals to create and manage their own online identities, which offers greater control over access to personal data. Using blockchain for identity verification can also afford the potential of “digital watermarks” that could be assigned to each of an individual’s transactions, as well as negating the creation of unique usernames and passwords online. After arguing that this decentralized model will allow individuals to manage data on their own terms, Jacobvitz provides a list of companies, projects, and movements that are using blockchain for identity management.

Mainelli, Michael. “Blockchain Will Help Us Prove Our Identities in a Digital World.” Harvard Business Review. March 16, 2017.

In this Harvard Business Review article, author Michael Mainelli highlights a solution to identity problems for rich and poor alike–mutual distributed ledgers (MDLs), or blockchain technology. These multi-organizational data bases with unalterable ledgers and a “super audit trail” have three parties that deal with digital document exchanges: subjects are individuals or assets, certifiers are are organizations that verify identity, and inquisitors are entities that conducts know-your-customer (KYC) checks on the subject. This system will allow for a low-cost, secure, and global method of proving identity. After outlining some of the other benefits that this technology may have in creating secure and easily auditable digital documents, such as greater tolerance that comes from viewing widely public ledgers, Mainelli questions if these capabilities will turn out to be a boon or a burden to bureaucracy and societal behavior.

Personal Data Security Applications

Banafa, Ahmed. “How to Secure the Internet of Things (IoT) with Blockchain.” Datafloq. August 15, 2016.

This article details the data security risks that are coming up as the Internet of Things continues to expand, and how using blockchain technology can protect the personal data and identity information that is exchanged between devices. Banafa argues that, as the creation and collection of data is central to the functions of Internet of Things devices, there is an increasing need to better secure data that largely confidential and often personally identifiable. Decentralizing IoT networks, then securing their communications with blockchain can allow to remain scalable, private, and reliable. Enabling blockchain’s peer-to-peer, trustless communication may also enable smart devices to initiate personal data exchanges like financial transactions, as centralized authorities or intermediaries will not be necessary.

Shrier, David, Weige Wu and Alex Pentland. “Blockchain & Infrastructure (Identity, Data Security).” Massachusetts Institute of Technology. May 17, 2016.

This paper, the third of a four-part series on potential blockchain applications, covers the potential of blockchains to change the status quo of identity authentication systems, privacy protection, transaction monitoring, ownership rights, and data security. The paper also posits that, as personal data becomes more and more valuable, that we should move towards a “New Deal on Data” which provides individuals data protection–through blockchain technology– and the option to contribute their data to aggregates that work towards the common good. In order to achieve this New Deal on Data, robust regulatory standards and financial incentives must be provided to entice individuals to share their data to benefit society.

Paraguay’s transparency alchemists

Curated on October 5, 2017May 29, 2019 by Stefaan Verhulst

Story by the Open Contracting Partnership: “….The “Cocido de oro” scandal is seen as part of a well-organized and well-informed youth movement that has sprung up in Paraguay in recent years. An equally dramatic controversyinvolving alleged corruption and unfair staff appointments at one of the country’s top public universities led to the resignation of the Chancellor and other senior staff in September 2015. Mostly high school and university students, they are no longer willing to tolerate the waste and corruption in public spending — a hangover from 35 years of authoritarian rule. They expect their government to be more open and accountable, and public decision-making processes to be more inclusive and democratic.

Thanks to government initiatives that have sought to give citizens greater access to information about public institutions, these students, along with investigative journalists and other civil society groups, are starting to engage actively in civic affairs. And they are data-savvy, basing recommendations on empirical evidence about government policies and processes, how they are implemented, and whether they are working.

Leading the pack is the country’s public procurement office, which runs a portal that ranks among the most open government data sources in the world. Together with information about budgets, public bodies’ payrolls, and other government data, this is helping Paraguayans to tackle some of the biggest long-standing problems faced by the government, like graft, overpricing, nepotism and influence-peddling….

The government recognizes there’s still a long way to go in their quest to open up public data. Few institutions have opened their databases or publish their data on an open data portal, and use of the data that has been published is still limited, according to a report on the country’s third OGP Action Plan. Priority data sets aren’t accessible in ways that meet the needs of civil society, the report adds.

And yet, the tremors of a tectonic shift in transparency and accountability in Paraguay are already being felt. In a short time, armed with access to information, citizens have started engaging with how public money is and should be spent.

The government is now doubling down on its strategy of fostering public participation, using cutting-edge technology to increase citizens’ access to data about their state institutions. Health, education, and municipal-level government, and procurement spending across these areas are being prioritized….(More).

How We Can Stop Earthquakes From Killing People Before They Even Hit

Curated on October 5, 2017August 3, 2018 by Stefaan Verhulst

Justin Worland in Time Magazine: “…Out of that realization came a plan to reshape disaster management using big data. Just a few months later, Wani worked with two fellow Stanford students to create a platform to predict the toll of natural disasters. The concept is simple but also revolutionary. The One Concern software pulls geological and structural data from a variety of public and private sources and uses machine learning to predict the impact of an earthquake down to individual city blocks and buildings. Real-time information input during an earthquake improves how the system responds. And earthquakes represent just the start for the company, which plans to launch a similar program for floods and eventually other natural disasters….

Previous software might identify a general area where responders could expect damage, but it would appear as a “big red blob” that wasn’t helpful when deciding exactly where to send resources, Dayton says. The technology also integrates information from many sources and makes it easy to parse in an emergency situation when every moment matters. The instant damage evaluations mean fast and actionable information, so first responders can prioritize search and rescue in areas most likely to be worst-hit, rather than responding to 911 calls in the order they are received.

One Concern is not the only company that sees an opportunity to use data to rethink disaster response. The mapping company Esri has built rapid-response software that shows expected damage from disasters like earthquakes, wildfires and hurricanes. And the U.S. government has invested in programs to use data to shape disaster response at agencies like the National Oceanic and Atmospheric Administration (NOAA)….(More)”.

Cross-sector Collaboration in Data Science for Social Good: Opportunities, Challenges, and Open Questions Raised by Working with Academic Researchers

Curated on October 5, 2017August 3, 2018 by Stefaan Verhulst

Paper by presented by Anissa Tanweer and Brittany Fiore-Gartland at the Data Science for Social Good Conference: “Recent years have seen growing support for attempts to solve complex social problems through the use of increasingly available, increasingly combinable, and increasingly computable digital data. Sometimes referred to as “data science for social good” (DSSG), these efforts are not concentrated in the hands of any one sector of society. Rather, we see DSSG emerging as an inherently multi-sector and collaborative phenomenon, with key participants hailing from governments, nonprofit organizations, technology companies, and institutions of higher education. Based on three years of participant observation in a university-hosted DSSG program, in this paper we highlight academic contributions to multi-sector DSSG collaborations, including expertise, labor, ethics, experimentation, and neutrality. After articulating both the opportunities and challenges that accompany those contributions, we pose some key open questions that demand attention from participants in DSSG programs and projects. Given the emergent nature of the DSSG phenomenon, it is our contention that how these questions come to be answered will have profound implications for the way society is organized and governed….(More)”.

A Better Way to Trace Scattered Refugees

Curated on October 5, 2017August 3, 2018 by Stefaan Verhulst

Tina Rosenberg in The New York Times: “…No one knew where his family had gone. Then an African refugee in Ottawa told him about Refunite. He went on its website and opened an account. He gave his name, phone number and place of origin, and listed family members he was searching for.

Three-quarters of a century ago, while World War II still raged, the Allies created the International Tracing Service to help the millions who had fled their homes. Its central name index grew to 50 million cards, with information on 17.5 million individuals. The index still exists — and still gets queries — today.

Index cards have become digital databases, of course. And some agencies have brought tracing into the digital age in other ways. Unicef, for example, equips staff during humanitarian emergencies with a software called Primero, which helps them get children food, medical care and other help — and register information about unaccompanied children. A parent searching for a child can register as well. An algorithm makes the connection — “like a date-finder or matchmaker,” said Robert MacTavish, who leads the Primero project.

Most United Nations agencies rely for family tracing on the International Committee of the Red Cross, the global network of national Red Cross and Red Crescent societies. Florence Anselmo, who directs the I.C.R.C.’s Central Tracing Agency, said that the I.C.R.C. and United Nations agencies can’t look in one another’s databases. That’s necessary for privacy reasons, but it’s an obstacle to family tracing.

Another problem: Online databases allow the displaced to do their own searches. But the I.C.R.C. has these for only a few emergency situations. Anselmo said that most tracing is done by the staff of national Red Cross societies, who respond to requests from other countries. But there is no global database, so people looking for loved ones must guess which countries to search.

The organization is working on developing an algorithm for matching, but for now, the search engines are human. “When we talk about tracing, it’s not only about data matching,” Anselmo said. “There’s a whole part about accompanying families: the human aspect, professionals as well as volunteers who are able to look for people — even go house to house if needed.”

This is the mom-and-pop general store model of tracing: The customer makes a request at the counter, then a shopkeeper with knowledge of her goods and a kind smile goes to the back and brings it out, throwing in a lollipop. But the world has 65 million forcibly displaced people, a record number. Personalized help to choose from limited stock is appropriate in many cases. But it cannot possibly be enough.

Refunite seeks to become the eBay of family tracing….(More)”

Let’s create a nation of social scientists

Curated on October 4, 2017August 3, 2018 by Stefaan Verhulst

Geoff Mulgan in Times Higher Education: “How might social science become more influential, more relevant and more useful in the years to come?

Recent debates about impact have largely assumed a model of social science in which a cadre of specialists, based in universities, analyse and interpret the world and then feed conclusions into an essentially passive society. But a very different view sees specialists in the academy working much more in partnership with a society that is itself skilled in social science, able to generate hypotheses, gather data, experiment and draw conclusions that might help to answer the big questions of our time, from the sources of inequality to social trust, identity to violence.

There are some powerful trends to suggest that this second view is gaining traction. The first of these is the extraordinary explosion of new ways to observe social phenomena. Every day each of us leaves behind a data trail of who we talk to, what we eat and where we go. It’s easier than ever to survey people, to spot patterns, to scrape the web or to pick up data from sensors. It’s easier than ever to gather perceptions and emotions as well as material facts and easier than ever for organisations to practice social science – whether investment organisations analysing market patterns, human resources departments using behavioural science, or local authorities using ethnography.

That deluge of data is a big enough shift on its own. However, it is also now being used to feed interpretive and predictive tools using artificial intelligence to predict who is most likely to go to hospital, to end up in prison, which relationships are most likely to end in divorce.

Governments are developing their own predictive tools, and have also become much more interested in systematic experimentation, with Finland and Canada in the lead, moving us closer to Karl Popper’s vision of “methods of trial and error, of inventing hypotheses which can be practically tested…”…

The second revolution is less visible but could be no less profound. This is the hunger of many people to be creators of knowledge, not just users; to be part of a truly collective intelligence. At the moment this shift towards mass engagement in knowledge is most visible in neighbouring fields. Digital humanities mobilise many volunteers to input data and interpret texts – for example making ancient Arabic texts machine-readable. Even more striking is the growth of citizen science – eBird had 1.5 million reports last January; some 1.5 million people in the US monitor river streams and lakes, and SETI@home has 5 million volunteers. Thousands of patients also take part in funding and shaping research on their own conditions….

We’re all familiar with the old idea that it’s better to teach a man to fish than just to give him fish. In essence these trends ask us a simple question: why not apply the same logic to social science, and why not reorient social sciences to enhance the capacity of society itself to observe, analyse and interpret?…(More)”.

Information Seeding and Knowledge Production in Online Communities: Evidence from OpenStreetMap

Curated on October 4, 2017August 3, 2018 by Stefaan Verhulst

Paper by Abhishek Nagaraj: “The wild success of a few online community-produced knowledge goods, notably Wikipedia, has obscured the fact that most attempts at forming online communities fail. A large body of work analyses motivations behind user contributions to successful, online communities but less is known, however, about early-stage interventions that might make online communities more or less successful.

This study evaluates information seeding, a popular practice to bootstrap online communities by enabling contributors to build on externally-sourced information rather that starting from scratch. I analyze the effects of information seeding on follow-on contributions using data from more than 350 million contributions made by over 577,000 contributors to OpenStreetMap, a Wikipedia-style digital map-making community that was seeded with data from the US Census. To estimate the effects of information seeding, I rely on a natural experiment in which an oversight caused about 60% of quasi-randomly chosen US counties to be seeded with a complete Census map, while the rest were seeded with less complete versions. While access to knowledge generally encourages follow-on knowledge production, I find that a higher level of information seeding significantly lowered follow-on knowledge production and contributor activity on OpenStreetMap and was also associated with lower levels of long-term quality. I argue that information seeding can crowd out contributors’ ability to develop ownership over baseline knowledge and disincentivize follow-on contributions in some circumstances. Empirical evidence supports this explanation as the mechanism through which a higher level of information seeding can stifle rather than spur knowledge production in online communities….(More)”.

Mobility Score

Curated on October 3, 2017October 24, 2018 by Stefaan Verhulst

“MobilityScore® helps you understand how easy it is to get around. It works at any location or address within the US and Canada and gives you a score ranging from 0 (no mobility choices) to 100 (excellent mobility choices).

What do we mean by mobility? Any transportation option that can help you move around your city. Transportation is changing massively as new choices emerge: ridesharing, bikesharing, carsharing. Private and on-demand mobility services have sprung up. However, tools for measuring transportation access have not kept up. That’s why we created MobilityScore as an easy-to-understand measure of transportation access.

Technical Details

MobilityScore includes all the transportation choices that can be found on TransitScreen displays, including the following services:

Public transit (subways, trains, buses, ferries, cable cars…)
Car sharing services (Zipcar, Enterprise, and one-way services like car2go)
Bike sharing services
Hailed ride sharing services (e.g. taxis, Uber, Lyft)

We have developed a common way of comparing how choices that might seem very different contribute to your mobility. For each mobility choice, we measure how long it will take you until you can start moving on it – for example, the time it takes you to leave your building, walk to a subway station, and wait for a train.

Because we’re measuring how easy it is for you to move around the city, we also consider what mobility choices look like at different times of the day and different days of the week. Mobility data is regularly collected for most services, while ridehailing (Uber/Lyft) data is based on a geographic model of arrival times.

MobilityScore’s framework is future-proof. Just like we do with TransitScreen, we will integrate future services into the calculation as they emerge (e.g. microtransit, autonomous vehicles, mobility-as-a-service)….(More)”

BBC Four to investigate how flu pandemic spreads by launching BBC Pandemic app

Curated on October 1, 2017August 3, 2018 by Stefaan Verhulst

BBC Press Release: “In a first of its kind nationwide citizen science experiment, Dr Hannah Fry is asking volunteers to download the BBC Pandemic App onto their smartphones. The free app will anonymously collect vital data on how far users travel over a 24 hour period. Users will be asked for information about the number of people they have come into contact with during this time. This data will be used to simulate the spread of a highly infectious disease to see what might happen when – not if – a real pandemic hits the UK.

By partnering with researchers at the University of Cambridge and the London School of Hygiene and Tropical Medicine, the BBC Pandemic app will identify the human networks and behaviours that spread infectious disease. The data collated from the app will help improve public health planning and outbreak control.

The results of the experiment will be revealed in a 90 minute landmark documentary, BBC Pandemic which will air in spring 2018 on BBC Four with Dr Hannah Fry and Dr Javid Abdelmoneim. The pair will chart the creation of the first ever life-saving pandemic, provide new insight into the latest pandemic science and use the data collected by the BBC Pandemic app to chart how an outbreak would spread across the UK.

In the last 100 years there have been four major flu pandemics including the Spanish Influenza outbreak of 1918 that killed up to 100 million people world wide. The Government National Risk Register estimates that infectious diseases are an even greater risk since 2015 and pandemic flu is the key concern as 50% of the population could be affected.

“Nobody knows when the next epidemic will hit, how far it will spread, or how many people will be affected. And yet, because of the power of mathematics, we can still be prepared for whatever lies ahead. What’s really important is that every single download will help improve our models so please please do take part – it will make a difference.” explains Dr Fry.

Dr Abdelmoneim says: “We shouldn’t underestimate the flu virus. It could easily be the cause of a major pandemic that could sweep around the world in a matter of weeks. I’m really excited about the BBC Pandemic app. If it can help predict the spread of a disease and be used to work out ways to slow that spread, it will be much easier for society and our healthcare system to manage”.

Cassian Harrison, Editor BBC Four says: “This is a bold and tremendously exciting project; bringing genuine insight and discovery, and taking BBC Four’s Experimental brief absolutely literally!”…(More)”