Congress Takes Blockchain 101

Curated on Posted on by Stefaan Verhulst

Mike Orcutt at MIT Technology Review: “Congressman David Schweikert is determined to enlighten his colleagues in Washington about the blockchain. The opportunities the technology creates for society are vast, he says, and right now education is key to keeping the government from “screwing it up.”

Schweikert, a Republican from Arizona, co-chairs the recently launched Congressional Blockchain Caucus. He and fellow co-chair, Democratic Representative Jared Polis of Colorado, say they created it in response to increasing interest and curiosity on Capitol Hill about blockchain technology. “Members of Congress are starting to get visits from people that are doing things with the blockchain and talking about it,” says Polis. “They are interested in learning more, and we hope to provide the forum to do that.”

Blockchain technology is difficult to explain, and misconceptions among policymakers are almost inevitable. One important concept Schweikert says more people need to understand is that a blockchain is not necessarily Bitcoin, and there are plenty of applications of blockchains beyond transferring digital currency. Digital currencies, and especially Bitcoin, the most popular blockchain by far, make some policymakers and government officials wary. But focusing on currency keeps people from seeing the potential the blockchain has to reinvent how we control and manage valuable information, Schweikert argues.

A blockchain is a decentralized, online record-keeping system, or ledger, maintained by a network of computers that verify and record transactions using established cryptographic techniques. Bitcoin’s system, which is open-source, depends on people all around the world called miners. They use specialized computers to verify and record transactions, and receive Bitcoin currency in reward. Several other digital currencies work in a similar fashion.

Digital currency is not the main reason so many institutions have begun experimenting with blockchains in recent years, though. Blockchains can also be used to securely and permanently store other information besides currency transaction records. For instance, banks and other financial companies see this as a way to manage information vital to the transfer of ownership of financial assets more efficiently than they do now. Some experiments have involved the Bitcoin blockchain, some use the newer blockchain software platform called Ethereum, and others have used private or semi-private blockchains.

The government should adopt blockchain technology too, say the Congressmen. A decentralized ledger is better than a conventional database “whenever we need better consumer control of information and security” like in health records, tax returns, voting records, and identity management, says Polis. Several federal agencies and state governments are already experimenting with blockchain applications. The Department of Homeland Security, for example, is running a test to track data from its border surveillance devices in a distributed ledger….

Services for transferring money fall under the jurisdiction of several federal regulators, and face a patchwork of state licensing laws. New blockchain-based business models are challenging traditional notions of money transmission, she says, and many companies are unsure where they fit in the complicated legal landscape.

Boring has argued that financial technology companies would benefit from a regulatory safe zone, or “sandbox”—like those that are already in place in the U.K. and Singapore—where they could test products without the risk of “inadvertent regulatory violations.” We don’t need any new legislation from Congress yet, though—that could stifle innovation even more, she says. “What Congress should be doing is educating themselves on the issues.”…(More)”

Did artificial intelligence deny you credit?

Curated on Posted on by Stefaan Verhulst

 in The Conversation: “People who apply for a loan from a bank or credit card company, and are turned down, are owed an explanation of why that happened. It’s a good idea – because it can help teach people how to repair their damaged credit – and it’s a federal law, the Equal Credit Opportunity Act. Getting an answer wasn’t much of a problem in years past, when humans made those decisions. But today, as artificial intelligence systems increasingly assist or replace people making credit decisions, getting those explanations has become much more difficult.

Traditionally, a loan officer who rejected an application could tell a would-be borrower there was a problem with their income level, or employment history, or whatever the issue was. But computerized systems that use complex machine learning models are difficult to explain, even for experts.

Consumer credit decisions are just one way this problem arises. Similar concerns exist in health care, online marketing and even criminal justice. My own interest in this area began when a research group I was part of discovered gender bias in how online ads were targeted, but could not explain why it happened.

All those industries, and many others, who use machine learning to analyze processes and make decisions have a little over a year to get a lot better at explaining how their systems work. In May 2018, the new European Union General Data Protection Regulation takes effect, including a section giving people a right to get an explanation for automated decisions that affect their lives. What shape should these explanations take, and can we actually provide them?

Identifying key reasons

One way to describe why an automated decision came out the way it did is to identify the factors that were most influential in the decision. How much of a credit denial decision was because the applicant didn’t make enough money, or because he had failed to repay loans in the past?

My research group at Carnegie Mellon University, including PhD student Shayak Sen and then-postdoc Yair Zick created a way to measure the relative influence of each factor. We call it the Quantitative Input Influence.

In addition to giving better understanding of an individual decision, the measurement can also shed light on a group of decisions: Did an algorithm deny credit primarily because of financial concerns, such as how much an applicant already owes on other debts? Or was the applicant’s ZIP code more important – suggesting more basic demographics such as race might have come into play?…(More)”

Geospatial big data and cartography: research challenges and opportunities for making maps that matter

Curated on Posted on by Stefaan Verhulst
Screen Shot 2017-03-14 at 8.06.51 AMAnthony C. Robinson et al in the International Journal Of Cartography; “Geospatial big data present a new set of challenges and opportunities for cartographic researchers in technical, methodological and artistic realms. New computational and technical paradigms for cartography are accompanying the rise of geospatial big data. Additionally, the art and science of cartography needs to focus its contemporary efforts on work that connects to outside disciplines and is grounded in problems that are important to humankind and its sustainability. Following the development of position papers and a collaborative workshop to craft consensus around key topics, this article presents a new cartographic research agenda focused on making maps that matter using geospatial big data. This agenda provides both long-term challenges that require significant attention and short-term opportunities that we believe could be addressed in more concentrated studies….(More)”.

Analytics Tools Could Be the Key to Effective Message-Driven Nudging

Curated on Posted on by Stefaan Verhulst

 in Government Technology: “Appealing to the nuances of the human mind has been a feature of effective governance for as long as governance has existed, appearing prominently in the prescriptions of every great political theorist from Plato to Machiavelli. The most recent and informed iteration of this practice is nudging: leveraging insights about how humans think from behavioral science to create initiatives that encourage desirable behaviors.

Public officials nudge in many ways. Some seek to modify people’s behavior by changing the environments in which they make decisions, for instance moving vegetables to the front of a grocery store to promote healthy eating. Others try to make desirable behaviors easier, like streamlining a city website to make it simpler to sign up for a service. Still others use prompts like email reminders of a deadline to receive a free checkup to nudge people to act wisely by providing useful information.

Thus far, examples of the third type of nudging — direct messaging that prompts behavior — have been decidedly low tech. Typical initiatives have included sending behaviorally informed letters to residents who have not complied with a city code or mailing out postcard reminders to renew license plates. Governments have been attracted to these initiatives for their low cost and proven effectiveness.

While these low-tech nudges should certainly continue, cities’ recent adoption of tools that can mine and analyze data instantaneously has the potential to greatly increase the scope and effectiveness of message-driven nudging.

For one, using Internet of Things (IoT) ecosystems, cities can provide residents with real-time information so that they may make better-informed decisions. For example, cities could connect traffic sensors to messaging systems and send subscribers text messages at times of high congestion, encouraging them to take public transportation. This real-time information, paired with other nudges, could increase transit use, easing traffic and bettering the environment…
Instantaneous data-mining tools may also prove useful for nudging citizens in real time, at the moments they are most likely to partake in detrimental behavior. Tools like machine learning can analyze users’ behavior and determine if they are likely to make a suboptimal choice, like leaving the website for a city service without enrolling. Using clickstream data, the site could determine if a user is likely to leave and deliver a nudge, for example sending a message explaining that most residents enroll in the service. This strategy provides another layer of nudging, catching residents who may have been influenced by an initial nudge — like a reminder to sign up for a service or streamlined website — but may need an extra prod to follow through….(More)”

Dark Web

Curated on Posted on by Stefaan Verhulst

Kristin Finklea for the Congressional Research Service: “The layers of the Internet go far beyond the surface content that many can easily access in their daily searches. The other content is that of the Deep Web, content that has not been indexed by traditional search engines such as Google. The furthest corners of the Deep Web, segments known as the Dark Web, contain content that has been intentionally concealed. The Dark Web may be used for legitimate purposes as well as to conceal criminal or otherwise malicious activities. It is the exploitation of the Dark Web for illegal practices that has garnered the interest of officials and policymakers.

Individuals can access the Dark Web by using special software such as Tor (short for The Onion Router). Tor relies upon a network of volunteer computers to route users’ web traffic through a series of other users’ computers such that the traffic cannot be traced to the original user. Some developers have created tools—such as Tor2web—that may allow individuals access to Torhosted content without downloading and installing the Tor software, though accessing the Dark Web through these means does not anonymize activity. Once on the Dark Web, users often navigate it through directories such as the “Hidden Wiki,” which organizes sites by category, similar to Wikipedia. Individuals can also search the Dark Web with search engines, which may be broad, searching across the Deep Web, or more specific, searching for contraband like illicit drugs, guns, or counterfeit money.

While on the Dark Web, individuals may communicate through means such as secure email, web chats, or personal messaging hosted on Tor. Though tools such as Tor aim to anonymize content and activity, researchers and security experts are constantly developing means by which certain hidden services or individuals could be identified or “deanonymized.” Anonymizing services such as Tor have been used for legal and illegal activities ranging from maintaining privacy to selling illegal goods—mainly purchased with Bitcoin or other digital currencies. They may be used to circumvent censorship, access blocked content, or maintain the privacy of sensitive communications or business plans. However, a range of malicious actors, from criminals to terrorists to state-sponsored spies, can also leverage cyberspace and the Dark Web can serve as a forum for conversation, coordination, and action. It is unclear how much of the Dark Web is dedicated to serving a particular illicit market at any one time, and, because of the anonymity of services such as Tor, it is even further unclear how much traffic is actually flowing to any given site.

Just as criminals can rely upon the anonymity of the Dark Web, so too can the law enforcement, military, and intelligence communities. They may, for example, use it to conduct online surveillance and sting operations and to maintain anonymous tip lines. Anonymity in the Dark Web can be used to shield officials from identification and hacking by adversaries. It can also be used to conduct a clandestine or covert computer network operation such as taking down a website or a denial of service attack, or to intercept communications. Reportedly, officials are continuously working on expanding techniques to deanonymize activity on the Dark Web and identify malicious actors online….(More)”

Big data helps Belfort, France, allocate buses on routes according to demand

Curated on Posted on by Stefaan Verhulst

 in Digital Trends: “As modern cities smarten up, the priority for many will be transportation. Belfort, a mid-sized French industrial city of 50,000, serves as proof of concept for improved urban transportation that does not require the time and expense of covering the city with sensors and cameras.

Working with Tata Consultancy Services (TCS) and GFI Informatique, the Board of Public Transportation of Belfort overhauled bus service management of the city’s 100-plus buses. The project entailed a combination of ID cards, GPS-equipped card readers on buses, and big data analysis. The collected data was used to measure bus speed from stop to stop, passenger flow to observe when and where people got on and off, and bus route density. From start to finish, the proof of concept project took four weeks.

Using the TCS Intelligent Urban Exchange system, operations managers were able to detect when and where about 20 percent of all bus passengers boarded and got off on each city bus route. Utilizing big data and artificial intelligence the city’s urban planners were able to use that data analysis to make cost-effective adjustments including the allocation of additional buses on routes and during times of greater passenger demand. They were also able to cut back on buses for minimally used routes and stops. In addition, the system provided feedback on the effect of city construction projects on bus service….

Going forward, continued data analysis will help the city budget wisely for infrastructure changes and new equipment purchases. The goal is to put the money where the needs are greatest rather than just spending and then waiting to see if usage justified the expense. The push for smarter cities has to be not just about improved services, but also smart resource allocation — in the Belfort project, the use of big data showed how to do both….(More)”

The Crowd & the Cloud

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The Crowd & the Cloud (TV series): “Are you interested in birds, fish, the oceans or streams in your community? Are you concerned about fracking, air quality, extreme weather, asthma, Alzheimer’s disease, Zika or other epidemics? Now you can do more than read about these issues. You can be part of the solution.

Smartphones, computers and mobile technology are enabling regular citizens to become part of a 21st century way of doing science. By observing their environments, monitoring neighborhoods, collecting information about the world and the things they care about, so-called “citizen scientists” are helping professional scientists to advance knowledge while speeding up new discoveries and innovations.

The results are improving health and welfare, assisting in wildlife conservation, and giving communities the power to create needed change and help themselves.

Citizen science has amazing promise, but also raises questions about data quality and privacy. Its potential and challenges are explored in THE CROWD & THE CLOUD, a 4-part public television series premiering in April 2017. Hosted by former NASA Chief Scientist Waleed Abdalati, each episode takes viewers on a global tour of the projects and people on the front lines of this disruptive transformation in how science is done, and shows how anyone, anywhere can participate….(More)”

 

Migration tracking is a mess

Curated on Posted on by Stefaan Verhulst

Huub Dijstelbloem in Nature: “As debates over migration, refugees and freedom of movement intensify, technologies are increasingly monitoring the movements of people. Biometric passports and databases containing iris scans or fingerprints are being used to check a person’s right to travel through or stay within a territory. India, for example, is establishing biometric identification for its 1.3 billion citizens.

But technologies are spreading beyond borders. Security policies and humanitarian considerations have broadened the landscape. Drones and satellite images inform policies and direct aid to refugees. For instance, the United Nations Institute for Training and Research (UNITAR), maps refugee camps in Jordan and elsewhere with its Operational Satellite Applications Programme (UNOSAT; see www.unitar.org/unosat/map/1928).

Three areas are in need of research, in my view: the difficulties of joining up disparate monitoring systems; privacy issues and concerns over the inviolability of the human body; and ‘counter-surveillance’ deployed by non-state actors to highlight emergencies or contest claims that governments make.

Ideally, state monitoring of human mobility would be bound by ethical principles, solid legislation, periodical evaluations and the checks and balances of experts and political and public debates. In reality, it is ad hoc. Responses are arbitrary, fuelled by the crisis management of governments that have failed to anticipate global and regional migration patterns. Too often, this results in what the late sociologist Ulrich Beck called organized irresponsibility: situations of inadequacy in which it is hard to blame a single actor.

Non-governmental organizations, activists and migrant groups are using technologies to register incidents and to blame and shame states. For example, the Forensic Architecture research agency at Goldsmiths, University of London, has used satellite imagery and other evidence to reconstruct the journey of a boat that left Tripoli on 27 March 2011 with 72 passengers. A fortnight later, it returned to the Libyan coast with just 9 survivors. Although the boat had been spotted by several aircraft and vessels, no rescue operation had been mounted (go.nature.com/2mbwvxi). Whether the states involved can be held accountable is still being considered.

In the end, technologies to monitor mobility are political tools. Their aims, design, use, costs and consequences should be developed and evaluated accordingly….(More)”.

Does digital democracy improve democracy?

Curated on Posted on by Stefaan Verhulst

Thamy Pogrebinschi at Open Democracy: “The advancement of tools of information and communications technology (ICT) has the potential to impact democracy nearly as much as any other area, such as science or education. The effects of the digital world on politics and society are still difficult to measure, and the speed with which these new technological tools evolve is often faster than a scholar’s ability to assess them, or a policymaker’s capacity to make them fit into existing institutional designs.

Since their early inception, digital tools and widespread access to the internet have been changing the traditional means of participation in politics, making them more effective. Electoral processes have become more transparent and effective in several countries where the paper ballot has been substituted for electronic voting machines. Petition-signing became a widespread and powerful tool as individual citizens no longer needed to be bothered out in the streets to sign a sheet of paper, but could instead be simultaneously reached by the millions via e-mail and have their names added to virtual petition lists in seconds. Protests and demonstrations have also been immensely revitalized in the internet era. In the last few years, social networks like Facebook and WhatsApp have proved to be a driving-force behind democratic uprisings, by mobilizing the masses, invoking large gatherings, and raising awareness, as was the case of the Arab Spring.

While traditional means of political participation can become more effective by reducing the costs of participation with the use of ICT tools, one cannot yet assure that it would become less subject to distortion and manipulation. In the most recent United States’ elections, computer scientists claimed that electronic voting machines may have been hacked, altering the results in the counties that relied on them. E-petitions can also be easily manipulated, if safe identification procedures are not put in place. And in these times of post-facts and post-truths, protests and demonstrations can result from strategic partisan manipulation of social media, leading to democratic instability as has recently occurred in Brazil. Nevertheless, the distortion and manipulation of these traditional forms of participation were also present before the rise of ICT tools, and regardless, even if the latter do not solve these preceding problems, they may manage to make political processes more effective anyway.

The game-changer for democracy, however, is not the revitalization of the traditional means of political participation like elections, petition-signing and protests through digital tools. Rather, the real change on how democracy works, governments rule, and representation is delivered comes from entirely new means of e-participation, or the so-called digital democratic innovations. While the internet may boost traditional forms of political participation by increasing the quantity of citizens engaged, democratic innovations that rely on ICT tools may change the very quality of participation, thus in the long-run changing the nature of democracy and its institutions….(More)”

Bit By Bit: Social Research in the Digital Age

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Open Review of Book by Matthew J. Salganik: “In the summer of 2009, mobile phones were ringing all across Rwanda. In addition to the millions of calls between family, friends, and business associates, about 1,000 Rwandans received a call from Joshua Blumenstock and his colleagues. The researchers were studying wealth and poverty by conducting a survey of people who had been randomly sampled from a database of 1.5 million customers from Rwanda’s largest mobile phone provider. Blumenstock and colleagues asked the participants if they wanted to participate in a survey, explained the nature of the research to them, and then asked a series of questions about their demographic, social, and economic characteristics.

Everything I have said up until now makes this sound like a traditional social science survey. But, what comes next is not traditional, at least not yet. They used the survey data to train a machine learning model to predict someone’s wealth from their call data, and then they used this model to estimate the wealth of all 1.5 million customers. Next, they estimated the place of residence of all 1.5 million customers by using the geographic information embedded in the call logs. Putting these two estimates together—the estimated wealth and the estimated place of residence—Blumenstock and colleagues were able to produce high-resolution estimates of the geographic distribution of wealth across Rwanda. In particular, they could produce an estimated wealth for each of Rwanda’s 2,148 cells, the smallest administrative unit in the country.

It was impossible to validate these estimates because no one had ever produced estimates for such small geographic areas in Rwanda. But, when Blumenstock and colleagues aggregated their estimates to Rwanda’s 30 districts, they found that their estimates were similar to estimates from the Demographic and Health Survey, the gold standard of surveys in developing countries. Although these two approaches produced similar estimates in this case, the approach of Blumenstock and colleagues was about 10 times faster and 50 times cheaper than the traditional Demographic and Health Surveys. These dramatically faster and lower cost estimates create new possibilities for researchers, governments, and companies (Blumenstock, Cadamuro, and On 2015).

In addition to developing a new methodology, this study is kind of like a Rorschach inkblot test; what people see depends on their background. Many social scientists see a new measurement tool that can be used to test theories about economic development. Many data scientists see a cool new machine learning problem. Many business people see a powerful approach for unlocking value in the digital trace data that they have already collected. Many privacy advocates see a scary reminder that we live in a time of mass surveillance. Many policy makers see a way that new technology can help create a better world. In fact, this study is all of those things, and that is why it is a window into the future of social research….(More)”