Americas

Going Digital: Restoring Trust In Government In Latin American Cities

Curated on May 13, 2017October 10, 2018 by Stefaan Verhulst

Carlos Santiso at The Rockefeller Foundation Blog: “Driven by fast-paced technological innovations, an exponential growth of smartphones, and a daily stream of big data, the “digital revolution” is changing the way we live our lives. Nowhere are the changes more sweeping than in cities. In Latin America, almost 80 percent of the population lives in cities, where massive adoption of social media is enabling new forms of digital engagement. Technology is ubiquitous in cities. The expectations of Latin American “digital citizens” have grown exponentially as a result of a rising middle class and an increasingly connected youth.

This digital transformation is recasting the relation between states and citizens. Digital citizens are asking for better services, more transparency, and meaningful participation. Their rising expectations concern the quality of the services city governments ought to provide, but also the standards of integrity, responsiveness, and fairness of the bureaucracy in their daily dealings. A recent study shows that citizens’ satisfaction with public services is not only determined by the objective quality of the service, but also their subjective expectations and how fairly they consider being treated….

New technologies and data analytics are transforming the governance of cities. Digital-intensive and data-driven innovations are changing how city governments function and deliver services, and also enabling new forms of social participation and co-creation. New technologies help improve efficiency and further transparency through new modes of open innovation. Tech-enabled and citizen-driven innovations also facilitate participation through feedback loops from citizens to local authorities to identify and resolve failures in the delivery of public services.

Three structural trends are driving the digital revolution in governments.

The digital transformation of the machinery of government. National and city governments in the region are developing digital strategies to increase connectivity, improve services, and enhance accountability. According to a recent report, 75 percent of the 23 countries surveyed have developed comprehensive digital strategies, such as Uruguay Digital, Colombia’s Vive Digital or Mexico’s Agenda Digital, that include legally recognized digital identification mechanisms. “Smart cities” are intensifying the use of modern technologies and improve the interoperability of government systems, the backbone of government, to ensure that public services are inter-connected and thus avoid having citizens provide the same information to different entities. An important driver of this transformation is citizens’ demands for greater transparency and accountability in the delivery of public services. Sixteen countries in the region have developed open government strategies, and cities such as Buenos Aires in Argentina, La Libertad in Peru, and Sao Paolo in Brazil have also committed to opening up government to public scrutiny and new forms of social participation. This second wave of active transparency reforms follows a first, more passive wave that focused on facilitating access to information.

The digital transformation of the interface with citizens. Sixty percent of the countries surveyed by the aforementioned report have established integrated service portals through which citizens can access online public services. Online portals allow for a single point of access to public services. Cities, such as Bogotá and Rio de Janeiro, are developing their own online service platforms to access municipal services. These innovations improve access to public services and contribute to simplifying bureaucratic processes and cutting red-tape, as a recent study shows. Governments are resorting to crowdsourcing solutions, open intelligence initiatives, and digital apps to encourage active citizen participation in the improvement of public services and the prevention of corruption. Colombia’s Transparency Secretariat has developed an app that allows citizens to report “white elephants” — incomplete or overbilled public works. By the end of 2015, it identified 83 such white elephants, mainly in the capital Bogotá, for a total value of almost $500 million, which led to the initiation of criminal proceedings by law enforcement authorities. While many of these initiatives emerge from civic initiatives, local governments are increasingly encouraging them and adopting their own open innovation models to rethink public services.

The gradual mainstreaming of social innovation in local government. Governments are increasingly resorting to public innovation labs to tackle difficult problems for citizens and businesses. Governments innovation labs are helping address “wicked problems” by combining design thinking, crowdsourcing techniques, and data analytics tools. Chile, Colombia, Mexico, Brazil, and Uruguay, have developed such social innovation labs within government structures. As a recent report notes, these mechanisms come in different forms and shapes. Large cities, such as Buenos Aires, Mexico City, Quito, Rio de Janeiro, and Montevideo, are at the forefront of testing such laboratory mechanisms and institutionalizing tech-driven and citizen-centered approaches through innovation labs. For example, in 2013, Mexico City created its Laboratorio para la Ciudad, as a hub for civic innovation and urban creativity, relying on small-case experiments and interventions to improve specific government services and make local government more transparent, responsive, and receptive. It spearheaded an open government law for the city that encourages residents to participate in the design of public policies and requires city agencies to consider those suggestions…..(More)”.

Why big-data analysis of police activity is inherently biased

Curated on May 11, 2017May 29, 2019 by Stefaan Verhulst

William Isaac and Andi Dixon in The Conversation: “In early 2017, Chicago Mayor Rahm Emanuel announced a new initiative in the city’s ongoing battle with violent crime. The most common solutions to this sort of problem involve hiring more police officers or working more closely with community members. But Emanuel declared that the Chicago Police Department would expand its use of software, enabling what is called “predictive policing,” particularly in neighborhoods on the city’s south side.

The Chicago police will use data and computer analysis to identify neighborhoods that are more likely to experience violent crime, assigning additional police patrols in those areas. In addition, the software will identify individual people who are expected to become – but have yet to be – victims or perpetrators of violent crimes. Officers may even be assigned to visit those people to warn them against committing a violent crime.

Any attempt to curb the alarming rate of homicides in Chicago is laudable. But the city’s new effort seems to ignore evidence, including recent research from members of our policing study team at the Human Rights Data Analysis Group, that predictive policing tools reinforce, rather than reimagine, existing police practices. Their expanded use could lead to further targeting of communities or people of color.

Working with available data

At its core, any predictive model or algorithm is a combination of data and a statistical process that seeks to identify patterns in the numbers. This can include looking at police data in hopes of learning about crime trends or recidivism. But a useful outcome depends not only on good mathematical analysis: It also needs good data. That’s where predictive policing often falls short.

Machine-learning algorithms learn to make predictions by analyzing patterns in an initial training data set and then look for similar patterns in new data as they come in. If they learn the wrong signals from the data, the subsequent analysis will be lacking.

This happened with a Google initiative called “Flu Trends,” which was launched in 2008 in hopes of using information about people’s online searches to spot disease outbreaks. Google’s systems would monitor users’ searches and identify locations where many people were researching various flu symptoms. In those places, the program would alert public health authorities that more people were about to come down with the flu.

But the project failed to account for the potential for periodic changes in Google’s own search algorithm. In an early 2012 update, Google modified its search tool to suggest a diagnosis when users searched for terms like “cough” or “fever.” On its own, this change increased the number of searches for flu-related terms. But Google Flu Trends interpreted the data as predicting a flu outbreak twice as big as federal public health officials expected and far larger than what actually happened.

Criminal justice data are biased

The failure of the Google Flu Trends system was a result of one kind of flawed data – information biased by factors other than what was being measured. It’s much harder to identify bias in criminal justice prediction models. In part, this is because police data aren’t collected uniformly, and in part it’s because what data police track reflect longstanding institutional biases along income, race and gender lines….(More)”.

Scientists crowdsource autism data to learn where resource gaps exist

Curated on May 9, 2017August 3, 2018 by Stefaan Verhulst

SCOPE: “How common is autism? Since 2000, the U.S. Centers for Disease Control and Prevention has revised its estimate several times, with the numbers ticking steadily upward. But the most recent figure of 1 in 68 kids affected is based on data from only 11 states. It gives no indication of where people with autism live around the country nor whether their communities have the resources to treat them.
That’s a knowledge gap Stanford biomedical data scientist Dennis Wall, PhD, wants to fill — not just in the United States but also around the world. A new paper, published online in JMIR Public Health & Surveillance, explains how Wall and his team created GapMap, an interactive website designed to crowdsource the missing autism data. They’re now inviting people and families affected by autism to contribute to the database….
The pilot phase of the research, which is described in the new paper, estimated that the average distance from an individual in the U.S. to the nearest autism diagnostic center is 50 miles, while those with an autism diagnosis live an average of 20 miles from the nearest diagnostic center. The researchers think this may reflect lower rates of diagnosis among people in rural areas….Data submitted to GapMap will be stored in a secure, HIPAA-compliant database. In addition to showing where more autism treatment resources are needed, the researchers hope the project will help build communities of families affected by autism and will inform them of treatment options nearby. Families will also have the option of participating in future autism research, and the scientists plan to add more features, including the locations of environmental factors such as local pollution, to understand if they contribute to autism…(More)”

Artificial intelligence prevails at predicting Supreme Court decisions

Curated on May 9, 2017August 20, 2018 by Stefaan Verhulst

Matthew Hutson at Science: “See you in the Supreme Court!” President Donald Trump tweeted last week, responding to lower court holds on his national security policies. But is taking cases all the way to the highest court in the land a good idea? Artificial intelligence may soon have the answer. A new study shows that computers can do a better job than legal scholars at predicting Supreme Court decisions, even with less information.

Several other studies have guessed at justices’ behavior with algorithms. A 2011 project, for example, used the votes of any eight justices from 1953 to 2004 to predict the vote of the ninth in those same cases, with 83% accuracy. A 2004 paper tried seeing into the future, by using decisions from the nine justices who’d been on the court since 1994 to predict the outcomes of cases in the 2002 term. That method had an accuracy of 75%.

The new study draws on a much richer set of data to predict the behavior of any set of justices at any time. Researchers used the Supreme Court Database, which contains information on cases dating back to 1791, to build a general algorithm for predicting any justice’s vote at any time. They drew on 16 features of each vote, including the justice, the term, the issue, and the court of origin. Researchers also added other factors, such as whether oral arguments were heard….

From 1816 until 2015, the algorithm correctly predicted 70.2% of the court’s 28,000 decisions and 71.9% of the justices’ 240,000 votes, the authors report in PLOS ONE. That bests the popular betting strategy of “always guess reverse,” which has been the case in 63% of Supreme Court cases over the last 35 terms. It’s also better than another strategy that uses rulings from the previous 10 years to automatically go with a “reverse” or an “affirm” prediction. Even knowledgeable legal experts are only about 66% accurate at predicting cases, the 2004 study found. “Every time we’ve kept score, it hasn’t been a terribly pretty picture for humans,” says the study’s lead author, Daniel Katz, a law professor at Illinois Institute of Technology in Chicago…..Outside the lab, bankers and lawyers might put the new algorithm to practical use. Investors could bet on companies that might benefit from a likely ruling. And appellants could decide whether to take a case to the Supreme Court based on their chances of winning. “The lawyers who typically argue these cases are not exactly bargain basement priced,” Katz says….(More)”.

NYC’s New Tech to Track Every Homeless Person in the City

Curated on May 8, 2017August 3, 2018 by Stefaan Verhulst

Wired: “New York is facing a crisis. The city that never sleeps has become the city with the most people who have no home to sleep in. As rising rents outpace income growth across the five boroughs, some 62,000 people, nearly 40 percent of them children, live in homeless shelters—rates the city hasn’t seen since the Great Depression.

As New York City Mayor Bill de Blasio faces reelection in November, his reputation and electoral prospects depend in part on his ability to reverse this troubling trend. In the mayor’s estimation, combatting homelessness effectively will require opening 90 new shelters across the city and expanding the number of outreach workers who canvass the streets every day offering aid and housing. The effort will also require having the technology in place to ensure that work happens as efficiently as possible. To that end, the city is rolling out a new tool, StreetSmart, aims to give city agencies and non-profit groups a comprehensive view of all of the data being collected on New York’s homeless on a daily basis.

Think of StreetSmart as a customer relationship management system for the homeless. Every day in New York, some 400 outreach workers walk the streets checking in on homeless people and collecting information about their health, income, demographics, and history in the shelter system, among other data points. The workers get to know this vulnerable population and build trust in the hope of one day placing them in some type of housing.

Traditionally, outreach workers have entered information about every encounter into a database, keeping running case files. But those databases never talked to each other. One outreach worker in the Bronx might never know she was talking to the same person who’d checked into a Brooklyn shelter a week prior. More importantly, the worker might never know why that person left. What’s more, systems used by city agencies and non-profits seldom overlapped, complicating efforts to keep track of individuals….

The big promise of StreetSmart extends beyond its ability to help outreach workers in the moment. The aggregation of all this information could also help the city proactively design fixes to problems it wouldn’t have otherwise seen. The tool has a map feature that shows where encampments are popping up and where outreach workers are having the most interactions. It can also be used to assess how effective different housing facilities are at keeping people off the streets….(More)”.

Algorithmic accountability

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

Megan Rose Dickey at TechCrunch: “When Netflix recommends you watch “Grace and Frankie” after you’ve finished “Love,” an algorithm decided that would be the next logical thing for you to watch. And when Google shows you one search result ahead of another, an algorithm made a decision that one page was more important than the other. Oh, and when a photo app decides you’d look better with lighter skin, a seriously biased algorithm that a real person developed made that call.

Algorithms are sets of rules that computers follow in order to solve problems and make decisions about a particular course of action. Whether it’s the type of information we receive, the information people see about us, the jobs we get hired to do, the credit cards we get approved for, and, down the road, the driverless cars that either see us or don’t see us, algorithms are increasingly becoming a big part of our lives.

But there is an inherent problem with algorithms that begins at the most base level and persists throughout its adaption: human bias that is baked into these machine-based decision-makers.

You may remember that time when Uber’s self-driving car ran a red light in San Francisco, or when Google’s photo app labeled images of black people as gorillas. The Massachusetts Registry of Motor Vehicles’ facial-recognition algorithm mistakenly tagged someone as a criminal and revoked their driver’s license. And Microsoft’s bot Tay went rogue and decided to become a white supremacist. Those were algorithms at their worst. They have also recently been thrust into the spotlight with the troubles around fake news stories surfacing in Google search results and on Facebook.

But algorithms going rogue have much greater implications; they can result in life-altering consequences for unsuspecting people. Think about how scary it could be with algorithmically biased self-driving cars, drones and other sorts of automated vehicles. Consider robots that are algorithmically biased against black people or don’t properly recognize people who are not cisgender white people, and then make a decision on the basis that the person is not human.

Another important element to consider is the role algorithm’s play in determining what we see in the world, as well as how people see us. Think driverless cars “driven” by algorithms mowing down black people because they don’t recognize black people as human. Or algorithmic software that predicts future criminals, which just so happens to be biased against black people.

A variety of issues can arise as a result of bad or erroneous data, good but biased data because there’s not enough of it, or an inflexible model that can’t account for different scenarios.

The dilemma is figuring out what to do about these problematic algorithmic outcomes. Many researchers and academics are actively exploring how to increase algorithmic accountability. What would it mean if tech companies provided their code in order to make these algorithmic decisions more transparent? Furthermore, what would happen if some type of government board would be in charge of reviewing them?…(More)”.

DIY gun control: The people taking matters into their own hands

Curated on May 2, 2017May 29, 2019 by Stefaan Verhulst

Carrie Arnold at New Scientist: “Since the start of the year, there have been 105 mass shootings in the US, including a murder-suicide shooting at a school in San Bernardino, California, and the murder video recently posted on Facebook.

Legislators have always struggled to address this problem. But in the first 100 days of Donald Trump’s administration, new gun legislation has only expanded, not restricted gun rights. In short order, lawmakers made it easier for certain people with mental illness to buy guns, and pushed to expand the locations where people can carry firearms.

Over the past few years, however, gun owners and sellers have started taking matters into their own hands and have come up with creative solutions to reduce the threat from guns.

From working with public health organisations so gun sellers can recognise the signs of depression in a prospective buyer to developing biometric gun locks, citizen scientists are cobbling together measures they hope will stave off the worst aspects of US gun culture.

The Federation of American Scientists estimates that 320 million firearms circulate in the US – about enough for every man, woman and child. According to the independent policy group Gun Violence Archive, there were 385 mass shootings in 2016, and it looks as if the numbers for 2017 will not differ wildly.

In the absence of regulations against guns, individual gun sellers and owners are trying to help”

Although the number of these incidents is alarming, it is dwarfed by the amount of suicides, which account for more than half of all firearms deaths (see graph, right). And last year, a report from the Associated Press and the USA Today Network showed that accidental shootings kill almost twice as many children as is shown in US government data.

In just one week in 2009, New Hampshire gun shop owner Ralph Demicco sold three guns that were ultimately used by their new owners to end their own lives. Demicco’s horror and dismay that he had inadvertently contributed to their deaths led him to start what has become known as the Gun Shop Project.

The project uses insights from the study of suicide to teach gun sellers to recognise signs of suicidal intent in buyers, and know when to avoid selling a gun. To do this, Demicco teamed up with Catherine Barber, an epidemiologist at the Harvard T. H. Chan School of Public Health.

Part of what the project does is challenge myths. With suicide, the biggest is that people plan suicides over a long period. But empirical evidence shows that people usually act in a moment of brief but extreme emotion. One study has found that nearly half of people who attempted suicide contemplated their attempt for less than 10 minutes. In the time it takes to find another method, a suicidal crisis often passes, so even a small delay in obtaining a gun could make a difference….Another myth that Demicco and Barber are seeking to dispel is that if you take away someone’s gun, they’ll just find another way to hurt themselves. While that’s sometimes true, Barber says, alternatives are less likely to be fatal. Gun attempts result in death more than 80 per cent of the time; only 2 per cent of pill-based suicide attempts are lethal.

Within a year of its launch in 2009, half of all gun sellers in New Hampshire had hung posters about the warning signs of suicide by the cash registers in their stores. The programme has expanded to 21 states, and Barber is now analysing data to see how well it is working.

Another grass-roots project is trying to prevent children from accidentally shooting themselves. Kai Kloepfer, an undergraduate at Massachusetts Institute of Technology, has been working on a fingerprint lock to prevent anyone other than the owner using a gun. He has founded a start-up called Biofire Technologies to improve the lock’s reliability and bring it into production….

Grass-roots schemes like the Gun Shop Project have a better chance of being successful, because gun users are already buying in. But it may take years for the project to become big enough to have a significant effect on national statistics.

Regulatory changes might be needed to make any improvements stick in the long term. At the very least, new regulations shouldn’t block the gun community’s efforts at self-governance.

Change will not come quickly, regardless. Barber sees parallels between the Gun Shop Project and campaigns against drink driving in the 1980s and 90s.

“One commercial didn’t change rates of drunk driving. It was an ad on TV, a scene in a movie, repeated over and over, that ultimately had an impact,” she says….(More)

Beyond Civil Society: Activism, Participation, and Protest in Latin America

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

Book edited by Sonia E. Alvarez, Jeffrey W. Rubin, Millie Thayer, Gianpaolo Baiocchi, and Agustín Laó-Montes: “The contributors to Beyond Civil Society argue that the conventional distinction between civic and uncivic protest, and between activism in institutions and in the streets, does not accurately describe the complex interactions of forms and locations of activism characteristic of twenty-first-century Latin America. They show that most contemporary political activism in the region relies upon both confrontational collective action and civic participation at different moments. Operating within fluid, dynamic, and heterogeneous fields of contestation, activists have not been contained by governments or conventional political categories, but rather have overflowed their boundaries, opening new democratic spaces or extending existing ones in the process. These essays offer fresh insight into how the politics of activism, participation, and protest are manifest in Latin America today while providing a new conceptual language and an interpretive framework for examining issues that are critical for the future of the region and beyond. (Read the foreword by Arturo Escobar and introduction)…(More)”

Can blockchain technology help poor people around the world?

Curated on May 1, 2017October 9, 2018 by Stefaan Verhulst

Nir Kshetri at The Conversation: “…Most simply, a blockchain is an inexpensive and transparent way to record transactions….A blockchain system, though, inherently enforces rules about authentication and transaction security. That makes it safe and affordable for a person to store any amount of money securely and confidently. While that’s still in the future, blockchain-based systems are already helping people in the developing world in very real ways.

Sending money internationally

In 2016, emigrants working abroad sent an estimated US$442 billion to their families in their home countries. This global flow of cash is a significant factor in the financial well-being of families and societies in developing nations. But the process of sending money can be extremely expensive….Hong Kong’s blockchain-enabled Bitspark has transaction costs so low it charges a flat HK$15 for remittances of less than HK$1,200 (about $2 in U.S. currency for transactions less than $150) and 1 percent for larger amounts. Using the secure digital connections of a blockchain system lets the company bypass existing banking networks and traditional remittance systems.

Similar services helping people send money to the Philippines, Ghana, Zimbabwe, Uganda, Sierra Leone and Rwanda also charge a fraction of the current banking rates.

Insurance

Most people in the developing world lack health and life insurance, primarily because it’s so expensive compared to income. Some of that is because of high administrative costs: For every dollar of insurance premium collected, administrative costs amounted to $0.28 in Brazil, $0.54 in Costa Rica, $0.47 in Mexico and $1.80 in the Philippines. And many people who live on less than a dollar a day have neither the ability to afford any insurance, nor any company offering them services….Consuelo is a blockchain-based microinsurance service backed by Mexican mobile payments company Saldo.mx. Customers can pay small amounts for health and life insurance, with claims verified electronically and paid quickly.

Helping small businesses

Blockchain systems can also help very small businesses, which are often short of cash and also find it expensive – if not impossible – to borrow money. For instance, after delivering medicine to hospitals, small drug retailers in China often wait up to 90 days to get paid. But to stay afloat, these companies need cash. They rely on intermediaries that pay immediately, but don’t pay in full. A $100 invoice to a hospital might be worth $90 right away – and the intermediary would collect the $100 when it was finally paid….

Humanitarian aid

Blockchain technology can also improve humanitarian assistance. Fraud, corruption, discrimination and mismanagement block some money intended to reduce poverty and improve education and health care from actually helping people.In early 2017 the U.N. World Food Program launched the first stage of what it calls “Building Block,” giving food and cash assistance to needy families in Pakistan’s Sindh province. An internet-connected smartphone authenticated and recorded payments from the U.N. agency to food vendors, ensuring the recipients got help, the merchants got paid and the agency didn’t lose track of its money.

…In the future, blockchain-based projects can help people and governments in other ways, too. As many as 1.5 billion people – 20 percent of the world’s population – don’t have any documents that can verify their identity. That limits their ability to use banks, but also can bar their way when trying to access basic human rights like voting, getting health care, going to school and traveling.

Several companies are launching blockchain-powered digital identity programs that can help create and validate individuals’ identities….(More)”