Can Data Help Brazil Take a Bite Out of Crime?

Curated on Posted on by Stefaan Verhulst

Joe Leahy at ZY See Beyond: “When Argentine entrepreneur Federico Vega two years ago launched a startup offering Uberlike services for Brazil’s freight industry, the sector was on the cusp of a wave of cargo theft.

Across Brazil, but especially in Rio de Janeiro, crime has soared, with armed gangs robbing one truck every 50 minutes in Rio last year.

But while the authorities have reacted with force to the crime wave, Vega turned to software engineers at his CargoX startup. By studying a range of industry and security data, CargoX developed software that identifies risks and helps drivers avoid crime hot spots, or if a robbery does happen, alerts the company in real time.CargoX says that in Brazil, 0.1 percent by value of all cargo transported by trucks is stolen. “We are about 50 percent lower than that, but we still have tons of work to do,” says São Paulo–based Vega.

CargoX is one of a growing number of Brazilian technology startups that are seeking digital solutions to the problem of endemic crime in Latin America’s largest country.

Having started from zero two years ago, CargoX today has signed up more than 5,000 truckers. The company scans data from all sources to screen its motorists and study past crimes to see what routes, times, neighborhoods and types of cargo represent the highest risk.

Certain gas stations that might, for instance, be known for prostitution are avoided because of their criminal associations. Daytime delivery is better than night. Drivers are tracked by GPS and must stay inside “geofences” — known safe routes. Foraying outside these alerts the system.

Vega says the key is to learn from the data. “Everyone says it’s good to learn from your mistakes, but it’s even better to learn from other people’s mistakes.”

The use of big data to anticipate crime is at the center of the approach of another tech-savvy entrepreneur, Pedro Moura Costa, the founder of BVRio Institute, an organization that seeks market solutions to environmental issues.

Organized crime is targeting everything from highway robbery to the illegal plunder of tropical hardwoods in the Amazon while online crime such as credit card fraud is also rampant, analysts say….(More)”.

How the government will operate in 2030

Curated on Posted on by Stefaan Verhulst

Darrell West at the Hill: “Imagine it is 2030 and you are a U.S. government employee working from home. With the assistance of the latest technology, you participate in video calls with clients and colleagues, augment your job activities through artificial intelligence and a personal digital assistant, work through collaboration software, and regularly get rated on a one-to-five scale by clients regarding your helpfulness, follow-through, and task completion.

How did you — and the government — get here? The sharing economy that unfolded in 2018 has revolutionized the public-sector workforce. The days when federal employees were subject to a centrally directed Office of Personnel and Management that oversaw permanent, full-time workers sitting in downtown office buildings are long gone. In their place is a remote workforce staffed by a mix of short- and long-term employees. This has dramatically improved worker productivity and satisfaction.

In the new digital world that has emerged, the goal is to use technology to make employees accountable. Gone are 20- or 30-year careers in the federal bureaucracy. Political leaders have always preached the virtue of running government like a business, and the success of Uber, Airbnb, and WeWork has persuaded them to focus on accountability and performance.

Companies such as Facebook demonstrated they could run large and complex organizations with less than 20,000 employees, and the federal government followed suit in the late 2020s. Now, workers deploy the latest tools of artificial intelligence, virtual reality, data analytics, robots, driverless cars, and digital assistants to improve the government. Unlike the widespread mistrust and cynicism that had poisoned attitudes in the decades before, the general public now sees government as a force for achieving positive results.

Many parts of the federal government are decentralized and mid-level employees are given greater authority to make decisions — but are subject to digital ratings that keep them accountable for their performance. The U.S. government borrowed this technique from China, where airport authorities in 2018 installed digital devices that allowed visitors to rate the performance of individual passport officers after every encounter. The reams of data have enabled Chinese authorities to fire poor performers and make sure foreign visitors see a friendly and competent face at the Beijing International Airport.

Alexa-like devices are given to all federal employees. The devices are used to keep track of leave time, file reimbursement requests, request time off, and complete a range of routine tasks that used to take employees hours. Through voice-activated commands, they navigate these mundane tasks quickly and efficiently. No one can believe the mountains of paperwork required just a decade ago….(More)”.

Data for Development: What’s next? Concepts, trends and recommendations

Curated on Posted on by Stefaan Verhulst

Report by the WebFoundation: “The exponential growth of data provides powerful new ways for governments and companies to understand and respond to challenges and opportunities. This report, Data for Development: What’s next, investigates how organisations working in international development can leverage the growing quantity and variety of data to improve their investments and projects so that they better meet people’s needs.

Investigating the state of data for development and identifying emerging data trends, the study provides recommendations to support German development cooperation actors seeking to integrate data strategies and investments in their work. These insights can guide any organisation seeking to use data to enhance their development work.

The research considers four types of data: (1) big data, (2) open data, (3) citizen-generated data and (4) real-time data, and examines how they are currently being used in development-related policy-making and how they might lead to better development outcomes….(More)”.

Cambridge Analytica scandal: legitimate researchers using Facebook data could be collateral damage

Curated on Posted on by Stefaan Verhulst

 at The Conversation: “The scandal that has erupted around Cambridge Analytica’s alleged harvesting of 50m Facebook profiles assembled from data provided by a UK-based academic and his company is a worrying development for legitimate researchers.

Political data analytics company Cambridge Analytica – which is affiliated with Strategic Communication Laboratories (SCL) – reportedly used Facebook data, after it was handed over by Aleksandr Kogan, a lecturer at the University of Cambridge’s department of psychology.

Kogan, through his company Global Science Research (GSR) – separate from his university work – gleaned the data from a personality test app named “thisisyourdigitallife”. Roughly 270,000 US-based Facebook users voluntarily responded to the test in 2014. But the app also collected data on those participants’ Facebook friends without their consent.

This was possible due to Facebook rules at the time that allowed third-party apps to collect data about a Facebook user’s friends. The Mark Zuckerberg-run company has since changed its policy to prevent such access to developers….

Social media data is a rich source of information for many areas of research in psychology, technology, business and humanities. Some recent examples include using Facebook to predict riots, comparing the use of Facebook with body image concern in adolescent girls and investigating whether Facebook can lower levels of stress responses, with research suggesting that it may enhance and undermine psycho-social constructs related to well-being.

It is right to believe that researchers and their employers value research integrity. But instances where trust has been betrayed by an academic – even if it’s the case that data used for university research purposes wasn’t caught in the crossfire – will have a negative impact on whether participants will continue to trust researchers. It also has implications for research governance and for companies to share data with researchers in the first place.

Universities, research organisations and funders govern the integrity of research with clear and strict ethics proceduresdesigned to protect participants in studies, such as where social media data is used. The harvesting of data without permission from users is considered an unethical activity under commonly understood research standards.

The fallout from the Cambridge Analytica controversy is potentially huge for researchers who rely on social networks for their studies, where data is routinely shared with them for research purposes. Tech companies could become more reluctant to share data with researchers. Facebook is already extremely protective of its data – the worry is that it could become doubly difficult for researchers to legitimately access this information in light of what has happened with Cambridge Analytica….(More)”.

Coastal research increasingly depends on citizen scientists

Curated on Posted on by Stefaan Verhulst

Brenna Visser at CS Monitor: “…This monthly ritual is a part of the COASST survey, a program that relies on data taken by volunteers to study large-scale patterns in seabird populations on the West Coast. The Haystack Rock Awareness Program conducts similar surveys for sea stars and marine debris throughout the year.

Surveys like these play a small part in a growing trend in the science community to use citizen scientists as a way to gather massive amounts of data. Over the weekend, marine scientists and conservationists came to Cannon Beach for an annual Coast Conference, a region wide event to discuss coastal science and stewardship.

Whether the presentation was about ocean debris, marine mammals, seabirds, or ocean jellies, many relied on the data collection work of volunteers throughout the state. A database for citizen science programs called Citsci.org, which recorded only a few dozen groups 10 years ago, now has more than 500 groups registered across the country, with new ones registering every day….

Part of the rise has to do with technology, she said. Apps that help identify species and allow unprecedented access to information have driven interest up and removed barriers that would have otherwise made it harder to collect data without formal training. Another is the science community slowly coming around to accept citizen science.

“I think there’s a lot of reticence in the science community to use citizen science. There’s some doubt the data collected is of the precision or accuracy that is needed to document phenomena,” Parrish said. “But as it grows, the more standardized it becomes. What we’re seeing right now is a lot of discussion in citizen science programs asking what they need to do to get to that level.”…While a general decline in federal funding for scientific research could play a factor in the science community’s acceptance of using volunteer-collected data, Parrish said, regardless of funding, there are some projects only citizen scientists can accomplish….(More)”

How Incorporating Behavioral Science into Cash Transfer Programs Is Changing Lives

Curated on Posted on by Stefaan Verhulst

Josh Martin and Laura Rawlings at Next Billion: “…Today, a new generation of cash transfer programs – currently being piloted in several countries in Africa – uses behavioral insights to help beneficiaries decide how to spend their cash and follow through on those plans. But the circumstances under which they receive the funds—like how long they have to wait on payment day or how close the local market is to the payment site—impact whether they put that intention into action. Other often-overlooked program design factors, such as the frequency of payments or how the purpose of the cash is framed, can disproportionately affect how people spend (or save) their money. Insights from behavioral science show that people act in predictable ways—and we can use that knowledge to design cash transfer programs that support people’s goals and continue to set them up for success.

For example, in our work, we have found that the way payments are made often caters more to administrators’ convenience than beneficiaries’ needs. But some innovators are already changing the timing, location and frequency of payments to suit recipients. For instance, GiveDirectly, a nonprofit that provides unconditional cash transfers, is experimenting with allowing beneficiaries in Kenya to choose when they’d prefer their payments to occur. This is important because getting money at the wrong time can actually increase stress. When cash arrives infrequently, it forces recipients to stretch funds until the next payment. But if it is transferred too often, recipients must save slowly over time, pulling their attention away from other critical tasks. While it isn’t always possible to pay everyone according to their ideal schedule, even offering some payment flexibility may help recipients achieve their goals more quickly.

A simple prompt for beneficiaries to consider how they’d like to use their money right before receiving it can also support their financial goals. Other tactics include reminders to follow through on plans, systems to provide feedback to people on their savings progress, and wallets to help them physically separate (and thus mentally separate) what they want to spend routinely from what they want to set aside for the future. Many inexpensive options exist that are fairly easy to put in place.

To bring more of these solutions to cash transfer programs, ideas42 and the World Bank, with financial support from the Global Innovation Fund, are launching a new initiative, Behavioral Design for Cash Transfer Programs. Working with government partners to identify the best options for incorporating behavioral designs in cash transfer programs across several African nations is a critical next step in improving this anti-poverty tool. We can then work to make behavioral science an automatic part of any social protection program that features a cash transfer….(More)”.

The Promise of Community Citizen Science

Curated on Posted on by Stefaan Verhulst

Report by Ramya Chari, Luke J. Matthews, Marjory S. Blumenthal, Amanda F. Edelman, and Therese Jones: “Citizen science is public participation in research and scientific endeavors. Citizens volunteer as data collectors in science projects; collaborate with scientific experts on research design; and actively lead and carry out research, exerting a high degree of control and ownership over scientific activities. The last type — what we refer to as community citizen science — tends to involve action-oriented research to support interventional activities or policy change. This type of citizen science can be of particular importance to those working at the nexus of science and decisionmaking.

The authors examine the transformative potential of community citizen science for communities, science, and decisionmaking. The Perspective is based on the authors’ experiences working in collaboration with community groups, extensive readings of the scientific literature, and numerous interviews with leading scholars and practitioners in the fields of citizen science and participatory research. It first discusses models of citizen science in general, including community citizen science, and presents a brief history of its rise. It then looks at possible factors motivating the development of community citizen science, drawing from an exploration of the relationships among citizens, science, and decisionmaking. The final section examines areas in which community citizen science may exhibit promise in terms of outcomes and impacts, discusses concerns that may hinder its overall potential, and assesses the roles different stakeholders may play to continue to develop community citizen science into a positive force for science and society.

Key Findings

At Its Core, Citizen Science Is Public Participation in Research and Scientific Endeavors

  • Citizens volunteer as data collectors in science projects, collaborate with scientific experts on research design, and actively lead and carry out research.
  • It is part of a long tradition of rebirth of inventors, scientists, do-it-yourselfers, and makers at all levels of expertise.
  • Instead of working alone, today’s community citizen scientists take advantage of new technologies for networking and coordination to work collaboratively; learn from each other; and share knowledge, insights, and findings.

The Democratization of Science and the Increasingly Distributed Nature of Expertise Are Not Without Concern

  • There is some tension and conflict between current standards of practice and the changes required for citizen science to achieve its promising future.
  • There is also some concern about the potential for bias, given that some efforts begin as a form of activism.

Yet the Efforts of Community Citizen Science Can Be Transformative

  • Success will require an engaged citizenry, promote more open and democratic decisionmaking processes, and generate new solutions for intractable problems.
  • If its promise holds true, the relationship between science and society will be profoundly transformed for the betterment of all…(More)”.

The Metric God That Failed

Curated on Posted on by Stefaan Verhulst
Jerry Muller in PS Long Reads: “Over the past few decades, formal institutions have increasingly been subjected to performance measurements that define success or failure according to narrow and arbitrary metrics. The outcome should have been predictable: institutions have done what they can to boost their performance metrics, often at the expense of performance itself.

…In 1986, the American management guru Tom Peters popularized the organizational theorist Mason Haire’s dictum that, “What gets measured gets done,” and with it a credo of measured performance that I call “metric fixation.” In time, the devotees of measured performance would arrive at a naive article of faith that is nonetheless appealing for its mix of optimism and scientism: “Anything that can be measured can be improved.”

In the intervening decades, this faith-based conceit has developed into a dogma about the relationship between measurement and performance. Evangelists of “disruption” and “best practices” have carried the new gospel to ever more distant shores. If you work in health care, education, policing, or the civil service, you have probably been subjected to the policies and practices wrought by metric-centrism.

There are three tenets to the metrical canon. The first holds that it is both possible and desirable to replace judgment – acquired through personal experience and talent – with numerical indicators of comparative performance based on standardized data. Second, making such metrics public and transparent ensures that institutions are held accountable. And, third, the best way to motivate people within organizations is to attach monetary or reputational rewards and penalties to their measured performance….(More)”.

Anthology on Democratic Innovation

Curated on Posted on by Stefaan Verhulst

Report by Democracy Lab: “Democratic systems are in a phase of systemic transition: from the post-war understanding of what democracy is – and how it works – towards a different, deeper democracy. In regards to the numerous challenges democracies faces, we need to question how to make democracies more resilient and to explore what the next steps towards a new form of democracy could be. It seems unlikely that today’s challenges, such as the destruction of our ecosystem or structural inequality, can be solved with the paradigms, structures and processes that helped produce them.

Democratic systems need to be able to shape an increasingly complex world and respond to the socio-economic, cultural, technological, and ecological transformation processes that societies are going through. Public discourse about the future of democracy often solely focuses on democratic reforms in order to improve existing structures and processes within the parameters of postwar democracy.

Many ideas and experiments thus aim at improving the “status quo of politics”. From citizens’ assemblies to digital tools for deliberation and participation, there is an abundance of ideas and tools that could help update our democratic systems. In his book “Realizing Democracy”, Harvard scholar Alberto Mangabeira Unger adds a new element to this “update” with his idea of radical reform: In his words, “reform is radical when it addresses and changes the basic arrangements of a society; its formative structure of its institutions and enacted beliefs; it is reform because it deals with one discrete part of this structure at a time.” According to Unger, societies must work on both the radical and incremental level of political reform. In addition to changes at policy level, societies must be willing to also reflect on what would make a difference and open up to a more fundamental perspective and self-reflection on why democracy is needed, and how its structures can be rebuild within the boundaries of the ecosystem….

The Anthology on Democratic Innovation presents a selection of the projects and ideas discussed during the Conference. It gives decision-makers, academia, journalists and civil society a glimpse into the vast array of ideas that are “already out there” in order to improve liberal democracies and make them fit for the 21st century….(More)”.

Is Distributed Ledger Technology Built for Personal Data?

Curated on Posted on by Stefaan Verhulst

Paper by Henry Chang: “Some of the appealing characteristics of distributed ledger technology (DLT), which blockchain is a type of, include guaranteed integrity, disintermediation and distributed resilience. These characteristics give rise to the possible consequences of immutability, unclear ownership, universal accessibility and trans-border storage. These consequences have the potential to contravene data protection principles of Purpose Specification, Use Limitation, Data Quality, Individual Participation and Trans-Border Data Flow. This paper endeavors to clarify the various types of DLTs, how they work, why they exhibit the depicted characteristics and the consequences. Using the universal privacy principles developed by the Organisation of Economic Cooperation and Development (OECD), this paper then describes how each of the consequence causes concerns for privacy protection and how attempts are being made to address them in the design and implementation of various applications of blockchain and DLT, and indicates where further research and best-practice developments lie….(More)”.