Country and Region: Latin America and the Caribbean
Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia, Bonaire, Bouvet Island, Brazil, British Virgin Islands, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French Part), Saint Vincent and the Grenadines, Sint Eustatius and Saba, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, United States Virgin Islands, Uruguay, Venezuela
Paper by Natalia Garbiras-Díaz and Mateo Montenegro: “ICT-enabled monitoring tools effectively encourage citizens to oversee their elections and reduce fraud
Despite many efforts by governments and international organizations to guarantee free and fair elections, in many democracies, electoral integrity continues to be threatened. Irregularities including fraud, vote buying or voter intimidation reduce political accountability, which can distort the allocation of public goods and services (Hicken 2011, Khemani 2015).
But why is it so hard to prevent and curb electoral irregularities? While traditional strategies such as the deployment of electoral observers and auditors have proven effective (Hyde 2010, Enikolopov et al. 2013, Leefers and Vicente 2019), these are difficult to scale up and involve large investments in the training, security and transportation of personnel to remote and developing areas.
In Garbiras-Díaz and Montenegro (2022), we designed and implemented a large-scale field experiment during the election period in Colombia to study an innovative and light-touch strategy that circumvents many of these costs. We examine whether citizens can effectively oversee elections through online platforms, and demonstrate that delegating monitoring to citizens can provide a cost-effective alternative to more traditional strategies. Moreover, with growing access to the internet in developing countries reducing the barriers to online monitoring, this strategy is scalable and can be particularly impactful. Our results show how citizens can be encouraged to monitor elections, and, more importantly, illustrate how this form of monitoring can prevent politicians from using electoral irregularities to undermine the integrity of elections…(More)”.
Blog by Christine Grillo: “For María Mari-Narváez, a recent decision by the Supreme Court of Puerto Rico was both a victory and a moment of reckoning. The Court granted Kilómetro Cero, a citizen-led police accountability project in Puerto Rico, full access to every use-of-force report filed by the Puerto Rico Police Department since 2014. The decision will make it possible for advocates such as Mari to get a clear picture of how state police officers are using force, and when that use of force crosses the line into abuse. But the court victory flooded her small organization with data.
“We won, finally, and then I realized I was going to be receiving thousands of documents that I had zero capacity to process,” says Mari.
“One of the things that’s important to me when analyzing data is to find out where the gaps are, why those gaps exist, and what those gaps represent.” —Tarak Shah, data scientist
The Court made its decision in April 2021, and the police department started handing over PDF files in July. By the end, there could be up to 10,000 documents that get turned in. In addition to incident reports, the police had to provide their use-of-force database. Combined, the victory provides a complicated mixture of quantitative and qualitative data that can be analyzed to answer questions about what the state police are doing to its citizens during police interventions. In particular, Kilómetro Cero, which Mari founded, wants to find out if some Puerto Ricans are more likely to be victims of police violence than others.
“We’re looking for bias,” says Mari. “Bias against poor people, or people who live in a certain neighborhood. Gender bias. Language bias. Bias against drug users, sex workers, immigrants, people who don’t have a house. We’re trying to analyze the language of vulnerability.”…(More)”.
Paper by Emmanuel Letouzé et al: “The near-ubiquitous use of mobile devices generates mobility data that can paint pictures of urban behavior at unprecedented levels of granularity and complexity. In the current period of intense sociopolitical polarization, mobility data can help reveal which urban spaces serve to attenuate or accentuate socioeconomic divides. If urban spaces served to bridge class divides, people from different socioeconomic groups would be prone to mingle in areas further removed from their homes, creating opportunities for sharing experiences in the physical world. In an opposing scenario, people would remain among neighbors and peers, creating “local urban bubbles” that reflect and reinforce social inequities and their adverse effects on social mixity, cohesion, and trust. These questions are especially salient in cities with high levels of socioeconomic inequality, such as Mexico City.
Building on a joint research project between Data-Pop Alliance and Oxfam Mexico titled “Mundos Paralelos” [Parallel Worlds], this paper leverages privacy-preserving mobility data to unveil the unequal use and appropriation of urban spaces by the inhabitants of Mexico City. This joint research harnesses a year (2018–2019) of anonymized mobility data to perform mobility and behavioral analysis of specific groups at high spatial resolution. Its main findings suggest that Mexico City is a spatially fragmented, even segregated city: although distinct socioeconomic groups do meet in certain spaces, a pattern emerges where certain points of interest are exclusive to the high- and low-income groups analyzed in this paper. The results demonstrate that spatial inequality in Mexico City is marked by unequal access to government services and cultural sites, which translates into unequal experiences of urban life and biased access to the city. The paper concludes with a series of public policy recommendations to foster a more equitable and inclusive appropriation of public space…(More)”.
Book by David Nemer: “Brazilian favelas are impoverished settlements usually located on hillsides or the outskirts of a city. In Technology of the Oppressed, David Nemer draws on extensive ethnographic fieldwork to provide a rich account of how favela residents engage with technology in community technology centers and in their everyday lives. Their stories reveal the structural violence of the information age. But they also show how those oppressed by technology don’t just reject it, but consciously resist and appropriate it, and how their experiences with digital technologies enable them to navigate both digital and nondigital sources of oppression—and even, at times, to flourish.
Nemer uses a decolonial and intersectional framework called Mundane Technology as an analytical tool to understand how digital technologies can simultaneously be sites of oppression and tools in the fight for freedom. Building on the work of the Brazilian educator and philosopher Paulo Freire, he shows how the favela residents appropriate everyday technologies—technological artifacts (cell phones, Facebook), operations (repair), and spaces (Telecenters and Lan Houses)—and use them to alleviate the oppression in their everyday lives. He also addresses the relationship of misinformation to radicalization and the rise of the new far right. Contrary to the simplistic techno-optimistic belief that technology will save the poor, even with access to technology these marginalized people face numerous sources of oppression, including technological biases, racism, classism, sexism, and censorship. Yet the spirit, love, community, resilience, and resistance of favela residents make possible their pursuit of freedom…(More)”.
A government‘s toolkit to disrupt corruption through data-based technologies.
Blog by Camilo Cetina: “The Lava Jato corruption scandal exposed a number of Brazilian government officers in 2016, including the then president of the Brazilian Chamber of Representatives, and further investigations have implicated other organisations in a way that reveals a worrying phenomenon worldwide: corruption is mutating into complex forms of organized crime.
For corruption networks to thrive and predate public funds, they need to capture government officers. Furthermore, the progressive digitalization of economies and telecommunications increases the potential of corruption networks to operate transnationally, which makes it easier to identify new cooperation mechanisms (for example, mobilizing illicit cash through a church) and accumulate huge profits thanks to transnational operations. This simultaneously increases their ability to reorganize and hide among huge amounts of data underlying the digital platforms used to mobilize money around the world.
However, at the same time, data-based technologies can significantly contribute as a response to the challenges revealed by recent corruption cases such as Lava Jato, Odebrecht, the Panama Papers or the Pandora Papers. The new report DIGIntegrity, the executive summary of which was recently published by CAF — Development Bank of Latin America, highlights how anti-corruption policies can become more effective when they target specific datasets which then are reused through digital platforms to prevent, detect and investigate corruption networks.
The report explains how the growing digitalization accompanied by the globalization of the economy is having a twofold effect on governments’ integrity agendas. On the one hand, globalization and technology provide unprecedented opportunities for corruption to grow, thus facilitating the concealment of illicit flows of money, and hindering jurisdictional capacities for detection and punishment. But, on the other hand, systemic improvements in governance and collective action are being achieved thanks to new technologies that help provide automated services and make public management processes more visible through open data and increasingly public records. There are “integrity dividends” derived from the growing digitization of governments and the increasingly intensive use of data intelligence to prevent corruption….(More).”
OECD Report: “Governments can use artificial intelligence (AI) to design better policies and make better and more targeted decisions, enhance communication and engagement with citizens, and improve the speed and quality of public services. The Latin America and the Caribbean (LAC) region is seeking to leverage the immense potential of AI to promote the digital transformation of the public sector. The OECD, in collaboration with CAF, Development Bank of Latin America, prepared this report to help national governments in the LAC region understand the current regional baseline of activities and capacities for AI in the public sector; to identify specific approaches and actions they can take to enhance their ability to use this emerging technology for efficient, effective and responsive governments; and to collaborate across borders in pursuit of a regional vision for AI in the public sector. This report incorporates a stocktaking of each country’s strategies and commitments around AI in the public sector, including their alignment with the OECD AI Principles. It also includes an analysis of efforts to build key governance capacities and put in place critical enablers for AI in the public sector. It concludes with a series of recommendations for governments in the LAC region….(More)”.
Press Release by Fundação de Amparo à Pesquisa do Estado de São Paulo: “Brazilian researchers have developed a computer program that locates swimming pools and rooftop water tanks in aerial photographs with the aid of artificial intelligence to help identify areas vulnerable to infestation by Aedes aegypti, the mosquito that transmits dengue, zika, chikungunya and yellow fever.
The innovation, which can also be used as a public policy tool for dynamic socio-economic mapping of urban areas, resulted from research and development work by professionals at the University of São Paulo (USP), the Federal University of Minas Gerais (UFMG) and the São Paulo State Department of Health’s Endemic Control Superintendence (SUCEN), as part of a project supported by FAPESP. An article about it is published in the journal PLOS ONE.
“Our work initially consisted of creating a model based on aerial images and computer science to detect water tanks and pools, and to use them as a socio-economic indicator,” said Francisco Chiaravalloti Neto, last author of the article. He is a professor in the Epidemiology Department at USP’s School of Public Health (FSP), with a first degree in engineering.
As the article notes, previous research had already shown that dengue tends to be most prevalent in deprived urban areas, so that prevention of dengue, zika and other diseases transmitted by the mosquito can be made considerably more effective by use of a relatively dynamic socio-economic mapping model, especially given the long interval between population censuses in Brazil (ten years or more).
“This is one of the first steps in a broader project,” Chiaravalloti Neto said. Among other aims, he and his team plan to detect other elements of the images and quantify real infestation rates in specific areas so as to be able to refine and validate the model.
“We want to create a flow chart that can be used in different cities to pinpoint at-risk areas without the need for inspectors to call on houses, buildings and other breeding sites, as this is time-consuming and a waste of the taxpayer’s money,” he added…(More)”.
Article by Agustina Iñiguez: “Within the Latin American and Caribbean region, it has been recorded that at least 25% of the population lives in informal settlements. Given that their expansion is one of the major problems afflicting these cities, a project is presented, supported by the IDB, which proposes how new technologies are capable of contributing to the identification and detection of these areas in order to intervene in them and help reduce urban informality.
Informal settlements, also known as slums, shantytowns, camps or favelas, depending on the country in question, are uncontrolled settlements on land where, in many cases, the conditions for a dignified life are not in place. Through self-built dwellings, these sites are generally the result of the continuous growth of the housing deficit.
For decades, the possibility of collecting information about the Earth’s surface through satellite imagery has been contributing to the analysis and production of increasingly accurate and useful maps for urban planning. In this way, not only the growth of cities can be seen, but also the speed at which they are growing and the characteristics of their buildings.
Advances in artificial intelligence facilitate the processing of a large amount of information. When a satellite or aerial image is taken of a neighbourhood where a municipal team has previously demarcated informal areas, the image is processed by an algorithm that will identify the characteristic visual patterns of the area observed from space. The algorithm will then identify other areas with similar characteristics in other images, automatically recognising the districts where informality predominates. It is worth noting that while satellites are able to report both where and how informal settlements are growing, specialised equipment and processing infrastructure are also required…(More)”
Paper by Sarita Albagli & Allan Yu Iwama: “The article presents results of a research project aiming to develop theoretical and empirical contributions on participatory approaches and methods of citizen science for risk mapping and adaptation to climate change. In the first part, the paper presents a review of the literature on key concepts and perspectives related to participatory citizen science, introducing the concept of the “right to research”. It highlights the mutual fertilization with participatory mapping methods to deal with disaster situations associated to climate change. In the second part, the paper describes and presents the results and conclusions of an action-research developed on the coastline between the states of São Paulo and Rio de Janeiro, Brazil in 2017–2018. It involved affected communities as protagonists in mapping and managing risks of natural disasters caused by extreme climate events, by combining citizen science approaches and methods with Participatory Geographic Information Systems (PGIS) and social cartography. The article concludes by pointing out the contributions and limits of the “right to research” as a relevant Social Science approach to reframe citizen science from a democratic view….(More)”.
Article by Juan Daniel Oviedo, Katharina Fenz, François Fonteneau, and Simon Riedl: “In recent years, breakthrough technologies in artificial intelligence (AI) and the use of satellite imagery made it possible to disrupt the way we collect, process, and analyze data. Facilitated by the intersection of new statistical techniques and the availability of (big) data, it is now possible to create hypergranular estimates.
National statistical offices (NSOs) could be at the forefront of this change. Conventional tasks of statistical offices, such as the coordination of household surveys and censuses, will remain at the core of their work. However, just like AI can enhance the capabilities of doctors, it also has the potential to make statistical offices better, faster, and eventually cheaper.
Still, many countries struggle to make this happen. In a COVID-19 world marked by constrained financial and statistical capacities, making innovation work for statistical offices is of prime importance to create better lives for all…
In the case of Colombia, this novel method facilitated a scale-up from existing poverty estimates that contained 1,123 data points to 78,000 data points, which represents a 70-fold increase. This results in much more granular estimates highlighting Colombia’s heterogeneity between and within municipalities (see Figure 1).
Figure 1. Poverty shares (%) Colombia, in 2018
Traditional methods don´t allow for cost-efficient hypergranular estimations but serve as a reference point, due to their ground-truthing capacity. Hence, we have combined existing data with novel AI techniques, to go down to granular estimates of up to 4×4 kilometers. In particular, we have trained an algorithm to connect daytime and nighttime satellite images….(More)”.