Paper by Arun G. Chandrasekhar, Esther Duflo, Michael Kremer, João F. Pugliese, Jonathan Robinson & Frank Schilbach: “An enduring puzzle regarding technology adoption in developing countries is that new technologies often diffuse slowly through the social network. Two of the key predictions of the canonical epidemiological model of technology diffusion are that forums to share information and higher returns to technology should both spur social transmission. We design a large-scale experiment to test these predictions among farmers in Western Kenya, and we fail to find support for either. However, in the same context, we introduce a technology that diffuses very fast: a simple kitchen spoon (painted in blue) to measure out how much fertilizer to use. We develop a model that explains both the failure of the standard approaches and the surprising success of this new technology. The core idea of the model is that not all information is reliable, and farmers are reluctant to develop a reputation of passing along false information. The model and data suggest that there is value in developing simple, transparent technologies to facilitate communication…(More)”.
Spirals of Delusion: How AI Distorts Decision-Making and Makes Dictators More Dangerous
Essay by Henry Farrell, Abraham Newman, and Jeremy Wallace: “In policy circles, discussions about artificial intelligence invariably pit China against the United States in a race for technological supremacy. If the key resource is data, then China, with its billion-plus citizens and lax protections against state surveillance, seems destined to win. Kai-Fu Lee, a famous computer scientist, has claimed that data is the new oil, and China the new OPEC. If superior technology is what provides the edge, however, then the United States, with its world class university system and talented workforce, still has a chance to come out ahead. For either country, pundits assume that superiority in AI will lead naturally to broader economic and military superiority.
But thinking about AI in terms of a race for dominance misses the more fundamental ways in which AI is transforming global politics. AI will not transform the rivalry between powers so much as it will transform the rivals themselves. The United States is a democracy, whereas China is an authoritarian regime, and machine learning challenges each political system in its own way. The challenges to democracies such as the United States are all too visible. Machine learning may increase polarization—reengineering the online world to promote political division. It will certainly increase disinformation in the future, generating convincing fake speech at scale. The challenges to autocracies are more subtle but possibly more corrosive. Just as machine learning reflects and reinforces the divisions of democracy, it may confound autocracies, creating a false appearance of consensus and concealing underlying societal fissures until it is too late.
Early pioneers of AI, including the political scientist Herbert Simon, realized that AI technology has more in common with markets, bureaucracies, and political institutions than with simple engineering applications. Another pioneer of artificial intelligence, Norbert Wiener, described AI as a “cybernetic” system—one that can respond and adapt to feedback. Neither Simon nor Wiener anticipated how machine learning would dominate AI, but its evolution fits with their way of thinking. Facebook and Google use machine learning as the analytic engine of a self-correcting system, which continually updates its understanding of the data depending on whether its predictions succeed or fail. It is this loop between statistical analysis and feedback from the environment that has made machine learning such a formidable force…(More)”
Nowcasting daily population displacement in Ukraine through social media advertising data
Pre-Publication Paper by Douglas R. Leasure et al: “In times of crisis, real-time data mapping population displacements are invaluable for targeted humanitarian response. The Russian invasion of Ukraine on February 24, 2022 forcibly displaced millions of people from their homes including nearly 6m refugees flowing across the border in just a few weeks, but information was scarce regarding displaced and vulnerable populations who remained inside Ukraine. We leveraged near real-time social media marketing data to estimate sub-national population sizes every day disaggregated by age and sex. Our metric of internal displacement estimated that 5.3m people had been internally displaced away from their baseline administrative region by March 14. Results revealed four distinct displacement patterns: large scale evacuations, refugee staging areas, internal areas of refuge, and irregular dynamics. While this innovative approach provided one of the only quantitative estimates of internal displacement in virtual real-time, we conclude by acknowledging risks and challenges for the future…(More)”.
State of Gender Data
Report by Data2X: “Gender data is fundamental to achieving gender equality and the Sustainable Development Goals. It helps identify inequalities, illuminate a path forward, and monitor global progress. As recognition of its importance has grown over the last decade, the availability of gender data—and its use in decision-making—has improved.
Yet overlapping crises, from the COVID-19 pandemic to climate change and conflict, have imperiled progress on gender equality and the Sustainable Development Goals. In 2022, UN Secretary General Antonio Gutierrez declared that the Sustainable Development Goals are in need of rescue. The 2022 SDG Gender Index by EM2030 found little progress on global gender equality between 2015 and 2020, and a recent assessment by UN Women demonstrates that more than one quarter of the indicators needed to measure progress on gender equality are “far or very far” from 2030 targets….The State of Gender Data is an evolving Data2X publication and digital experience designed to highlight global progress and spur action on gender data. Data2X will update the initiative annually, providing insight into a new dimension of gender data. For our initial launch, we focus on examining funding trends and highlighting promising solutions and key commitments….(More)”.
Citizen science in environmental and ecological sciences
Paper by Dilek Fraisl et al: “Citizen science is an increasingly acknowledged approach applied in many scientific domains, and particularly within the environmental and ecological sciences, in which non-professional participants contribute to data collection to advance scientific research. We present contributory citizen science as a valuable method to scientists and practitioners within the environmental and ecological sciences, focusing on the full life cycle of citizen science practice, from design to implementation, evaluation and data management. We highlight key issues in citizen science and how to address them, such as participant engagement and retention, data quality assurance and bias correction, as well as ethical considerations regarding data sharing. We also provide a range of examples to illustrate the diversity of applications, from biodiversity research and land cover assessment to forest health monitoring and marine pollution. The aspects of reproducibility and data sharing are considered, placing citizen science within an encompassing open science perspective. Finally, we discuss its limitations and challenges and present an outlook for the application of citizen science in multiple science domains…(More)”.
Academic freedom and democracy in African countries: the first study to track the connection
Article by Liisa Laakso: “There is growing interest in the state of academic freedom worldwide. A 1997 Unesco document defines it as the right of scholars to teach, discuss, research, publish, express opinions about systems and participate in academic bodies. Academic freedom is a cornerstone of education and knowledge.
Yet there is surprisingly little empirical research on the actual impact of academic freedom. Comparable measurements have also been scarce. It was only in 2020 that a worldwide index of academic freedom was launched by the Varieties of Democracy database, V-Dem, in collaboration with the Scholars at Risk Network….
My research has been on the political science discipline in African universities and its role in political developments on the continent. As part of this project, I have investigated the impact of academic freedom in the post-Cold War democratic transitions in Africa.
A study I published with the Tunisian economist Hajer Kratou showed that academic freedom has a significant positive effect on democracy, when democracy is measured by indicators such as the quality of elections and executive accountability.
However, the time factor is significant. Countries with high levels of academic freedom before and at the time of their democratic transition showed high levels of democracy even 5, 10 and 15 years later. In contrast, the political situation was more likely to deteriorate in countries where academic freedom was restricted at the time of transition. The impact of academic freedom was greatest in low-income countries….(More)”
Data for Peace and Humanitarian Response? The Case of the Ukraine-Russia War
Article by Behruz Davletov, Uma Kalkar, Salwa Mansuri, Marine Ragnet, and Stefaan Verhulst at Data & Policy: “Since the outbreak of hostilities between Russia and Ukraine on 24 February 2022, more than 4,889 (28,081 according to the Ukrainian government) civilians have been killed and over 7 million people have been displaced. The conflict has had a significant impact on civilians, particularly women and children. In response to the crisis, local and international organizations have sought to provide immediate humanitarian assistance, and initiated numerous initiatives to monitor violations and work toward peacebuilding and conflict resolution.
As in other areas of society, data and data science have become important to tailor, conduct, and monitor emergency responses in conflict zones. Data has also become crucial to support humanitarian action and peacebuilding. For example, data collected from satellite, GPS, and drone technologies can be used to map a conflict’s evolution, understand the needs of civilians, evaluate migration patterns, analyze discourses coming from both sides, and track the delivery of assistance.
This article focuses on the role that data has played in crisis response and peacebuilding related to the Russian-Ukrainian war so as to demonstrate how data can be used for peace. We consider a variety of publicly available evidence to examine various aspects of how data is playing a role in the ongoing conflict, mainly from a humanitarian response perspective. In particular, we consider the following aspects and taxonomy of data usage:
- Prediction: Data is used to monitor and plan for likely events and risks both prior to and during the conflict;
- Narratives: Data plays a critical role in both constructing and countering misinformation and disinformation;
- Infrastructure Damage: Data can be used to track and respond to infrastructure damage, as well as to associated human rights violations and migration flows;
- Human Rights Violations and Abuses: Data is used to identify and report human rights abuses, and to help construct a legal basis for justice;
- Migration Flows: Large-scale population flows, both within Ukraine and toward neighboring countries, are one of the defining features of the conflict. Data is being used to monitor these flows, and to target humanitarian assistance;
- Humanitarian Response: In addition to the above, data is also being used for a wide variety of humanitarian purposes, including ensuring basic and medical supplies, and addressing the resulting mental health crisis….(More)”.
U.S. Government Effort to Tap Private Weather Data Moves Along Slowly
Article by Isabelle Bousquette: “The U.S. government’s six-year-old effort to improve its weather forecasting ability by purchasing data from private-sector satellite companies has started to show results, although the process is moving more slowly than anticipated.
After a period of testing, the National Oceanic and Atmospheric Administration, a scientific, service and regulatory arm of the Commerce Department, began purchasing data from two satellite companies, Spire Global Inc. of Vienna, Va., and GeoOptics Inc. of Pasadena, Calif.
The weather data from these two companies fills gaps in coverage left by NOAA’s own satellites, the agency said. NOAA also began testing data from a third company this year.
Beyond these companies, new entrants to the field offering weather data based on a broader range of technologies have been slow to emerge, the agency said.
“We’re getting a subset of what we hoped,” said Dan St. Jean, deputy director of the Office of System Architecture and Advanced Planning at NOAA’s Satellite and Information Service.
NOAA’s weather forecasts help the government formulate hurricane evacuation plans and make other important decisions. The agency began seeking out private sources of satellite weather data in 2016. The idea was to find a more cost-effective alternative to funding NOAA’s own satellite constellations, the agency said. It also hoped to seed competition and innovation in the private satellite sector.
It isn’t yet clear whether there is a cost benefit to using private data, in part because the relatively small number of competitors in the market has made it challenging to determine a steady market price, NOAA said.
“All the signs in the nascent ‘new space’ industry indicated that there would be a plethora of venture capitalists wanting to compete for NOAA’s commercial pilot/purchase dollars. But that just never materialized,” said Mr. St. Jean…(More)”.
Reorganise: 15 stories of workers fighting back in a digital age
Book edited by Hannah O’Rourke & Edward Saperia: “In only a decade, the labour market has changed beyond all recognition – from zero-hour contracts to platform monopolies. As capitalism has re-created itself for the digital age, so too must the workers whose labour underpins it.
From a union for instagram influencers to roadworkers organising through a Facebook Group, former WSJ journalist Lucy Harley-McKeown takes us on a journey to discover how workers are fighting back in the 21st century…(More)”.
Mapping community resources for disaster preparedness: humanitarian data capability and automated futures
Report by Anthony McCosker et al: “The project seeks to enable local community disaster preparedness and thus build community resilience by improving the quality of data about community strengths, resources and assets.
In this report, the authors define a gap in existing humanitarian mapping approaches and the uses of open, public and social media data in humanitarian contexts. The report surveys current knowledge and present a selection of case studies delivering data and humanitarian mapping in local communities.
Drawing on this knowledge and practice review and stakeholder workshops throughout 2021, the authors also define a method and toolkit for the effective use of community assets data…(More)”