Why is it so hard to establish the death toll?


Article by Smriti Mallapaty: “Given the uncertainty of counting fatalities during conflict, researchers use other ways to estimate mortality.

One common method uses household surveys, says Debarati Guha-Sapir, an epidemiologist who specializes in civil conflicts at the University of Louvain in Louvain-la-Neuve, Belgium, and is based in Brussels. A sample of the population is asked how many people in their family have died over a specific period of time. This approach has been used to count deaths in conflicts elsewhere, including in Iraq3 and the Central African Republic4.

The situation in Gaza right now is not conducive to a survey, given the level of movement and displacement, say researchers. And it would be irresponsible to send data collectors into an active conflict and put their lives at risk, says Ball.

There are also ethical concerns around intruding on people who lack basic access to food and medication to ask about deaths in their families, says Jamaluddine. Surveys will have to wait for the conflict to end and movement to ease, say researchers.

Another approach is to compare multiple independent lists of fatalities and calculate mortality from the overlap between them. The Human Rights Data Analysis Group used this approach to estimate the number of people killed in Syria between 2011 and 2014. Jamaluddine hopes to use the ministry fatality data in conjunction with those posted on social media by several informal groups to estimate mortality in this way. But Guha-Sapir says this method relies on the population being stable and not moving around, which is often not the case in conflict-affected communities.

In addition to deaths immediately caused by the violence, some civilians die of the spread of infectious diseases, starvation or lack of access to health care. In February, Jamaluddine and her colleagues used modelling to make projections of excess deaths due to the war and found that, in a continued scenario of six months of escalated conflict, 68,650 people could die from traumatic injuries, 2,680 from non-communicable diseases such as cancer and 2,720 from infectious diseases — along with thousands more if an epidemic were to break out. On 30 July, the ministry declared a polio epidemic in Gaza after detecting the virus in sewage samples, and in mid-August it confirmed the first case of polio in 25 years, in a 10-month-old baby…

The longer the conflict continues, the harder it will be to get reliable estimates, because “reports by survivors get worse as time goes by”, says Jon Pedersen, a demographer at !Mikro in Oslo, who advises international agencies on mortality estimates…(More)”.

Germany’s botched data revamp leaves economists ‘flying blind’


Article by Olaf Storbeck: “Germany’s statistical office has suspended some of its most important indicators after botching a data update, leaving citizens and economists in the dark at a time when the country is trying to boost flagging growth.

In a nation once famed for its punctuality and reliability, even its notoriously diligent beancounters have become part of a growing perception that “nothing works any more” as Germans moan about delayed trains, derelict roads and bridges, and widespread staff shortages.

“There used to be certain aspects in life that you could just rely on, and the fact that official statistics are published on time was one of them — not any more,” said Jörg Krämer, chief economist of Commerzbank, adding that the suspended data was also closely watched by monetary policymakers and investors.

Since May the Federal Statistical Office (Destatis) has not updated time-series data for retail and wholesale sales, as well as revenue from the services sector, hospitality, car dealers and garages.

These indicators, which are published monthly and adjusted for seasonal changes, are a key component of GDP and crucial for assessing consumer demand in the EU’s largest economy.

Private consumption accounted for 52.7 per cent of German output in 2023. Retail sales made up 28 per cent of private consumption but shrank 3.4 per cent from a year earlier. Overall GDP declined 0.3 per cent last year, Destatis said.

The Wiesbaden-based authority, which was established in 1948, said the outages had been caused by IT issues and a complex methodological change in EU business statistics in a bid to boost accuracy.

Destatis has been working on the project since the EU directive in 2019, and the deadline for implementing the changes is December.

But a series of glitches, data issues and IT delays meant Destatis has been unable to publish retail sales and other services data for four months.

A key complication is that the revenues of companies that operate in both services and manufacturing will now be reported differently for each sector. In the past, all revenue was treated as either services or manufacturing, depending on which unit was bigger…(More)”

Synthetic Data and Social Science Research


Paper by Jordan C. Stanley & Evan S. Totty: “Synthetic microdata – data retaining the structure of original microdata while replacing original values with modeled values for the sake of privacy – presents an opportunity to increase access to useful microdata for data users while meeting the privacy and confidentiality requirements for data providers. Synthetic data could be sufficient for many purposes, but lingering accuracy concerns could be addressed with a validation system through which the data providers run the external researcher’s code on the internal data and share cleared output with the researcher. The U.S. Census Bureau has experience running such systems. In this chapter, we first describe the role of synthetic data within a tiered data access system and the importance of synthetic data accuracy in achieving a viable synthetic data product. Next, we review results from a recent set of empirical analyses we conducted to assess accuracy in the Survey of Income & Program Participation (SIPP) Synthetic Beta (SSB), a Census Bureau product that made linked survey-administrative data publicly available. Given this analysis and our experience working on the SSB project, we conclude with thoughts and questions regarding future implementations of synthetic data with validation…(More)”

Artificial Intelligence as a Catalyzer for Open Government Data Ecosystems: A Typological Theory Approach


Paper by Anthony Simonofski et al: “Artificial Intelligence (AI) within digital government has witnessed growing interest as it can improve governance processes and stimulate citizen engagement. Despite the rise of Generative AI, discussions on AI fusion with Open Government Data (OGD) remain limited to specific implementations and scattered across disciplines. Drawing from the synthesis of the literature through a systematic review, this study examines and structures how AI can enrich OGD initiatives. Employing a typological approach, ideal profiles of AI application within the OGD lifecycle are formalized, capturing varied roles across the portal and ecosystems perspectives. The resulting conceptual framework identifies eight ideal types of AI applications for OGD: AI as Portal Curator, Explorer, Linker, and Monitor, and AI as Ecosystem Data Retriever, Connecter, Value Developer and Engager. This theoretical foundation shows the under-investigation of some types and will inform policymakers, practitioners, and researchers in leveraging AI to cultivate OGD ecosystems…(More)”.

Visualizing Ship Movements with AIS Data


Article by Jon Keegan: “As we run, drive, bike, and fly, humans leave behind telltale tracks of movement on Earth—if you know where to look. Physical tracks, thermal signatures, and chemical traces can reveal where we’ve been. But another type of breadcrumb trail comes from the radio signals emitted by the cars, planes, trains, and boats we use.

Just like ADS-B transmitters on airplanes, which provide real-time location, identification, speed, and orientation data, the AIS (Automatic Identification System) performs the same function for ships at sea.

Operating at 161.975 and 162.025 MHz, AIS transmitters broadcast a ship’s identification number, name, call sign, length, beam, type, and antenna location every six minutes. Ship location, position timestamp, and direction are transmitted more frequently. The primary purpose of AIS is maritime safety—it helps prevent collisions, assists in rescues, and provides insight into the impact of ship traffic on marine life.

Unlike ADS-B in a plane, AIS can only be turned off in rare circumstances. The result of this is a treasure trove of fascinating ship movement data. You can even watch live ship data on sites like Vessel Finder.

Using NOAA’s “Marine Cadastre” tool, you can download 16 years’ worth of detailed daily ship movements (filtered to the minute), in addition to “transit count” maps generated from a year’s worth of data to show each ship’s accumulated paths…(More)”.

Data Privacy for Record Linkage and Beyond


Paper by Shurong Lin & Eric Kolaczyk: “In a data-driven world, two prominent research problems are record linkage and data privacy, among others. Record linkage is essential for improving decision-making by integrating information of the same entities from different sources. On the other hand, data privacy research seeks to balance the need to extract accurate insights from data with the imperative to protect the privacy of the entities involved. Inevitably, data privacy issues arise in the context of record linkage. This article identifies two complementary aspects at the intersection of these two fields: (1) how to ensure privacy during record linkage and (2) how to mitigate privacy risks when releasing the analysis results after record linkage. We specifically discuss privacy-preserving record linkage, differentially private regression, and related topics…(More)”.

Mapping AI Narratives at the Local Level


Article for Urban AI: “In May 2024, Nantes Métropole (France) launched a pioneering initiative titled “Nantes Débat de l’IA” (meaning “Nantes is Debating AI”). This year-long project is designed to curate the organization of events dedicated to artificial intelligence (AI) across the territory. The primary aim of this initiative is to foster dialogue among local stakeholders, enabling them to engage in meaningful discussions, exchange ideas, and develop a shared understanding of AI’s impact on the region.

Over the course of one year, the Nantes metropolitan area will host around sixty events focused on AI, bringing together a wide range of participants, including policymakers, businesses, researchers, and civil society. These events provide a platform for these diverse actors to share their perspectives, debate critical issues, and explore the potential opportunities and challenges AI presents. Through this collaborative process, the goal is to cultivate a common culture around AI, ensuring that all relevant voices are heard as the city navigates to integrate this transformative technology…(More)”.

Utilizing big data without domain knowledge impacts public health decision-making


Paper by Miao Zhang, Salman Rahman, Vishwali Mhasawade and Rumi Chunara: “…New data sources and AI methods for extracting information are increasingly abundant and relevant to decision-making across societal applications. A notable example is street view imagery, available in over 100 countries, and purported to inform built environment interventions (e.g., adding sidewalks) for community health outcomes. However, biases can arise when decision-making does not account for data robustness or relies on spurious correlations. To investigate this risk, we analyzed 2.02 million Google Street View (GSV) images alongside health, demographic, and socioeconomic data from New York City. Findings demonstrate robustness challenges; built environment characteristics inferred from GSV labels at the intracity level often do not align with ground truth. Moreover, as average individual-level behavior of physical inactivity significantly mediates the impact of built environment features by census tract, intervention on features measured by GSV would be misestimated without proper model specification and consideration of this mediation mechanism. Using a causal framework accounting for these mediators, we determined that intervening by improving 10% of samples in the two lowest tertiles of physical inactivity would lead to a 4.17 (95% CI 3.84–4.55) or 17.2 (95% CI 14.4–21.3) times greater decrease in the prevalence of obesity or diabetes, respectively, compared to the same proportional intervention on the number of crosswalks by census tract. This study highlights critical issues of robustness and model specification in using emergent data sources, showing the data may not measure what is intended, and ignoring mediators can result in biased intervention effect estimates…(More)”

AI Localism Repository: A Tool for Local AI Governance


About: “In a world where AI continues to be ever more entangled with our communities, cities, and decision-making processes, local governments are stepping up to address the challenges of AI governance. Today, we’re excited to announce the launch of the newly updated AI Localism Repository—a curated resource designed to help local governments, researchers, and citizens understand how AI is being governed at the state, city, or community level.

What is AI Localism?

AI Localism refers to the actions taken by local decision-makers to address AI governance in their communities. Unlike national or global policies, AI Localism offers immediate solutions tailored to specific local conditions, creating opportunities for greater effectiveness and accountability in the governance of AI.

What’s the AI Localism Repository?

The AI Localism Repository is a collection of examples of AI governance measures from around the world, focusing on how local governments are navigating the evolving landscape of AI. This resource is more than just a list of laws—it highlights innovative methods of AI governance, from the creation of expert advisory groups to the implementation of AI pilot programs.

Why AI Localism Matters

Local governments often face unique challenges in regulating AI, from ethical considerations to the social impact of AI in areas like law enforcement, housing, and employment. Yet, local initiatives are frequently overlooked by national and global AI policy observatories. The AI Localism Repository fills this gap, offering a platform for local policymakers to share their experiences and learn from one another…(More)”

Governing AI for Humanity


The United Nations Secretary-General’s High-level Advisory Body on AI’s Final Report: “This report outlines a blueprint for addressing AI-related risks and sharing its transformative potential globally, including by:​

  • ​Urging the UN to lay the foundations of the first globally inclusive and distributed architecture for AI governance based on international cooperation;​
  • Proposing seven recommendations to address gaps in current AI governance arrangements;​
  • Calling on all governments and stakeholders to work together in governing AI to foster development and protection of all human rights.​

​This includes light institutional mechanisms to complement existing efforts and foster inclusive global AI governance arrangements that are agile, adaptive and effective to keep pace with AI’s evolution.​..(More)”.