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)”.
New Data Browser on education, science, and culture
UNESCO: “The UIS is excited to introduce the new UIS Data Browser, which brings together all our data on education, science, and culture, making it a convenient resource for everyone, from policymakers to researchers.
With a refreshed interface, users can easily view and download customized data for their needs. The new browser also offers better tools for exploring metadata and documentation. Plus, the browser has great visualization features. You can filter indicators by country or region and create line or bar charts to see trends over time. It’s easy to share your findings on social media, too!
For those who like to dive deeper, a web-based UIS Data Application Programming Interface (API) allows for more technical data extraction for use in reports and applications. The UIS Data API provides access to all education, science, and culture data available on the UIS data browser through HTTP requests. It allows for the regular retrieval of data for custom analysis, visualizations, and applications…(More)”.
Trust in official statistics remains high but there’s still work to do
Article by Ian Diamond (UK): “..I’m excited about the potential of new data sources, and I want everyone in the UK to have the skills to understand and use the stats they allow us to create. With this in mind, we’re launching a whole host of new projects to bring our stats to the people:
How to videos
To benefit from stats, and be confident that they are reliable, we need to understand more about the data they have been derived from and how to read and use them.
Our new set of video guides are a great place to start, covering topics such as why data matters to how the ONS de-identifies them and where we get them from.
They are all available to watch on our YouTube channel.
Playground survey
During the 2023/2024 school year, we teamed up with the BBC and the Micro:bit Foundation to give children in primary schools the opportunity to take part in a nationwide playground survey.
The BBC Micro:bit Playground Survey is a wonderful way for children to learn data skills at an early age, getting to grips with data collection and analysis in a way that is relevant to their everyday lives, in a familiar and fun setting.
If children become data-literate now, they will be well prepared to navigate and take advantage of the huge amounts of data that will no doubt play an important role in their adult lives.
Keep an eye out for the results in October.
Navigating numbers – the ONS data education programme
We’ve also been busy developing a data education programme for students in further education or sixth form.
Navigating numbers: how data are used to create statistics includes a series of five classroom toolkits, exploring topics such as gender pay gaps, inflation, and health.
Created with the support of the Association of Colleges (AoC), this learning resource is free for teachers to use and available for download on the ONS website.
The ONS’s educational webinar series: Bringing data to life
If you want to learn more about measuring the cost of living or our nation’s health, then our new webinar series has you covered. These and other topics will be brought to life in this new series of online events, launching in September 2024…(More)”
Advancing Data Equity: An Action-Oriented Framework
WEF Report: “Automated decision-making systems based on algorithms and data are increasingly common today, with profound implications for individuals, communities and society. More than ever before, data equity is a shared responsibility that requires collective action to create data practices and systems that promote fair and just outcomes for all.
This paper, produced by members of the Global Future Council on Data Equity, proposes a data equity definition and framework for inquiry that spurs ongoing dialogue and continuous action towards implementing data equity in organizations. This framework serves as a dynamic tool for stakeholders committed to operationalizing data equity, across various sectors and regions, given the rapidly evolving data and technology landscapes…(More)”.