Zillow introduces First Street’s comprehensive climate risk data on for-sale listings across the US

Curated on Posted on by Stefaan Verhulst

Press Release: “Zillow® is introducing climate risk data, provided by First Street…Home shoppers will gain insights into five key risks—flood, wildfire, wind, heat and air quality—directly from listing pages, complete with risk scores, interactive maps and insurance requirements.

Zillow® is introducing climate risk data, provided by First Street, the standard for climate risk financial modeling, on for-sale property listings across the U.S. Home shoppers will gain insights into five key risks—flood, wildfire, wind, heat and air quality—directly from listing pages, complete with risk scores, interactive maps and insurance requirements.

With more than 80% of buyers now considering climate risks when purchasing a home, this feature provides a clearer understanding of potential hazards, helping buyers to better assess long-term affordability and plan for the future. In assisting buyers to navigate the growing risk of climate change, Zillow is the only platform to feature tailored insurance recommendations alongside detailed historical insights, showing if or when a property has experienced past climate events, such as flooding or wildfires…
When using Zillow’s search map view, home shoppers can explore climate risk data through an interactive map highlighting five key risk categories: flood, wildfire, wind, heat and air quality. Each risk is color-coded and has its own color scale, helping consumers intuitively navigate their search. Informative labels give more context to climate data and link to First Street’s property-specific climate risk reports for full insights.

When viewing a for-sale property on Zillow, home shoppers will see a new climate risk section. This section includes a separate module for each risk category—flood, wildfire, wind, heat and air quality—giving detailed, property-specific data from First Street. This section not only shows how these risks might affect the home now and in the future, but also provides crucial information on wind, fire and flood insurance requirements.

Nationwide, more new listings came with major climate risk, compared to homes listed for sale five years ago, according to a Zillow analysis conducted in August. That trend holds true for all five of the climate risk categories Zillow analyzed. Across all new listings in August, 16.7% were at major risk of wildfire, while 12.8% came with a major risk of flooding…(More)”.

Federal Court Invalidates NYC Law Requiring Food Delivery Apps to Share Customer Data with Restaurants

Curated on Posted on by Stefaan Verhulst

Article by Hunton, Andrews, Kurth: “On September 24, 2024, a federal district court held that New York City’s “Customer Data Law” violates the First Amendment. Passed in the summer of 2021, the law requires food-delivery apps to share customer-specific data with restaurants that prepare delivered meals.

The New York City Council enacted the Customer Data Law to boost the local restaurant industry in the wake of the pandemic. The law requires food-delivery apps to provide restaurants (upon the restaurants’ request) with each diner’s full name, email address, phone number, delivery address, and order contents. Customers may opt out of such sharing. The law’s supporters argue that requiring such disclosure addresses exploitation by the delivery apps and helps restaurants advertise more effectively.

Normally, when a customer places an order through a food-delivery app, the app provides the restaurant with the customer’s first name, last initial and food order. Food-delivery apps share aggregate data analytics with restaurants but generally do not share customer-specific data beyond the information necessary to fulfill an order. Some apps, for example, provide restaurants with data related to their menu performance, customer feedback and daily operations.

Major food-delivery app companies challenged the Customer Data Law, arguing that its data sharing requirement compels speech impermissibly under the First Amendment. Siding with the apps, the U.S. District Court for the Southern District of New York declared the city’s law invalid, holding that its data sharing requirement is not appropriately tailored to a substantial government interest…(More)”.

Need for Co-creating Urban Data Collaborative

Curated on Posted on by Stefaan Verhulst

Blog by Gaurav Godhwani: “…The Government of India has initiated various urban reforms for our cities like — Atal Mission for Rejuvenation and Urban Transformation 2.0 (AMRUT 2.0), Smart Cities Mission (SCM), Swachh Bharat Mission 2.0 (SBM-Urban 2.0) and development of Urban & Industrial Corridors. To help empower cities with data, the Ministry of Housing & Urban Affairs(MoHUA) has also launched various data initiatives including — DataSmart Cities Strategy, Data Maturity Assessment Framework, Smart Cities Open Data Portal, City Innovation Exchange, India Urban Data Exchange and the India Urban Observatory.

Unfortunately, most of the urban data remains in silos and capacities for our cities to harness urban data to improve decision-making, strengthen citizen participation continues to be limited. As per the last Data Maturity Assessment Framework (DMAF) assessment conducted in November 2020 by MoHUA, among 100 smart cities only 45 cities have drafted/ approved their City Data Policies with just 32 cities having a dedicated data budget in 2020–21 for data-related activities. Moreover, in-terms of fostering data collaborations, only 12 cities formed data alliances to achieve tangible outcomes. We hope smart cities continue this practice by conducting a yearly self-assessment to progress in their journey to harness data for improving their urban planning.

Seeding Urban Data Collaborative to advance City-level Data Engagements

There is a need to bring together a diverse set of stakeholders including governments, civil societies, academia, businesses and startups, volunteer groups and more to share and exchange urban data in a secure, standardised and interoperable manner, deriving more value from re-using data for participatory urban development. Along with improving data sharing among these stakeholders, it is necessary to regularly convene, ideate and conduct capacity building sessions and institutionalise data practices.

Urban Data Collaborative can bring together such diverse stakeholders who could address some of these perennial challenges in the ecosystem while spurring innovation…(More)”

Mapping AI Narratives at the Local Level

Curated on Posted on by Stefaan Verhulst

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)”.

AI Localism Repository: A Tool for Local AI Governance

Curated on Posted on by Stefaan Verhulst

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)”

Reviving the commons: A scoping review of urban and digital commoning

Curated on Posted on by Stefaan Verhulst

Report by James Henderson and Oliver Escobar: “The review aims to contribute to the growing discourse on the commons, highlighting its significance in contemporary societies and its potential as an alternative to traditional forms of socioeconomic and political organisation via the state and/or the market. Practitioners in the field argue that we are witnessing a revival of the commons in the 21st century. This report interrogates the nature of that revival and explores key concepts, examples, trends and debates in theory and practice, while outlining an emerging research agenda…(More)”.

Place identity: a generative AI’s perspective

Curated on Posted on by Stefaan Verhulst

Paper by Kee Moon Jang et al: “Do cities have a collective identity? The latest advancements in generative artificial intelligence (AI) models have enabled the creation of realistic representations learned from vast amounts of data. In this study, we test the potential of generative AI as the source of textual and visual information in capturing the place identity of cities assessed by filtered descriptions and images. We asked questions on the place identity of 64 global cities to two generative AI models, ChatGPT and DALL·E2. Furthermore, given the ethical concerns surrounding the trustworthiness of generative AI, we examined whether the results were consistent with real urban settings. In particular, we measured similarity between text and image outputs with Wikipedia data and images searched from Google, respectively, and compared across cases to identify how unique the generated outputs were for each city. Our results indicate that generative models have the potential to capture the salient characteristics of cities that make them distinguishable. This study is among the first attempts to explore the capabilities of generative AI in simulating the built environment in regard to place-specific meanings. It contributes to urban design and geography literature by fostering research opportunities with generative AI and discussing potential limitations for future studies…(More)”.

Atlas of Intangibles

Curated on Posted on by Stefaan Verhulst

About: “Atlas of Intangibles is a data experience designed to highlight the rich, interconnected web of sensory information that lies beneath our everyday encounters. Showcasing sensory data collected by me around the city of London through score-based data walks, the digital experience allows viewers to choose specific themes and explore related data as views — journeys, connections, and typologies. Each data point is rich in context, encompassing images and audio recordings…(More)”.

Data sovereignty for local governments. Considerations and enablers

Curated on Posted on by Stefaan Verhulst

Report by JRC Data sovereignty for local governments refers to a capacity to control and/or access data, and to foster a digital transformation aligned with societal values and EU Commission political priorities. Data sovereignty clauses are an instrument that local governments may use to compel companies to share data of public interest. Albeit promising, little is known about the peculiarities of this instrument and how it has been implemented so far. This policy brief aims at filling the gap by systematising existing knowledge and providing policy-relevant recommendations for its wider implementation…(More)”.

Modeling Cities and Regions as Complex Systems

Curated on Posted on by Stefaan Verhulst

Book by Roger White, Guy Engelen and Inge Uljee: “Cities and regions grow (or occasionally decline), and continuously transform themselves as they do so. This book describes the theory and practice of modeling the spatial dynamics of urban growth and transformation. As cities are complex, adaptive, self-organizing systems, the most appropriate modeling framework is one based on the theory of self-organizing systems—an approach already used in such fields as physics and ecology. The book presents a series of models, most of them developed using cellular automata (CA), which are inherently spatial and computationally efficient. It also provides discussions of the theoretical, methodological, and philosophical issues that arise from the models. A case study illustrates the use of these models in urban and regional planning. Finally, the book presents a new, dynamic theory of urban spatial structure that emerges from the models and their applications.

The models are primarily land use models, but the more advanced ones also show the dynamics of population and economic activities, and are integrated with models in other domains such as economics, demography, and transportation. The result is a rich and realistic representation of the spatial dynamics of a variety of urban phenomena. The book is unique in its coverage of both the general issues associated with complex self-organizing systems and the specifics of designing and implementing models of such systems…(More)”.