Automating Public Services: Learning from Cancelled Systems

Curated on Posted on by Stefaan Verhulst

Report by Joanna Redden, Jessica Brand, Ina Sander and Harry Warne: “Pressure on public finances means that governments are trying to do more with less. Increasingly, policymakers are turning to technology to cut costs. But what if this technology doesn’t work as it should?

This report looks at the rise and fall of automated decision systems (ADS). If you’ve tried to get medical advice over the phone recently you’ve got some experience of an ADS – a computer system or algorithm designed to help or replace human decision making. These sorts of systems are being used by governments to consider when and how to act. The stakes are high. For example, they’re being used to try to detect crime and spot fraud, and to determine whether child protective services should act.

This study identifies 61 occasions across Australia, Canada, Europe, New Zealand and the United States when ADS projects were cancelled or paused. From this evidence, we’ve made recommendations designed to increase transparency and to protect communities and individuals…(More)”.

Mini Data Centers heat local swimming pools for free

Curated on Posted on by Stefaan Verhulst

Springwise: “It is now well-understood that data centres consume vast amounts of energy. This is because the banks of servers in the data centres require a lot of cooling, which, in turn, uses a lot of energy. But one data centre has found a use for all the heat that it generates, a use that could also help public facilities such as swimming pools save money on their energy costs.

Deep Green, which runs data centres, has developed small edge data centres that can be installed locally and divert some of their excess heat to warm leisure centres and public swimming pools. The system, dubbed a “digital boiler”, involves immersing central processing unit (CPU) servers in special cooling tubs, which use oil to remove heat from the servers. This oil is then passed through a heat exchanger, which removes the heat and uses it to warm buildings or swimming pools.

Photo source Deep Green

The company says the heat donation from one of its digital boilers will cut a public swimming pool’s gas requirements by around 70 per cent, saving leisure centres thousands of pounds every year while also drastically reducing carbon emissions. Deep Green pays for the electricity it uses and donates the heat for free. This is a huge benefit, as Britain’s public swimming pools are facing massive increases in heating bills, which is causing many to close or restrict their hours…(More)”.

Policy Guide on Social Impact Measurement for the Social and Solidarity Economy

Curated on Posted on by Stefaan Verhulst

OECD Report: “As social and solidarity economy (SSE) entities are increasingly requested to demonstrate their positive contribution to society, social impact measurement can help them understand the additional, net value generated by their activities, in the pursuit of their mission and beyond. Policy plays an important role to facilitate a conducive environment to unlock the uptake of social impact measurement among SSE actors. Drawing on a mapping exercise and good practice examples from over 33 countries, this international policy guide navigates how policy makers can support social impact measurement for the social and solidarity economy by: (i) improving the policy framework, (ii) delivering guidance, (iii) building evidence and (iv) supporting capacity. Building on the earlier publication Social Impact Measurement for the Social and Solidarity Economy released in 2021 the guide is published under the framework of the OECD Global Action “Promoting Social and Solidarity Economy Ecosystems”, funded by the European Union’s Foreign Partnership Instrument…(More)”.

Building Trust in AI: A Landscape Analysis of Government AI Programs

Curated on Posted on by Stefaan Verhulst

Paper by Susan Ariel Aaronson: “As countries around the world expand their use of artificial intelligence (AI), the Organisation for Economic Co-operation and Development (OECD) has developed the most comprehensive website on AI policy, the OECD.AI Policy Observatory. Although the website covers public policies on AI, the author of this paper found that many governments failed to evaluate or report on their AI initiatives. This lack of reporting is a missed opportunity for policy makers to learn from their programs (the author found that less than one percent of the programs listed on the OECD.AI website had been evaluated). In addition, the author found discrepancies between what governments said they were doing on the OECD.AI website and what they reported on their own websites. In some cases, there was no evidence of government actions; in other cases, links to government sites did not work. Evaluations of AI policies are important because they help governments demonstrate how they are building trust in both AI and AI governance and that policy makers are accountable to their fellow citizens…(More)”.

Data Collaborative Case Study: NYC Recovery Data Partnership

Curated on Posted on by Stefaan Verhulst

Report by the Open Data Policy Lab (The GovLab): “In July 2020, following severe economic and social losses due to the COVID-19 pandemic, the administration of New York City Mayor Bill de Blasio announced the NYC Recovery Data Partnership. This data collaborative asked private and civic organizations with assets relevant to New York City to provide their data to the city. Senior city leaders from the First Deputy Mayor’s Office, the Mayor’s Office of Operations, Mayor’s Office of Information Privacy and Mayor’s Office of Data Analytics formed an internal coalition which served as trusted intermediaries, assessing agency requests from city agencies to use the data provided and allocating access accordingly. The data informed internal research conducted by various city agencies, including New York City Emergency Management’s Recovery Team and the NYC…(More)”Department of City Planning. The experience reveals the ability of crises to spur innovation, the value of responsiveness from both data users and data suppliers, and the importance of technical capacity, and the value of a network of peers. In terms of challenges, the experience also exposes the limitations of data, the challenges of compiling complex datasets, and the role of resource constraints.

Mapping Diversity

Curated on Posted on by Stefaan Verhulst

About: “Mapping Diversity is a platform for discovering key facts about diversity and representation in street names across Europe, and to spark a debate about who is missing from our urban spaces.

We looked at the names of 145,933 streets across 30 major European cities, located in 17 different countries. More than 90% of the streets named after individuals are dedicated to white men. Where did all the other inhabitants of Europe end up? The lack of diversity in toponymy speaks volumes about our past and contributes to shaping Europe’s present and future…(More)”.

Principles for effective beneficial ownership disclosure

Curated on Posted on by Stefaan Verhulst

Open Ownership: “The Open Ownership Principles (OO Principles) are a framework for considering the elements that influence whether the implementation of reforms to improve the transparency of the beneficial ownership of corporate vehicles will lead to effective beneficial ownership disclosure, that is, it generates high-quality and reliable data, maximising usability for users.

The OO Principles are intended to support governments implementing effective beneficial ownership transparency reforms and guide international institutions, civil society, and private sector actors in understanding and supporting reforms. They are a tool to identify and separate issues affecting implementation, and they provide a framework for assessing and improving existing disclosure regimes. If implemented together, the OO Principles enable disclosure systems to generate actionable and usable data across the widest range of policy applications of beneficial ownership data.

The nine principles are interdependent, but can be broadly grouped by the three main ways they improve data. The Definition, Coverage, and Detail principles enable data disclosure and collection. The Central register, Access, and Structured data principles facilitate data storage and auditability. Finally, the Verification, Up-to-date and historical records, and Sanctions and enforcement principles improve data quality and reliability….Download January 2023 version (translated versions are forthcoming)”

Whole of government innovation

Curated on Posted on by Stefaan Verhulst

Report by Geoff Mulgan: ‘Whole of government’ approaches – that aim to mobilise and align many ministries and agencies around a common challenge – have a long history. There have been notable examples during major wars, and around attempts to digitize societies, to cut energy use and to respond to the COVID-19 pandemic.

This paper has been prepared as part of a European Commission programme which I’m chairing looking at ‘whole of government innovation’ and working with national governments to help them better align their actions.

My paper – linked below – looks at the lessons of history. It outlines the many tools governments can use to achieve cross-cutting goals, linking R&D to law, regulation and procurement, and collaborating with business, universities and civil society. It argues that it is unwise to rely only on committees and boards. It shows how these choices link to innovation strategy and funding, including the relevance of half a century of experiment with moon-shots and missions.

The paper describes how the organisational challenges vary depending on the nature of the task; why governments need to avoid common technology or ‘STI trap’, of focusing only on hardware and not on social arrangements or business models; why constellations and flotillas of coordination are usually more realistic than true ‘whole of government approaches; the importance of mobilising hearts and minds as well as money and command.

Finally, it addresses the relevance of different approaches to current tasks such as the achievement of a net zero economy and society. The paper is shared as a working document – I’m keen to find new examples and approaches…(More)”.

How the Digital Transformation Changed Geopolitics

Curated on Posted on by Stefaan Verhulst

Paper by Dan Ciuriak: “In the late 2000s, a set of connected technological developments – introduction of the iPhone, deep learning through stacked neural nets, and application of GPUs to neural nets – resulted in the generation of truly astronomical amounts of data and provided the tools to exploit it. As the world emerged from the Great Financial Crisis of 2008-2009, data was decisively transformed from a mostly valueless by-product – “data exhaust” – to the “new oil”, the essential capital asset of the data-driven economy, and the “new plutonium” when deployed in social and political applications. This economy featured steep economies of scale, powerful economies of scope, network externalities in many applications, and pervasive information asymmetry. Strategic commercial policies at the firm and national levels were incentivized by the newfound scope to capture economic rents, destabilizing the rules-based system for trade and investment. At the same time, the new disruptive general-purpose technologies built on the nexus of Big Data, machine learning and artificial intelligence reconfigured geopolitical rivalry in several ways: by shifting great power rivalry onto new and critical grounds on which none had a decisive established advantage; by creating new vulnerabilities to information warfare in societies, especially open societies; and by enhancing the tools for social manipulation and the promotion of political personality cults. Machine learning, which essentially industrialized the very process of learning, drove an acceleration in the pace of innovation, which precipitated industrial policies driven by the desire to capture first mover advantage and by the fear of falling behind.

These developments provide a unifying framework to understand the progressive unravelling of the US-led global system as the decade unfolded, despite the fact that all the major innovations that drove the transition were within the US sphere and the US enjoyed first mover advantages. This is in stark contrast to the previous major economic transition to the knowledge-based economy, in which case US leadership on the key innovations extended its dominance for decades and indeed powered its rise to its unipolar moment. The world did not respond well to the changed technological and economic conditions and hence we are war: hot war, cold war, technological war, trade war, social war, and internecine political war. This paper focuses on the role of technological and economic conditions in shaping geopolitics, which is critical to understand if we are to respond to the current world disorder and to prepare to handle the coming transition in technological and economic conditions to yet another new economic era based on machine knowledge capital…(More)”.

Urban AI Guide

Curated on Posted on by Stefaan Verhulst

Guide by Popelka, S., Narvaez Zertuche, L., Beroche, H.: “The idea for this guide arose from conversations with city leaders, who were confronted with new technologies, like artificial intelligence, as a means of solving complex urban problems, but who felt they lacked the background knowledge to properly engage with and evaluate the solutions. In some instances, this knowledge gap produced a barrier to project implementation or led to unintended project outcomes.

The guide begins with a literature review, presenting the state of the art in research on urban artificial intelligence. It then diagrams and describes an “urban AI anatomy,” outlining and explaining the components that make up an urban AI system. Insights from experts in the Urban AI community enrich this section, illuminating considerations involved in each component. Finally, the guide concludes with an in-depth examination of three case studies: water meter lifecycle in Winnipeg, Canada, curb digitization and planning in Los Angeles, USA, and air quality monitoring in Vilnius, Lithuania. Collectively, the case studies highlight the diversity of ways in which artificial intelligence can be operationalized in urban contexts, as well as the steps and requirements necessary to implement an urban AI project.

Since the field of urban AI is constantly evolving, we anticipate updating the guide annually. Please consider filling out the contribution form, if you have an urban AI use case that has been operationalized. We may contact you to include the use case as a case study in a future edition of the guide.

As a continuation of the guide, we offer customized workshops on urban AI, oriented toward municipalities and other urban stakeholders, who are interested in learning more about how artificial intelligence interacts in urban environments. Please contact us if you would like more information on this program…(More)”.