Paper by Angeliki Kerasidou & Charalampia (Xaroula) Kerasidou: “It is widely acknowledged that trust plays an important role for the acceptability of data sharing practices in research and healthcare, and for the adoption of new health technologies such as AI. Yet there is reported distrust in this domain. Although in the UK, the NHS is one of the most trusted public institutions, public trust does not appear to accompany its data sharing practices for research and innovation, specifically with the private sector, that have been introduced in recent years. In this paper, we examine the question of, what is it about sharing NHS data for research and innovation with for-profit companies that challenges public trust? To address this question, we draw from political theory to provide an account of public trust that helps better understand the relationship between the public and the NHS within a democratic context, as well as, the kind of obligations and expectations that govern this relationship. Then we examine whether the way in which the NHS is managing patient data and its collaboration with the private sector fit under this trust-based relationship. We argue that the datafication of healthcare and the broader ‘health and wealth’ agenda adopted by consecutive UK governments represent a major shift in the institutional character of the NHS, which brings into question the meaning of public good the NHS is expected to provide, challenging public trust. We conclude by suggesting that to address the problem of public trust, a theoretical and empirical examination of the benefits but also the costs associated with this shift needs to take place, as well as an open conversation at public level to determine what values should be promoted by a public institution like the NHS….(More)”.
Unleashing the power of data for electric vehicles and charging infrastructure
Report by Thomas Deloison: “As the world moves toward widespread electric vehicle (EV) adoption, a key challenge lies ahead: deploying charging infrastructure rapidly and effectively. Solving this challenge will be essential to decarbonize transport, which has a higher reliance on fossil fuels than any other sector and accounts for a fifth of global carbon emissions. However, the companies and governments investing in charging infrastructure face significant hurdles, including high initial capital costs and difficulties related to infrastructure planning, permitting, grid connections and grid capacity development.
Data has the power to facilitate these processes: increased predictability and optimized planning and infrastructure management go a long way in easing investments and accelerating deployment. Last year, members of the World Business Council for Sustainable Development (WBCSD) demonstrated that digital solutions based on data sharing could reduce carbon emissions from charging by 15% and unlock crucial grid capacity and capital efficiency gains.
Exceptional advances in data, analytics and connectivity are making digital solutions a potent tool to plan and manage transport, energy and infrastructure. Thanks to the deployment of sensors and the rise of connectivity, businesses are collecting information faster than ever before, allowing for data flows between physical assets. Charging infrastructure operators, automotive companies, fleet operators, energy providers, building managers and governments collect insights on all aspects of electric vehicle charging infrastructure (EVCI), from planning and design to charging experiences at the station.
The real value of data lies in its aggregation. This will require breaking down siloes across industries and enabling digital collaboration. A digital action framework released by WBCSD, in collaboration with Arcadis, Fujitsu and other member companies and partners, introduces a set of recommendations for companies and governments to realize the full potential of digital solutions and accelerate EVCI deployments:
- Map proprietary data, knowledge gaps and digital capacity across the value chain to identify possible synergies. The highest value potential from digital solutions will lie at the nexus of infrastructure, consumer behavior insights, grid capacity and transport policy. For example, to ensure the deployment of charging stations where they will be most needed and at the right capacity level, it is crucial to plan investments within energy grid capacity, spatial constraints and local projected demand for EVs.
- Develop internal data collection and storage capacity with due consideration for existing structures for data sharing. A variety of schemes allow actors to engage in data sharing or monetization. Yet, their use is limited by mismatched use of data standards and specification and process uncertainty. Companies must build a strong understanding of these structures internally by providing internal training and guidance, and invest in sound data collection, storage and analysis capacity.
- Foster a policy environment that supports digital collaboration across sectors and industries. Digital policies must provide incentives and due diligence frameworks to guide data exchanges across industries and support the adoption of common standards and protocols. For instance, it will be crucial to integrate linkages with energy systems and infrastructure beyond roads in the rollout of the European mobility data space…(More)”.
How Statisticians Should Grapple with Privacy in a Changing Data Landscape
Article by Joshua Snoke, and Claire McKay Bowen: “Suppose you had a data set that contained records of individuals, including demographics such as their age, sex, and race. Suppose also that these data contained additional in-depth personal information, such as financial records, health status, or political opinions. Finally, suppose that you wanted to glean relevant insights from these data using machine learning, causal inference, or survey sampling adjustments. What methods would you use? What best practices would you ensure you followed? Where would you seek information to help guide you in this process?…(More)”
Attacks on Tax Privacy: How the Tax Prep Industry Enabled Meta to Harvest Millions of Taxpayers’ Sensitive Data
Congressional Report: “The investigation revealed that:
- Tax preparation companies shared millions of taxpayers’ data with Meta, Google, and other Big Tech firms: The tax prep companies used computer code – known as pixels – to send data to Meta and Google. While most websites use pixels, it is particularly reckless for online tax preparation websites to use them on webpages where tax return information is entered unless further steps are taken to ensure that the pixels do not access sensitive information. TaxAct, TaxSlayer, and H&R Block confirmed that they had used the Meta Pixel, and had been using it “for at least a couple of years” and all three companies had been using Google Analytics (GA) for even longer.
- Tax prep companies shared extraordinarily sensitive personal and financial information with Meta, which used the data for diverse advertising purposes: TaxAct, H&R Block, and TaxSlayer each revealed, in response to this Congressional inquiry, that they shared taxpayer data via their use of the Meta Pixel and Google’s tools. Although the tax prep companies and Big Tech firms claimed that all shared data was anonymous, the FTC and experts have indicated that the data could easily be used to identify individuals, or to create a dossier on them that could be used for targeted advertising or other purposes.
- Tax prep companies and Big Tech firms were reckless about their data sharing practices and their treatment of sensitive taxpayer data: The tax prep companies indicated that they installed the Meta and Google tools on their websites without fully understanding the extent to which they would send taxpayer data to these tech firms, without consulting with independent compliance or privacy experts, and without full knowledge of Meta’s use of and disposition of the data.
- Tax prep companies may have violated taxpayer privacy laws by sharing taxpayer data with Big Tech firms: Under the law, “a tax return preparer may not disclose or use a taxpayer’s tax return information prior to obtaining a written consent from the taxpayer,” – and they failed to do so when it came to the information that was turned over to Meta and Google. Tax prep companies can also turn over data to “auxiliary service providers in connection with the preparation of a tax return.” But Meta and Google likely do not meet the definition of “auxiliary service providers” and the data sharing with Meta was for advertising purposes – not “in connection with the preparation of a tax return.”…(More)”.
Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology
Paper by Nikhil Agarwal, Alex Moehring, Pranav Rajpurkar & Tobias Salz: “While Artificial Intelligence (AI) algorithms have achieved performance levels comparable to human experts on various predictive tasks, human experts can still access valuable contextual information not yet incorporated into AI predictions. Humans assisted by AI predictions could outperform both human-alone or AI-alone. We conduct an experiment with professional radiologists that varies the availability of AI assistance and contextual information to study the effectiveness of human-AI collaboration and to investigate how to optimize it. Our findings reveal that (i) providing AI predictions does not uniformly increase diagnostic quality, and (ii) providing contextual information does increase quality. Radiologists do not fully capitalize on the potential gains from AI assistance because of large deviations from the benchmark Bayesian model with correct belief updating. The observed errors in belief updating can be explained by radiologists’ partially underweighting the AI’s information relative to their own and not accounting for the correlation between their own information and AI predictions. In light of these biases, we design a collaborative system between radiologists and AI. Our results demonstrate that, unless the documented mistakes can be corrected, the optimal solution involves assigning cases either to humans or to AI, but rarely to a human assisted by AI…(More)”.
Weather Warning Inequity: Lack of Data Collection Stations Imperils Vulnerable People
Article by Chelsea Harvey: “Devastating floods and landslides triggered by extreme downpours killed hundreds of people in Rwanda and the Democratic Republic of Congo in May, when some areas saw more than 7 inches of rain in a day.
Climate change is intensifying rainstorms throughout much of the world, yet scientists haven’t been able to show that the event was influenced by warming.
That’s because they don’t have enough data to investigate it.
Weather stations are sparse across Africa, making it hard for researchers to collect daily information on rainfall and other weather variables. The data that does exist often isn’t publicly available.
“The main issue in some countries in Africa is funding,” said Izidine Pinto, a senior researcher on weather and climate at the Royal Netherlands Meteorological Institute. “The meteorological offices don’t have enough funding.”
There’s often too little money to build or maintain weather stations, and strapped-for-cash governments often choose to sell the data they do collect rather than make it free to researchers.
That’s a growing problem as the planet warms and extreme weather worsens. Reliable forecasts are needed for early warning systems that direct people to take shelter or evacuate before disasters strike. And long-term climate data is necessary for scientists to build computer models that help make predictions about the future.
The science consortium World Weather Attribution is the latest research group to run into problems. It investigates the links between climate change and individual extreme weather events all over the globe. In the last few months alone, the organization has demonstrated the influence of global warming on extreme heat in South Asia and the Mediterranean, floods in Italy, and drought in eastern Africa.
Most of its research finds that climate change is making weather events more likely to occur or more intense.
The group recently attempted to investigate the influence of climate change on the floods in Rwanda and Congo. But the study was quickly mired in challenges.
The team was able to acquire some weather station data, mainly in Rwanda, Joyce Kimutai, a research associate at Imperial College London and a co-author of the study, said at a press briefing announcing the findings Thursday. But only a few stations provided sufficient data, making it impossible to define the event or to be certain that climate model simulations were accurate…(More)”.
Asymmetries: participatory democracy after AI
Article by Gianluca Sgueo in Grand Continent (FR): “When it comes to AI, the scientific community expresses divergent opinions. Some argue that it could enable democratic governments to develop more effective and possibly more inclusive policies. Policymakers who use AI to analyse and process large volumes of digital data would be in a good position to make decisions that are closer to the needs and expectations of communities of citizens. In the view of those who view ‘government by algorithms’ favourably, AI creates the conditions for more effective and regular democratic interaction between public actors and civil society players. Other authors, on the other hand, emphasise the many critical issues raised by the ‘implantation’ of such a complex technology in political and social systems that are already highly complex and problematic. Some authors believe that AI could undermine even democratic values, by perpetuating and amplifying social inequalities and distrust in democratic institutions – thus weakening the foundations of the social contract. But if everyone is right, is no one right? Not necessarily. These two opposing conceptions give us food for thought about the relationship between algorithms and democracies…(More)”.
Next Generation Virtual Worlds: Societal, Technological, Economic and Policy Challenges for the EU
JRC Report: “This report provides an overview of the opportunities that next generation virtual worlds may bring in different sectors such as education, manufacturing, health, and public services among others. This potential will need to be harnessed in light of the challenges the EU may need to address along societal, technological, and economic and policy dimensions. We apply a multidisciplinary and multisectoral perspective to our analysis, covering technical, social, industrial, political and economic facets. The report also offers a first techno-economic analysis of the digital ecosystem identifying current key players in different subdomains related to virtual worlds…(More)”.
COVID-19 digital contact tracing worked — heed the lessons for future pandemics
Article by Marcel Salathé: “During the first year of the COVID-19 pandemic, around 50 countries deployed digital contact tracing. When someone tested positive for SARS-CoV-2, anyone who had been in close proximity to that person (usually for 15 minutes or more) would be notified as long as both individuals had installed the contact-tracing app on their devices.
Digital contact tracing received much media attention, and much criticism, in that first year. Many worried that the technology provided a way for governments and technology companies to have even more control over people’s lives than they already do. Others dismissed the apps as a failure, after public-health authorities hit problems in deploying them.
Three years on, the data tell a different story.
The United Kingdom successfully integrated a digital contact-tracing app with other public-health programmes and interventions, and collected data to assess the app’s effectiveness. Several analyses now show that, even with the challenges of introducing a new technology during an emergency, and despite relatively low uptake, the app saved thousands of lives. It has also become clearer that many of the problems encountered elsewhere were not to do with the technology itself, but with integrating a twenty-first-century technology into what are largely twentieth-century public-health infrastructures…(More)”.
Government at a Glance
OECD Report: “Published every two years, Government at a Glance provides reliable, internationally comparable indicators on government activities and their results in OECD countries. Where possible, it also reports data for selected non-member countries. It includes input, process, output and outcome indicators as well as contextual information for each country.
Each indicator in the publication is presented in a user-friendly format, consisting of graphs and/or charts illustrating variations across countries and over time, brief descriptive analyses highlighting the major findings conveyed by the data, and a methodological section on the definition of the indicator and any limitations in data comparability…(More)”.