Paper by M. Fairbairn, and Z. Kish: “Open data is increasingly being promoted as a route to achieve food security and agricultural development. This article critically examines the promotion of open agri-food data for development through a document-based case study of the Global Open Data for Agriculture and Nutrition (GODAN) initiative as well as through interviews with open data practitioners and participant observation at open data events. While the concept of openness is striking for its ideological flexibility, we argue that GODAN propagates an anti-political, neoliberal vision for how open data can enhance agricultural development. This approach centers values such as private innovation, increased production, efficiency, and individual empowerment, in contrast to more political and collectivist approaches to openness practiced by some agri-food social movements. We further argue that open agri-food data projects, in general, have a tendency to reproduce elements of “data colonialism,” extracting data with minimal consideration for the collective harms that may result, and embedding their own values within universalizing information infrastructures…(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)”.
Russia Is Trying to Leave the Internet and Build Its Own
Article by Timmy Broderick: “Last week the Russian government tried to disconnect its Internet infrastructure from the larger global Web. This test of Russia’s “sovereign Internet” seemingly failed, causing outages that suggest the system is not ready for practical use.
“Sovereign Internet is not really a whole different Internet; it is more like a project that uses various tools,” says Natalia Krapiva, tech-legal counsel at the international digital-rights nonprofit Access Now. “It involves technology like deep packet inspection, which allows major filtering of the Internet and gives governments the ability to throttle certain connections and websites.” By cutting off access to sites such as Western social media platforms, the Russian government could restrict residents from viewing any source of information other than the country’s accepted channels of influence.
This method of curtailing digital freedom goes beyond Russia: other countries are also attempting to develop their own nationwide Internet. And if successful, these endeavors could fragment the World Wide Web. Scientific American talked with Krapiva over Zoom about the implications of this latest test, the motive behind Russia’s actions and the ways the push for a sovereign Internet affect the digital rights of all users…(More)”.
Just Citation
Paper by Amanda Levendowski: “Contemporary citation practices are often unjust. Data cartels, like Google, Westlaw, and Lexis, prioritize profits and efficiency in ways that threaten people’s autonomy, particularly that of pregnant people and immigrants. Women and people of color have been legal scholars for more than a century, yet colleagues consistently under-cite and under-acknowledge their work. Other citations frequently lead to materials that cannot be accessed by disabled people, poor people or the public due to design, paywalls or link rot. Yet scholars and students often understand citation practices as “just” citation and perpetuate these practices unknowingly. This Article is an intervention. Using an intersectional feminist framework for understanding how cyberlaws oppress and liberate oppressed, an emerging movement known as feminist cyberlaw, this Article investigates problems posed by prevailing citation practices and introduces practical methods that bring citation into closer alignment with the feminist values of safety, equity, and accessibility. Escaping data cartels, engaging marginalized scholars, embracing free and public resources, and ensuring that those resources remain easily available represent small, radical shifts that promote just citation. This Article provides powerful, practical tools for pursuing all of them…(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)”.
Open data for AI: what now?
UNESCO Report: “…A vast amount of data on environment, industry, agriculture health about the world is now being collected through automatic processes, including sensors. Such data may be readily available, but also are potentially too big for humans to handle or analyse effectively, nonetheless they could serve as input to AI systems. AI and data science techniques have demonstrated great capacity to analyse large amounts of data, as currently illustrated by generative AI systems, and help uncover formerly unknown hidden patterns to deliver actionable information in real-time. However, many contemporary AI systems run on proprietary datasets, but data that fulfil the criteria of open data would benefit AI systems further and mitigate potential hazards of the systems such as lacking fairness, accountability, and transparency.
The aim of these guidelines is to apprise Member States of the value of open data, and to outline how data are curated and opened. Member States are encouraged not only to support openness of high-quality data, but also to embrace the use of AI technologies and facilitate capacity building, training and education in this regard, including inclusive open data as well as AI literacy…(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)”.