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)”.
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)”.
Why Citizen-Driven Policy Making Is No Longer A Fringe Idea
Article by Tatjana Buklijas: “Deliberative democracy is a term that would have been met with blank stares in academic and political circles just a few decades ago.
Yet this approach, which examines ways to directly connect citizens with decision-making processes, has now become central to many calls for government reform across the world.
This surge in interest was firstly driven by the 2008 financial crisis. After the banking crash, there was a crisis of trust in democratic institutions. In Europe and the United States, populist political movements helped drive public feeling to become increasingly anti-establishment.
The second was the perceived inability of representative democracy to effectively respond to long-term, intergenerational challenges, such as climate change and environmental decline.
Within the past few years, hundreds of citizens’ assemblies, juries and other forms of ‘minipublics’ have met to learn, deliberate and produce recommendations on topics from housing shortages and covid-19 policies, to climate action.
One of the most recent assemblies in the United Kingdom was the People’s Plan for Nature that produced a vision for the future of nature, and the actions society must take to protect and renew it.
When it comes to climate action, experts argue that we need to move beyond showpiece national and international goal-setting, and bring decision-making closer to home.
Scholars say that that local and regional minipublics should be used much more frequently to produce climate policies, as this is where citizens experience the impact of the changing climate and act to make everyday changes.
While some policymakers are critical of deliberative democracy and see these processes as redundant to the existing deliberative bodies, such a national parliaments, others are more supportive. They view them as a way to get a better understanding of both what the public both thinks, and also how they might choose to implement change, after being given the chance to learn and deliberate on key questions.
Research has shown that the cognitive diversity of minipublics ensure a better quality of decision-making, in comparison to the more experienced, but also more homogenous traditional decision-making bodies…(More)”.
Engaging Scientists to Prevent Harmful Exploitation of Advanced Data Analytics and Biological Data
Proceedings from the National Academies of Sciences: “Artificial intelligence (AI), facial recognition, and other advanced computational and statistical techniques are accelerating advancements in the life sciences and many other fields. However, these technologies and the scientific developments they enable also hold the potential for unintended harm and malicious exploitation. To examine these issues and to discuss practices for anticipating and preventing the misuse of advanced data analytics and biological data in a global context, the National Academies of Sciences, Engineering, and Medicine convened two virtual workshops on November 15, 2022, and February 9, 2023. The workshops engaged scientists from the United States, South Asia, and Southeast Asia through a series of presentations and scenario-based exercises to explore emerging applications and areas of research, their potential benefits, and the ethical issues and security risks that arise when AI applications are used in conjunction with biological data. This publication highlights the presentations and discussions of the workshops…(More)”.