Stefaan Verhulst
Article by James Evans and Eamon Duede: “With the emergence of AI in science, we are witnessing the prelude to a curious inversion – our human ability to instrumentally control nature is beginning to outpace human understanding of nature, and in some instances, appears possible without understanding at all. With rapid adoption of AI across all scientific disciplines, what does this mean for the future of scientific inquiry? And what comes after science?…Historically, human curiosity motivated the search to increase our scientific understanding of nature, driving us to develop new methods (including science itself), which often also yielded increased control. Algorithms, understood as tools, were never invested with the same capacity. In the emerging new era, entire regions of the scientific enterprise may not yield the same degree of human understanding despite improved control. Such a result has the potential to reduce the curiosity that drives us to seek out new questions, methods, and solutions, attenuating scientist engagement. Moreover, although algorithms for science have increased in their decision-making capacity, only a few have explicitly sought to invest them with flexibility and explicitly encoded curiosity for sustained performance.
If successful, science “after science” must rely increasingly on human curiosity..(More)”.
Book by Brian Potter: “Efficiency is the engine of civilization. But where do improvements in production efficiency come from? In The Origins of Efficiency, Brian Potter argues that improving production efficiency—finding ways to produce goods and services in less time, with less labor, using fewer resources—is the force behind some of the most consequential changes in human history. He examines the fundamental characteristics of a production process and how each can be made faster, cheaper, and more reliable, with detailed examples from a range of industries: steel and semiconductors, wind turbines and container shipping, Tesla and the Ford Model T, and more. The Origins of Efficiency is a comprehensive companion for anyone seeking to understand how we arrived at this age of material abundance—and how we can push efficiency improvements into domains like housing, medicine, and education, where much work is left to be done…(More)”.
Paper by Sarah McKenna et al: “Co-production of research, where researchers and experts by experience work as equal partners throughout a research project, can improve the quality, relevance, implementation and impact of research. However, there is limited evidence on methods for successful co-production in data-intensive research with underserved groups. In partnership with the charity Voice of Young People in Care (VOYPIC) and a group of care experienced young people, the Administrative Data Research Centre Northern Ireland (ADRC NI) piloted and evaluated a co-production approach in a research project that used linked administrative data to examine the association between care experience and mental ill health and mortality.
The aim of this paper is to report the impact of co-production using the pilot as a case study, and assess the mechanisms involved against published principles of co-production. Additionally, we consider if co-production in this context is a special case that warrants bespoke guidance…(More)”.
Book by Michelle A. Amazeen: “We often blame social media for the rampant problem of disinformation, but mainstream news media is also at fault. Not only do news outlets disguise paid content to look like online news articles, a practice called “native advertising,” but new research suggests that this form of advertising even influences the real journalism that appears next to it—both perceptions of the journalism as well as its actual substance. In Content Confusion, Michelle Amazeen explores the origins and evolution of this mainstream media practice, how it affects audiences and the industry, and what the implications are for an accurately informed public.
For policymakers, in particular, the book highlights the long-standing principles from governmental regulation as well as industry professional codes that support clear identification of the provenance of content, an issue that will no doubt intensify with the release of generative artificial intelligence in the wild…(More)”.
Report by the Tony Blair Institute: “Forests are indispensable global life-support systems: they regulate our climate, purify our air and water, safeguard biodiversity, and sustain the livelihoods of millions. Yet they are vanishing at unprecedented rates. Illegal logging and mining, agricultural expansion, and climate change are degrading ecosystems and biodiversity, threatening rural livelihoods, and undermining climate stability. At the same time, rapid advances in digital technologies, particularly artificial intelligence, are opening new frontiers for conservation. While not a silver bullet, digital solutions can serve as powerful enablers, providing better understanding, faster intelligence and greater effectiveness in forest action.
The Digital Tree framework presented in this report illustrates how components of digital and AI solutions for forestry are interconnected and mutually reinforcing. The roots represent enabling foundations such as connectivity, secure data ecosystems and computing power. The trunk encompasses core technologies that transform the ways in which forest data is captured, including satellites, drones, sensors and robotics. The branches represent analytics powered by AI and machine learning (ML), which convert raw data into actionable insights for a better understanding of current forest conditions, and how to link changes to their drivers, anticipate future risks and optimise operations. The canopy represents myriad real-life applications being developed to enable stronger forest outcomes. Finally, the nutrients represent just and inclusive forest stewardship – embedding the knowledge systems of indigenous peoples and local communities (IPLC), enabling their participation in technology development and data collection, and ensuring benefits flow back to the communities that safeguard forests. This digital ecosystem is self-reinforcing, where improvements in one area strengthen the whole…(More)”
The Digital Tree Structure
Paper by J. Nathan Matias and Megan Price: “As AI systems from decision-making algorithms to generative AI are deployed more widely, computer scientists and social scientists alike are being called on to provide trustworthy quantitative evaluations of AI safety and reliability. These calls have included demands from affected parties to be given a seat at the table of AI evaluation. What, if anything, can public involvement add to the science of AI? In this perspective, we summarize the sociotechnical challenge of evaluating AI systems, which often adapt to multiple layers of social context that shape their outcomes. We then offer guidance for improving the science of AI by engaging lived-experience experts in the design, data collection, and interpretation of scientific evaluations. This article reviews common models of public engagement in AI research alongside common concerns about participatory methods, including questions about generalizable knowledge, subjectivity, reliability, and practical logistics. To address these questions, we summarize the literature on participatory science, discuss case studies from AI in healthcare, and share our own experience evaluating AI in areas from policing systems to social media algorithms. Overall, we describe five parts of any quantitative evaluation where public participation can improve the science of AI: equipoise, explanation, measurement, inference, and interpretation. We conclude with reflections on the role that participatory science can play in trustworthy AI by supporting trustworthy science…(More)”.
OECD Report: “Personal health data (PHD) are transforming how individuals engage with health systems, creating new opportunities for trust, innovation, and improving access and quality of care. This report examines how OECD countries enable individuals to access, manage, and share their health information across digital platforms and patient portals. Drawing from in-depth interviews with national authorities in Australia, Denmark, Finland, Japan, Korea, and the United Kingdom, the paper analyses policy, technical, and governance enablers that underpin equitable access to personal health data. It identifies leading practices in interoperability, data architecture, privacy, consent, digital identity, and patient engagement. Countries with mature ecosystems demonstrated consistent public trust frameworks, integration across sectors, and strong legislative foundations balancing privacy with data interoperability and sharing. As healthcare becomes increasingly digital and the availability of patient-generated data grows, ensuring that individuals can securely access and use their own health data will be critical for future-ready, data-driven, and person-centred health systems…(More)”.
Article by Mansoor Al Mansoori and Noura Al Ghaithi: “For more than a decade, global leaders have recognized the rising burden of chronic, non-communicable diseases (NCDs) such as heart disease, diabetes, obesity and cancer. These conditions are the leading cause of death globally – accounting for 71% of all deaths – and represent the most costly, preventable health challenge of our time.
Abu Dhabi, however, is establishing a new global benchmark for health, demonstrating that prevention at population scale is possible. Advances in digitalization, AI, multimodal data and life sciences technology are making it possible to move decisively from reactive “sick care” to predictive, proactive and personalized healthcare…At the core of its digital health transformation lies a unified strategy: Predict, Prevent and Act to Cure and to Restore. This is powered by Abu Dhabi’s Intelligent Health System, which integrates medical records, insurance data, genomics, environmental and lifestyle data into a fully sovereign, privacy-protected ecosystem.
Abu Dhabi’s Predict, Prevent and Act to Cure and to Restore healthy system framework.Image: DOH Abu Dhabi
This infrastructure is powered by platforms like Malaffi, the region’s first health information exchange, connecting 100% of the emirate’s public and private healthcare providers and insurers with real-time access to patient histories, enabling more coordinated, efficient and patient-centred care and reducing system level costs for diagnostics.
Meanwhile, Sahatna, a mobile app used by more than 800,000 residents, empowers the community members to take ownership of their health. It provides secure access to personal health data, enables proactive appointment booking across the ecosystem, instant telehealth consultations, wellness tracking and behavioural nudges toward prevention. This plays a critical role in simplifying personal health, helping to shift the public’s mindset from reactive treatment to self-led prevention…(More)”.
Article by Kathy Talkington: “…Before the advent of vaccines, antibiotics, and modern sanitation, infectious diseases were the leading killers. But today, chronic diseases such as diabetes, hypertension, and asthma account for 70% of deaths and 86% of health care expenses in the United States. Yet the clinical data that doctors must report is still largely restricted to infectious diseases.
So, if doctors aren’t required to report chronic disease data and cannot feasibly do so, where can public health agencies turn? One major source is insurance providers. They collect information daily on the types of illnesses that patients have, the treatments being recommended, and the medications being prescribed. Insurance providers use this data to determine reimbursement rates, assess the quality of care, and guide treatment, but public health agencies do not have ready access to this information.
To help overcome this gap, The Pew Charitable Trusts recently launched a project to build data-driven partnerships between state public health agencies and their Medicaid counterparts. Why Medicaid? First, as the nation’s largest single payer, it can provide public health agencies with a large pool of claims data. Second, Medicaid serves people who would benefit most by more effective public health programs, including families with low incomes, people with disabilities, and older adults. And, lastly, Medicaid influences the practices of two critical constituencies: private insurers that contract with Medicaid and the 70% of doctors who accept Medicaid payments…(More)”.
Paper by Chinasa T. Okolo: “The increasing development of machine learning (ML) models and adoption of artificial intelligence (AI) tools, particularly generative AI, has dramatically shifted practices around data, spurring the development of new industries centered around data labeling and revealing new forms of exploitation, including illegal data scraping for AI training datasets. These new complexities around data production, refinement, and use have also impacted African countries, elevating a need for comprehensive regulation and enforcement measures. While 38/55 African Union (AU) Member States have existing data protection regulations, there is a wide disparity in the comprehensiveness and quality of these regulations and in the ability of individual countries to enact sufficient protections against data privacy violations. Thus, to enable effective data governance, AU Member States must enact comprehensive data protection regulations and reform existing data governance measures to cover aspects such as data quality, privacy, responsible data sharing, transparency, and data worker labor protections. This paper analyzes data governance measures in Africa, outlines data privacy violations across the continent, and examines regulatory gaps imposed by a lack of comprehensive data governance to outline the sociopolitical infrastructure required to bolster data governance capacity.
This work introduces the RICE Data Governance Framework, which aims to operationalize comprehensive data governance in Africa by outlining best measures for data governance policy
reform, integrating revamped policies, increasing continentalwide cooperation in AI governance, and improving enforcement actions against data privacy violations…(More)”