This paper argues that a techno-philosophical reading of the EU AI Act provides insight into the long-term dynamics of data in AI systems, specifically, how the lifecycle from ingestion to deployment generates recursive value chains that challenge existing frameworks for Responsible AI. We introduce a conceptual tool to frame the AI pipeline, spanning data, training regimes, architectures, feature stores, and transfer learning. Using cross-disciplinary methods, we develop a technically grounded and philosophically coherent analysis of regulatory blind spots. Our central claim is that what remains absent from policymaking is an account of the dynamic of becoming that underpins both the technical operation and economic logic of AI. To address this, we advance a formal reading of AI inspired by Simondonian philosophy of technology, reworking his concept of individuation to model the AI lifecycle, including the pre-individual milieu, individuation, and individuated AI. To translate these ideas, we introduce futurity: the self-reinforcing lifecycle of AI, where more data enhances performance, deepens personalisation, and expands application domains. Futurity highlights the recursively generative, non-rivalrous nature of data, underpinned by infrastructures like feature stores that enable feedback, adaptation, and temporal recursion. Our intervention foregrounds escalating power asymmetries, particularly the tech oligarchy whose infrastructures of capture, training, and deployment concentrate value and decision-making. We argue that effective regulation must address these infrastructural and temporal dynamics, and propose measures including lifecycle audits, temporal traceability, feedback accountability, recursion transparency, and a right to contest recursive reuse.

You are free to share this article under the Attribution 4.0 International license. Infants outperform artificial intelligence in detecting what motivates other people's actions, according to a new study. The results, which highlight fundamental differences between cognition and computation, point to shortcomings in today's technologies and where improvements are needed for AI to more fully replicate human behavior. "Adults and even infants can easily make reliable inferences about what drives other people's actions," explains Moira Dillon, an assistant professor in New York University's psychology department and the senior author of the paper in the journal Cognition. "Current AI finds these inferences challenging to make." "The novel idea of putting infants and AI head-to-head on the same tasks is allowing researchers to better describe infants' intuitive knowledge about other people and suggest ways of integrating that knowledge into AI," she adds.

You are free to share this article under the Attribution 4.0 International license. Using machine learning to sift through the electronic health records of both mothers and newborns can predict how premature babies will fare in their first two months of life, researchers report. The new method, reported in the journal Science Translational Medicine, allows physicians to classify, at or before birth, which infants are likely to develop complications of prematurity. "Preterm birth is the single largest cause of death in children under age 5 worldwide." "This is a new way of thinking about preterm birth, placing the focus on individual health factors of the newborns rather than looking only at how early they are born," says senior author Nima Aghaeepour, an associate professor of anesthesiology, perioperative and pain medicine and of pediatrics Stanford University School of Medicine.

You are free to share this article under the Attribution 4.0 International license. Artificial intelligence can help identify biases in news reporting that we wouldn't otherwise see, researchers report. For a new study, researchers got a computer program to generate news coverage of COVID-19 using headlines from Canadian Broadcast Corporation (CBC) articles as prompts. They then compared the simulated news coverage to the actual reporting at the time. The findings show that CBC coverage was less focused on the medical emergency and more positively focused on personalities and geo-politics.

You are free to share this article under the Attribution 4.0 International license. Researchers have developed a new artificial-intelligence-based risk score that improves personalized care for female patients with heart attacks. Heart attacks are one of the leading causes of death worldwide, and women who suffer a heart attack have a higher mortality rate than men. This has been a matter of concern to cardiologists for decades and has led to controversy in the medical field about the causes and effects of possible gaps in treatment. The problem starts with the symptoms: unlike men, who usually experience chest pain with radiation to the left arm, a heart attack in women often manifests as abdominal pain radiating to the back or as nausea and vomiting.

You are free to share this article under the Attribution 4.0 International license. In 2020, Elon Musk said artificial intelligence would surpass human intelligence within five years, on its way to becoming "an immortal dictator." A new book says no way, not ever. The book, Why Machines Will Never Rule the World: Artificial Intelligence without Fear (Routledge, 2022), argues against the possibility of engineering machines that can surpass human intelligence. Coauthors are Barry Smith, professor in the philosophy department at the University at Buffalo and Jobst Landgrebe, senior research associate in the philosophy department and founder of Cognotekt, a German AI company.

You are free to share this article under the Attribution 4.0 International license. Cognitive behavioral therapy for chronic pain supported by artificial intelligence can yield the same results as programs delivered by therapists, a new study shows. Cognitive behavioral therapy (CBT) is an effective alternative to opioid painkillers for managing chronic pain. But getting patients to complete those programs is challenging, especially because psychotherapy often requires multiple sessions and mental health specialists are scarce. AI-supported therapy requires substantially less clinician time, making it more accessible to patients, the researchers report.

You are free to share this article under the Attribution 4.0 International license. Although artificial intelligence has a growing role in journalism, research finds that Americans don't know about AI's role in their lives--or their news. Technology has repeatedly transformed the news media industry--telegraph, radio, television, and then the internet. Yet despite these evolutions, technology remained the medium and human journalists the messengers. The introduction of AI has changed that model.

You are free to share this article under the Attribution 4.0 International license. Patients are 20% less likely to die of sepsis because a new AI system catches symptoms hours earlier than traditional methods, new research shows. The system scours medical records and clinical notes to identify patients at risk of life-threatening complications. The work, which could significantly cut patient mortality from one of the top causes of hospital deaths worldwide, is published in Nature Medicine and Nature Digital Medicine. "It is the first instance where AI is implemented at the bedside, used by thousands of providers, and where we're seeing lives saved," says Suchi Saria, founding research director of the Malone Center for Engineering in Healthcare at Johns Hopkins University, and lead author of the studies, which evaluated more than a half million patients over two years.

You are free to share this article under the Attribution 4.0 International license. Will artificial intelligence be a help or a hindrance in the response to climate change? In the journal Nature Climate Change, a team of experts in AI, climate change, and public policy present a framework for understanding the complex and multifaceted relationship of AI with greenhouse gas emissions and suggest ways to better align AI with climate change goals. "AI affects the climate in many ways, both positive and negative, and most of these effects are poorly quantified," says coauthor David Rolnick, assistant professor of computer science at McGill University and a core academic member of Mila – Quebec AI Institute. "For example, AI is being used to track and reduce deforestation, but AI-based advertising systems are likely making climate change worse by increasing the amount that people buy." "Climate change should be a key consideration when developing and assessing AI technologies," says Lynn Kaack, assistant professor of computer science and public policy at the Hertie School, and lead author of the report.