A new viewpoint article published in JMIR Mental Health argues that AI systems should evaluate the reliability of human training and feedback data to improve safety in mental health applications.

Researchers have proposed a new conceptual framework called “Health Elements” that positions digital technologies and AI as core structural drivers of health alongside biological, behavioral, social, and environmental factors. Published in Health Data Science, the framework argues that health outcomes emerge from dynamic interactions across multiple domains rather than from isolated risk factors alone. The study reflects growing recognition that digital systems—including algorithms, wearable devices, AI-enabled diagnostics, and health data infrastructures—are increasingly shaping health behaviors, access to care, and population-level outcomes.

The authors also discuss how multimodal health data integration, complex systems science, and AI-based analytical methods could support more adaptive public health and clinical decision-making. At the same time, they warn that algorithmic bias, digital inequity, and governance challenges may reinforce existing health disparities if ethical safeguards are not built into future digital health systems. An accompanying editorial describes the framework as a significant extension of traditional Social Determinants of Health models for the digital era.

As artificial intelligence systems become increasingly sophisticated, questions once confined to philosophy are rapidly entering mainstream scientific and public debate: Can AI possess consciousness? Could animals, organoids, or even fetuses have subjective experiences?

A research team led by Director Hakwan LAU of the Center for Neuroscience Imaging Research within the Institute for Basic Science (IBS), together with collaborators from the Université de Montréal and New York University, has published a new analysis arguing that current scientific methods may not yet be capable of reliably answering such questions. The paper critically examines how consciousness is currently studied in neuroscience and argues that many widely used experimental approaches fail to clearly distinguish subjective experience from general information processing.

Average support for gender equality worldwide has plateaued, in part because of higher population growth in countries where support is low and higher fertility among those with less egalitarian views.