While artificial intelligence (AI) is designed to enhance the quality of our lives, there is an increase in AI-mediated harm. Since AI systems operate semi-autonomously, neither their developers nor users typically intend or foresee such harm. Thus, it seems absurd to hold AI systems and stakeholders responsible, giving rise to a responsibility gap. To address this gap, researchers have now developed new notions of responsibility tailored to cover unintended and unforeseen consequences caused by AI.

A study by the University of Stuttgart, the California State University at Fullerton, and the Max Planck Institute for Intelligent Systems has found that there are benefits to representing one’s real-life disability through an avatar in virtual reality. The Metaverse is not just a technical platform, but also one for social interaction. Therefore, all users should be included in its development, including people with disabilities. The researchers appeal to companies to be more courageous in embracing diversity in virtual spaces as authentic self-representation allows people with disabilities to identify more strongly with their work.

Researchers have developed a novel Nickel-Cobalt bimetallic nanocomposite material. Its built-in dual electric field significantly enhances electromagnetic energy dissipation, achieving ultra-wideband absorption.

A highly efficient, wearable self-charging power system is reported, which consists of a triboelectric nanogenerator (TENG) with fabric coated by MXene paste as conductive layer and micro-supercapacitors (MSCs) with graphene films as electrode.

In a study now published in iScience, researchers from the University of Vienna (Austria), National Institute of Technology - Wakayama College (NITW; Japan), and Shimane University (Japan) present the largest cephalopod genome sequenced to date. Their analyses show that the vampire squid has retained parts of an ancient, squid-like chromosomal architecture, and thus revealing that modern octopuses evolved from squid-like ancestors.

Using a deep learning AI model, researchers identified the first-of-its-kind biomarker of chronic stress detectable through routine imaging, according to research being presented next week at the annual meeting of the Radiological Society of North America (RSNA).