The BBVA Foundation Frontiers of Knowledge Awards in Economics, Finance and Management has gone in this eighteenth edition to Charles F. Manski for his pioneering contributions to the measurement of uncertainty in economic research and its application to public policy analysis. The professor at Northwestern University (Chicago, United States) is described by the committee as a “foundational figure” in the development of modern methods that have transformed how economists infer conclusions from data, report degrees of uncertainty in their models, and evaluate public policies in the face of incomplete evidence.

Join us on March 6-20 for the AI Art Biennale organized by SWPS University in Kraków. The program includes exhibitions, performances, artist talks, workshops, and a scientific conference.

A European consortium, led by the Institute of New Imaging Technologies (INIT) at the Universitat Jaume I in Castelló and comprising the University of Limassol (Cyprus), Save the Children Finland, All Digital (Belgium) and 8d-Games (the Netherlands), aims to promote the protection and exercise of children’s rights in online gaming environments by creating participatory mechanisms that foster digital literacy, strengthen mental wellbeing and embed practices grounded in children’s fundamental rights.

“The main purpose of FAIR GAME”, explains the research team, which met for two days at the public university in Castelló, “is to make children’s rights visible, actionable and enforceable in one of the least regulated digital environments”, because its goal “is not only to mitigate risk, but to reorient the way the gaming ecosystem defines safety and responsibility”. For this reason, they add, it “seeks to bring about cultural and structural change in order to influence gaming platform policies and standards”.

Current 3D anomaly detection techniques often prove insufficient for noisy industrial scans. In a new study, researchers from Shibaura Institute of Technology, Japan, and FPT University, Vietnam, have developed Vote3D-AD as an innovative solution. The single-pass framework trains exclusively on defect-free data and utilizes the Varied Defect Synthesis pseudo-anomaly generator and a vote-and-cluster architecture to outperform state-of-the-art alternatives on various benchmarks. It is expected to further streamline inspection pipelines.