Scientists argue for more FDA oversight of healthcare AI tools
Peer-Reviewed Publication
Updates every hour. Last Updated: 13-Jul-2025 21:11 ET (14-Jul-2025 01:11 GMT/UTC)
An agile, transparent, and ethics-driven oversight system is needed for the U.S. Food and Drug Administration (FDA) to balance innovation with patient safety when it comes to artificial intelligence-driven medical technologies. That is the takeaway from a new report issued to the FDA, published this week in the open-access journal PLOS Medicine by Leo Celi of the Massachusetts Institute of Technology, and colleagues.
A bi-objective model applies Data Envelopment Analysis to educational indicators, helping identify realistic, gender-balanced improvement targets.
Pregnant women are more often uninsured and have worse access to routine medical care in states that ban (or restrict) abortion care, according to a new study appearing in the American Journal of Preventive Medicine, published by Elsevier, from researchers at Harvard Medical School, the City University of New York’s Hunter College, and other institutions. The researchers also link the deficiencies in pregnancy coverage and care to abortion-ban/restriction states’ skimpy Medicaid programs.
Tech sector carbon emissions continued their rise in recent years, fueled by rapid advances in artificial intelligence (AI) and data infrastructure, according to the ITU-WBA Greening Digital Companies 2025 report.
Abstract
Purpose – This study aims to investigate the relationship between climate policy uncertainty (CPU) and corporate environmental, social and governance (ESG) performance. We attempt to uncover the underlying rationale of how CPU influences corporate ESG performance and provides empirical evidence for companies’ strategic enhancement of ESG performance with risk reduction objectives.
Design/methodology/approach –We conduct a regression analysis using panel data from 4,490 Chinese listed companies spanning the period from 2011 to 2022. In addition, we use propensity score matching analysis (PSM), two-stage least squares (2SLS), system generalized method of moments (sys-GMM) and difference-indifferences (DID) methods to analyze the enterprise systematic risk.
Findings – The empirical findings reveal a positive correlation between CPU and corporate ESG performance, with a stronger effect observed in non-state-owned enterprises, heavy-polluting industries and those facing fierce market competition and strict environmental regulation. Mechanism analysis suggests that as CPU increases, companies with higher systemic risk tend to improve ESG performance more significantly, highlighting risk mitigation as a primary motive. Robustness tests further validate the consistency of our conclusions. Additionally, we find that enhancing ESG performance helps mitigate the risks and improve total factor productivity arising from the increased CPU.
Originality/value – This study examines the impact of CPU on the ESG performance of Chinese listed companies and its underlying logic. The conclusions of this paper provide important policy references for coordinated development and security, as well as for effectively mitigating the adverse impact of CPU. We hope to offer insights for companies to identify potential risk factors, thereby enhancing their level of sustainable development and sense of environmental responsibility.