In an increasingly digital world, millions of disabled people are being systematically excluded from critical services every day, from their medical records to bank accounts to emergency response systems.

New research in Contemporary Economic Policy reveals that generative artificial intelligence tools like GitHub Copilot may lead to more, not fewer, jobs in the software engineering workforce.

Language models like ChatGPT are not neutral. Without our realising it, they can absorb all kinds of bias – for example around gender and ethnicity – which then become increasingly embedded in the model. According to AI researcher Oskar van der Wal, we need different kinds of measurements to detect these biases so that they can be removed from the models. In his doctoral thesis, he shows how this can be done. On 29 April, he will defend his thesis at the University of Amsterdam.

A team of researchers from USC in collaboration with the California Institute of Technology (Caltech) have received approximately $7.8 million from the Advanced Research Projects Agency for Health (ARPA-H) Ocular Laboratory for Analysis of Biomarkers (OCULAB) program to build a medical device that could transform testing and treatment for a range of health conditions. The project, Personalized Automated Continuous Treatment for Eye Plus Systemic Disease (PACE+), aims to develop an implantable system, placed near the eye, that can measure biomarkers in tears to monitor dry eye disease (DED) and automatically deliver medication to treat the condition. The technology uses remote sensing capabilities and could be expanded for use in a range of other diseases, such as cancer, diabetes and neurological conditions. The OCULAB approach centers on tears as a diagnostic fluid. Tears contain many of the same biomarkers as blood but are easier to collect. Compared to intermittent blood draws, continuous monitoring of tears can track disease states more chronically with less burden to patients. The researchers intend to build a tiny implant, the size of a grain of rice, that can be placed through a small existing opening in the eyelid (corner of the eye) during a quick, painless procedure. A chip inside the implant measures tear biomarkers linked to DED symptoms and sends the data to the patient’s smartphone. The phone then automatically dispatches medication as needed through a second small device, tucked between the eye and lower lid. This helps manage symptoms as they fluctuate without requiring any action from the patient. Over the next 18 months, the researchers will focus on engineering and validating the system. This includes demonstrating in the lab that the sensor can accurately measure DED biomarkers, confirming that the system can be safely positioned around the eye and conducting early tests in preclinical models. If the team meets these milestones, the project is eligible for up to $9.3 million in additional funding.

A new generation of artificial intelligence (AI) tools could help save more patients who need heart transplants by making better use of donor hearts that are currently discarded, according to research presented today by Brian Wayda, MD, at International Society for Heart and Lung Transplantation (ISHLT) 46th Annual Meeting and Scientific Sessions.

Industrial electrification is becoming a matter of economic security as well as decarbonisation, according to new Oxford analysis. Continued reliance on fossil fuels leaves 75% of global industry exposed to recurring price shocks, while electrification offers a pathway to stable and resilient energy costs.