Science Daily April 14, 2022
A team of researchers in the UK examines how open science practices and the risks of misuse interface and proposes solutions to the problems identified. They argue that in the context of viral engineering, open code, data, and materials may increase the risk of the release of enhanced pathogens. Openly available machine learning models could reduce the amount of time needed in the laboratory and make pathogen engineering easier. To prevent the misuse of computational tools, controlling access to software and data may be necessary. They highlight that research preregistration, a practice promoted by the open science community to increase research quality, may harbor an opportunity to review and mitigate research risks. Risk mitigation measures need to be fused into practices developed to ensure open, high-quality, and reproducible scientific research. Open science and biosecurity experts need to work together to develop mechanisms to ensure responsible research with maximal societal benefit. They showed that science cannot be just open or closed: there are intermediate states that need to be explored, and difficult trade-offs touching on core scientific values may be needed…read more. Open Access TECHNICAL ARTICLEÂ