Regulating Revolutions

The use of machine learning and AI to complement areas of life science such as biotechnology, engineering biology and synthetic biology has become commonplace in just a few years. As shown in our latest special issue, AI-powered biological design tools now provide a range of capabilities to biologists, including viral vector design, deductions of genome-phenome associations, predictions of protein structure and binding, and even the generation of entirely new proteins and genomes. In short, AI is addressing some of the biggest questions in biology, and powering innovative applications across life sciences R&D, agriculture, sustainability, pollution control, energy security, human health and defence. Despite this rapid progress, the convergence of AI with bioscience is still in its infancy and proactive policy is needed to manage these technologies as they mature. The technology is advancing far faster than associated policy frameworks, and there is little governance specifically focused on the intersection of AI and life science.