Can AI design new life? A conversation with creator

MIT Technology Review spoke with Samuel King, the Stanford PhD student whose 2025 work used a generative AI model to propose genetic blueprints for microscopic viruses. The project is not AI-generated life. It is a computational design exercise that sits at the boundary between digital modeling and biological synthesis, and that boundary is exactly what makes the conversation important. The discussion explores how AI could speed up virology research by helping scientists generate and evaluate genetic designs more quickly. That might lead to better vaccines, diagnostics, or tools for studying pathogens. But the same capabilities could also lower barriers for misuse, raising difficult questions about screening, oversight, and who should have access to models that can propose biological sequences. King's work does not answer those questions, but it makes them concrete. The conversation also probes what it would mean to move from designing genetic instructions to actually creating new life in a laboratory. That step would involve scientific, ethical, and regulatory challenges far beyond a model's output. For now, the responsible approach is to treat AI as a powerful design aid that must be paired with strong biosecurity practices, expert review, and clear limits. The story is a reminder that AI's most consequential advances may come not from chatbots but from tools that reshape how researchers work with biology itself.