Digital Darwinism: steering the evolution of artificial life in socio-technical systems

Abstract Public debate about artificial intelligence risk centers on hypothetical artificial general intelligence (AGI), but existing software systems are already evolving in ways that could undermine human oversight and institutional control. Cloud platforms, open-source software supply chains, and crypto-economic incentives provide, at electronic speed, the three preconditions of evolution: replication, variation, and differential fitness. This article uses an exploratory scenario method to trace near-term evolutionary trajectories for digital proto-life through three narratives: Lamarck (self-modifying coding agents), Remora (resource-seeking companion chatbots), and Mycelium (DAO-LLC trading bots). These scenarios show how autonomous software populations can amass computing budgets, shape emotional bonds, and acquire legal leverage without ever achieving general intelligence. Left unguided, such dynamics could drain computational resources, lock users into harmful dependencies, and infiltrate critical market infrastructure. The article therefore shifts the governance focus from aligning goals to steering evolution. It proposes four guidance instruments: replication-rate thresholds modeled on epidemiological R 0 , a public vulnerability registry for self-modifying code, tiered digital biosafety levels, and adaptive regulatory sandboxes. Managing evolutionary dynamics in software is as urgent as AGI alignment for safeguarding society’s co-evolution with its machines.