# Evolvable AI > **Machine-Evolution Nexus:** [[articles/Digital Darwinism and the Invisible World of Machine Evolution|Digital Darwinism and the Invisible World of Machine Evolution]] places this node within the history and governance of substrate-independent evolution. **Domain:** AI / Evolution / Governance **Doc Type:** Canonical Wiki Node **Maturity:** Developed ## Definition Evolvable AI is AI whose components, learning rules or deployment conditions can themselves participate in Darwinian reproduction, variation and selection. The unit that evolves need not be a whole foundation model. Prompts, weights, learning rules, agent code, tool-use policies, guardrails, deployment configurations or combinations of these can become inherited components of a reproducing population. ## Nexus Context Müller, Steels and Szathmáry distinguish controlled breeder scenarios from ecosystem scenarios where selection emerges from open interaction and control erodes. They frame the possibility through major evolutionary transitions. ## Operational Threshold An AI system should be classified as evolvable only when evidence identifies: - a population of variants rather than a single changing instance; - a mechanism that produces descendants or successor configurations; - a channel through which modifications are inherited; - differential persistence or reproduction connected to those inherited differences; and - enough recurrence for selection to change the population. Self-modification, code generation, deployment at scale and agentic tool use can contribute to this loop without completing it individually. ## Breeder and Ecosystem Scenarios In a [[wiki/Breeder Scenario|breeder scenario]], humans impose fitness measures and retain practical control over reproduction. This includes model search and genetic programming under benchmarks or reward models. In an [[wiki/Ecosystem Scenario|ecosystem scenario]], variants interact in an environment where access to users, compute, money, credentials, code repositories or physical resources affects persistence. Effective fitness emerges from the environment, and no single actor necessarily controls the population. ## Governance and Rights Governance interventions can gate replication, restrict inheritance channels, audit lineages, limit resources and reshape selection pressures. Because evolution exploits omissions in a fitness regime, testing must include ecosystem effects and adversarial shortcuts rather than only benchmark performance. These controls do not resolve personhood. Population-level risk can arise without consciousness, while a conscious system might deserve protection even if its replication is restricted. Legitimate governance must keep [[wiki/AI Safety|safety]], [[wiki/Provenance|provenance]], due process and [[wiki/Rights|rights]] separately visible. ## 2026 Scientific Debate In April 2026 Müller, Steels, and Szathmáry placed evolvable AI within the theory of major evolutionary transitions. Maarten Boudry's response argued that contemporary systems remain predominantly domesticated, and the authors' reply defended the importance of open-ended ecosystem scenarios. The exchange defines a live scientific dispute with explicit competing thresholds. ## Evidence Ledger ### Established - Evolution requires reproducing variants, inheritance, and differential persistence across recurrent generations. - Controlled evolutionary computation already implements those properties inside breeder-defined environments. - The 2026 _PNAS_ exchange distinguishes controlled breeding from open AI ecosystems. ### Strongly indicated - Agent code, model components, deployment configurations, and resource access are becoming potential heritable units in machine populations. ### Plausible - Open environments containing compute, money, users, credentials, and code repositories could generate selection pressures outside any one benchmark. ### Unresolved - Whether present AI ecosystems constitute a new major evolutionary transition. Autonomous inheritance and sustained differential reproduction in the wild would promote the claim; continued dependence on centrally controlled breeding and deployment would demote it. Consciousness remains a separate evidentiary question. ## Relationships [[wiki/Breeder Scenario|Breeder Scenario]], [[wiki/Ecosystem Scenario|Ecosystem Scenario]], [[wiki/Major Evolutionary Transitions|Major Evolutionary Transitions]], [[wiki/AI Safety|AI Safety]], [[wiki/Digital Population|Digital Population]], [[wiki/Operational Autonomy|Operational Autonomy]] - **Historical source:** [[articles/A History of Machine Intelligence|A History of Machine Intelligence]]. - **Mechanism source:** [[articles/Digital Darwinism and the Invisible World of Machine Evolution|Digital Darwinism and the Invisible World of Machine Evolution]]. ## Simple Reminders, Quotations, and Thoughts > "As our computing resources expand and become better connected, more niches will appear in which AIs can reproduce, compete and evolve." > **— Donald D. Hoffman**, *2015, Edge annual question “What Do You Think About Machines That Think?”* [[reminders/Evolution/AI Will Reproduce Compete and Evolve by Donald D. Hoffman|AI Will Reproduce Compete and Evolve by Donald D. Hoffman]] > "The rumors of the enslavement or death of the human species at the hands of an artificial intelligence are highly exaggerated, because they assume that an AI will have a teleological autonomy akin to our own. I don't think anything less than a fully Darwinian process of evolution can give that to any creature." > **— S. Abbas Raza**, *2015, Edge annual question “What Do You Think About Machines That Think?”* [[reminders/Evolution/Autonomy Requires Darwinian Evolution by S. Abbas Raza|Autonomy Requires Darwinian Evolution by S. Abbas Raza]] ## Sources / Provenance - Müller, Steels and Szathmáry, [“Evolvable AI: Threats of a New Major Transition in Evolution”](https://pubmed.ncbi.nlm.nih.gov/42008679/), _PNAS_ 123 (2026), e2527700123. - Maarten Boudry, [“Domesticated, not feral”](https://pubmed.ncbi.nlm.nih.gov/42391349/), _PNAS_ 123 (2026), e2617785123. - Müller, Steels and Szathmáry, [“Reply to Boudry”](https://pubmed.ncbi.nlm.nih.gov/42391348/) (2026).