{"ID":2873494,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.06786","arxiv_id":"2509.06786","title":"\\texttt{R$^\\textbf{2}$AI}: Towards Resistant and Resilient AI in an Evolving World","abstract":"In this position paper, we address the persistent gap between rapidly growing AI capabilities and lagging safety progress. Existing paradigms divide into ``Make AI Safe'', which applies post-hoc alignment and guardrails but remains brittle and reactive, and ``Make Safe AI'', which emphasizes intrinsic safety but struggles to address unforeseen risks in open-ended environments. We therefore propose \\textit{safe-by-coevolution} as a new formulation of the ``Make Safe AI'' paradigm, inspired by biological immunity, in which safety becomes a dynamic, adversarial, and ongoing learning process. To operationalize this vision, we introduce \\texttt{R$^2$AI} -- \\textit{Resistant and Resilient AI} -- as a practical framework that unites resistance against known threats with resilience to unforeseen risks. \\texttt{R$^2$AI} integrates \\textit{fast and slow safe models}, adversarial simulation and verification through a \\textit{safety wind tunnel}, and continual feedback loops that guide safety and capability to coevolve. We argue that this framework offers a scalable and proactive path to maintain continual safety in dynamic environments, addressing both near-term vulnerabilities and long-term existential risks as AI advances toward AGI and ASI.","short_abstract":"In this position paper, we address the persistent gap between rapidly growing AI capabilities and lagging safety progress. Existing paradigms divide into ``Make AI Safe'', which applies post-hoc alignment and guardrails but remains brittle and reactive, and ``Make Safe AI'', which emphasizes intrinsic safety but strugg...","url_abs":"https://arxiv.org/abs/2509.06786","url_pdf":"https://arxiv.org/pdf/2509.06786v1","authors":"[\"Youbang Sun\",\"Xiang Wang\",\"Jie Fu\",\"Chaochao Lu\",\"Bowen Zhou\"]","published":"2025-09-08T15:13:23Z","proceeding":"cs.LG","tasks":"[\"cs.LG\"]","methods":"[]","has_code":false}