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Donate > cs > arXiv:2311.02462 Help | Advanced Search All fields Title Author Abstract Comments Journal reference ACM classification MSC classification Report number arXiv identifier DOI ORCID arXiv author ID Help pages Full text Search open search GO open navigation menu quick links Login Help Pages About --> Computer Science > Artificial Intelligence arXiv:2311.02462 (cs) [Submitted on 4 Nov 2023 ( v1 ), last revised 24 Sep 2025 (this version, v5)] Title: Levels of AGI for Operationalizing Progress on the Path to AGI Authors: Meredith Ringel Morris , Jascha Sohl-Dickstein , Noah Fiedel , Tris Warkentin , Allan Dafoe , Aleksandra Faust , Clement Farabet , Shane Legg View a PDF of the paper titled Levels of AGI for Operationalizing Progress on the Path to AGI, by Meredith Ringel Morris and 7 other authors View PDF HTML (experimental) Abstract: We propose a framework for classifying the capabilities and behavior of Artificial General Intelligence (AGI) models and their precursors. This framework introduces levels of AGI performance, generality, and autonomy, providing a common language to compare models, assess risks, and measure progress along the path to AGI. To develop our framework, we analyze existing definitions of AGI, and distill six principles that a useful ontology for AGI should satisfy. With these principles in mind, we propose "Levels of AGI" based on depth (performance) and breadth (generality) of capabilities, and reflect on how current systems fit into this ontology. We discuss the challenging requirements for future benchmarks that quantify the behavior and capabilities of AGI models against these levels. Finally, we discuss how these levels of AGI interact with deployment considerations such as autonomy and risk, and emphasize the importance of carefully selecting Human-AI Interaction paradigms for responsible and safe deployment of highly capable AI systems. Comments: version 5 - We updated the nomenclature of Level 4 to be "Exceptional" instead of "Virtuoso"; due to ICML 2024 position paper titling requirements, the title is now "Levels of AGI for Operationalizing Progress on the Path to AGI" rather than "Levels of AGI: Operationalizing Progress on the Path to AGI" Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2311.02462 [cs.AI] (or arXiv:2311.02462v5 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2311.02462 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Proceedings of ICML 2024 Submission history From: Meredith Morris [ view email ] [v1] Sat, 4 Nov 2023 17:44:58 UTC (423 KB) [v2] Fri, 5 Jan 2024 21:15:45 UTC (434 KB) [v3] Wed, 22 May 2024 02:14:49 UTC (85 KB) [v4] Wed, 5 Jun 2024 22:08:35 UTC (82 KB) [v5] Wed, 24 Sep 2025 18:37:50 UTC (70 KB) Full-text links: Access Paper: View a PDF of the paper titled Levels of AGI for Operationalizing Progress on the Path to AGI, by Meredith Ringel Morris and 7 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.AI < prev | next > new | recent | 2023-11 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar 1 blog link ( what is this? ) export BibTeX citation Loading... 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