The AGI Containment Problem
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Abstract (arXiv)
There is considerable uncertainty about what properties, capabilities and motivations future AGIs will have. In some plausible scenarios, AGIs may pose security risks arising from accidents and defects. In order to mitigate these risks, prudent early AGI research teams will perform significant testing on their creations before use. Unfortunately, if an AGI has human-level or greater intelligence, testing itself may not be safe; some natural AGI goal systems create emergent incentives for AGIs to tamper with their test environments, make copies of themselves on the internet, or convince developers and operators to do dangerous things. In this paper, we survey the AGI containment problem - the question of how to build a container in which tests can be conducted safely and reliably, even on AGIs with unknown motivations and capabilities that could be dangerous. We identify requirements for AGI containers, available mechanisms, and weaknesses that need to be addressed.
Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Apr 2016.
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Citing papers per year: 2021: 8; 2022: 7; 2023: 9; 2024: 5; 2025: 3; 2026: 4.
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- 2021Agent Incentives: A Causal Perspectivecited by 51
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- 2021A Word on Machine Ethics: A Response to Jiang et al. (2021)cited by 23
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- 2021Explaining Bayesian Neural Networkscited by 18
- 2026How Vulnerable Are AI Agents to Indirect Prompt Injections? Insights from a Large-Scale Public Competitioncited by 16
- 2024CLEAR: Can Language Models Really Understand Causal Graphs?cited by 14
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- 2024Computational Experiments Meet Large Language Model Based Agents: A Survey and Perspectivecited by 11
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- 2021The General Theory of General Intelligence: A Pragmatic Patternist Perspectivecited by 8
- 2026Measuring Progress Toward AGI: A Cognitive Frameworkcited by 6
- 2022Towards Inadequately Pre-trained Models in Transfer Learningcited by 5
- 2023Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Modelscited by 5
- 2024Integration of cognitive tasks into artificial general intelligence test for large modelscited by 5
- 2024Realizing Visual Question Answering for Education: GPT-4V as a Multimodal AIcited by 5
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- 2021Maximum and Leaky Maximum Propagationcited by 4
- 2022Exploring the Intersection between Neural Architecture Search and Continual Learningcited by 4
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- 2021Hard Choices and Hard Limits for Artificial Intelligencecited by 2
- 2023NovPhy: A Testbed for Physical Reasoning in Open-world Environmentscited by 2
- 2022Artificial Open World for Evaluating AGI: a Conceptual Designcited by 1
- 2024Why Is Anything Conscious?cited by 1
- 2021Modern Machine and Deep Learning Systems as a way to achieve Man-Computer Symbiosiscited by 0
- 2022Deep Learning and Artificial General Intelligence: Still a Long Way to Gocited by 0
- 2022The problem with AI consciousness: A neurogenetic case against synthetic sentiencecited by 0
- 2025Limitations on Accurate, Trusted, Human-level Reasoningcited by 0
- 2025Foundations of Artificial Intelligence Frameworks: Notion and Limits of AGIcited by 0
- 2026Federated Graph AGI for Cross-Border Insider Threat Intelligence in Government Financial Schemescited by 0
- 2026Measuring Progress Toward AGI: A Cognitive Framework27 May 2026
- 2026How Vulnerable Are AI Agents to Indirect Prompt Injections? Insights from a Large-Scale Public Competition16 Mar 2026
- 2026Federated Graph AGI for Cross-Border Insider Threat Intelligence in Government Financial Schemes18 Feb 2026
- 2026SE-Bench: Benchmarking Self-Evolution with Knowledge Internalization4 Feb 2026
- 2025Foundations of Artificial Intelligence Frameworks: Notion and Limits of AGI23 Nov 2025
- 2025Limitations on Accurate, Trusted, Human-level Reasoning25 Sep 2025
- 2025Position: AI Scaling: From Up to Down and Out2 Feb 2025
- 2024Why Is Anything Conscious?22 Sep 2024
- 2024CLEAR: Can Language Models Really Understand Causal Graphs?24 Jun 2024
- 2024Realizing Visual Question Answering for Education: GPT-4V as a Multimodal AI12 May 2024
- 2024Integration of cognitive tasks into artificial general intelligence test for large models4 Feb 2024
- 2024Computational Experiments Meet Large Language Model Based Agents: A Survey and Perspective1 Feb 2024
24 more
- 2023Honesty Is the Best Policy: Defining and Mitigating AI Deception3 Dec 2023
- 2023Generative AI vs. AGI: The Cognitive Strengths and Weaknesses of Modern LLMs19 Sep 2023
- 2023Reuse and Diffuse: Iterative Denoising for Text-to-Video Generation7 Sep 2023
- 2023Provably safe systems: the only path to controllable AGI5 Sep 2023
- 2023AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors21 Aug 2023
- 2023Why We Don't Have AGI Yet7 Aug 2023
- 2023Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Models14 Jun 2023
- 2023Text-to-image Diffusion Models in Generative AI: A Survey14 Mar 2023
- 2023NovPhy: A Testbed for Physical Reasoning in Open-world Environments3 Mar 2023
- 2022The problem with AI consciousness: A neurogenetic case against synthetic sentience7 Dec 2022
- 2022Exploring the Intersection between Neural Architecture Search and Continual Learning11 Jun 2022
- 2022A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs7 Jun 2022
- 2022Artificial Open World for Evaluating AGI: a Conceptual Design2 Jun 2022
- 2022Deep Learning and Artificial General Intelligence: Still a Long Way to Go25 Mar 2022
- 2022A Thermodynamics-informed Active Learning Approach to Perception and Reasoning about Fluids11 Mar 2022
- 2022Towards Inadequately Pre-trained Models in Transfer Learning9 Mar 2022
- 2021A Word on Machine Ethics: A Response to Jiang et al. (2021)7 Nov 2021
- 2021Explaining Bayesian Neural Networks23 Aug 2021
- 2021Collaborative Visual Navigation2 Jul 2021
- 2021Maximum and Leaky Maximum Propagation21 May 2021
- 2021Hard Choices and Hard Limits for Artificial Intelligence4 May 2021
- 2021The General Theory of General Intelligence: A Pragmatic Patternist Perspective28 Mar 2021
- 2021Agent Incentives: A Causal Perspective2 Feb 2021
- 2021Modern Machine and Deep Learning Systems as a way to achieve Man-Computer Symbiosis24 Jan 2021
- 2023AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviorscited by 580
- 2026How Vulnerable Are AI Agents to Indirect Prompt Injections? Insights from a Large-Scale Public Competitioncited by 16
- 2024Computational Experiments Meet Large Language Model Based Agents: A Survey and Perspectivecited by 11
- 2026How Vulnerable Are AI Agents to Indirect Prompt Injections? Insights from a Large-Scale Public Competition16 Mar 2026
- 2024Computational Experiments Meet Large Language Model Based Agents: A Survey and Perspective1 Feb 2024
- 2023AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors21 Aug 2023
- 2023Text-to-image Diffusion Models in Generative AI: A Surveycited by 264
- 2023Reuse and Diffuse: Iterative Denoising for Text-to-Video Generationcited by 49
- 2021Agent Incentives: A Causal Perspectivecited by 51
- 2022A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphscited by 49
- 2023Honesty Is the Best Policy: Defining and Mitigating AI Deceptioncited by 40
- 2023Provably safe systems: the only path to controllable AGIcited by 29
- 2021A Word on Machine Ethics: A Response to Jiang et al. (2021)cited by 23
- 2021Collaborative Visual Navigationcited by 18
- 2021Explaining Bayesian Neural Networkscited by 18
- 2023Generative AI vs. AGI: The Cognitive Strengths and Weaknesses of Modern LLMscited by 11
- 2022A Thermodynamics-informed Active Learning Approach to Perception and Reasoning about Fluidscited by 9
- 2021The General Theory of General Intelligence: A Pragmatic Patternist Perspectivecited by 8
- 2026Measuring Progress Toward AGI: A Cognitive Frameworkcited by 6
- 2022Towards Inadequately Pre-trained Models in Transfer Learningcited by 5
12 most cited of 29 All 29 (JSON)
- 2026Measuring Progress Toward AGI: A Cognitive Framework27 May 2026
- 2026Federated Graph AGI for Cross-Border Insider Threat Intelligence in Government Financial Schemes18 Feb 2026
- 2026SE-Bench: Benchmarking Self-Evolution with Knowledge Internalization4 Feb 2026
- 2025Foundations of Artificial Intelligence Frameworks: Notion and Limits of AGI23 Nov 2025
- 2025Limitations on Accurate, Trusted, Human-level Reasoning25 Sep 2025
- 2025Position: AI Scaling: From Up to Down and Out2 Feb 2025
- 2024Why Is Anything Conscious?22 Sep 2024
- 2024Realizing Visual Question Answering for Education: GPT-4V as a Multimodal AI12 May 2024
- 2024Integration of cognitive tasks into artificial general intelligence test for large models4 Feb 2024
- 2023Honesty Is the Best Policy: Defining and Mitigating AI Deception3 Dec 2023
- 2023Generative AI vs. AGI: The Cognitive Strengths and Weaknesses of Modern LLMs19 Sep 2023
- 2023Provably safe systems: the only path to controllable AGI5 Sep 2023
12 newest of 29 All 29 (JSON)