# A Pragmatic View of AI Personhood arXiv: https://arxiv.org/abs/2510.26396 ยท HTML: https://mlsanity.com/paper/2510.26396/ ## Key facts - Cited by 12 papers in the map (data through 14 Oct 2026). - Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. - Builds on 33 of its 167 references that are in the map. - First posted on arXiv 30 Oct 2025. ## Placed in - LLM agents and tool use / [General LLM agent frameworks and benchmarks](https://mlsanity.com/agents/general-llm-agent-frameworks-and-benchmarks/) ## Builds on (most cited first, 30 of 33) - [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022) - [Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback](https://mlsanity.com/paper/2204.05862/) (2022) - [Out of One, Many: Using Language Models to Simulate Human Samples](https://mlsanity.com/paper/2209.06899/) (2022) - [Counterfactual Multi-Agent Policy Gradients](https://mlsanity.com/paper/1705.08926/) (2017) - [Improving alignment of dialogue agents via targeted human judgements](https://mlsanity.com/paper/2209.14375/) (2022) - [Role-Play with Large Language Models](https://mlsanity.com/paper/2305.16367/) (2023) - [LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals](https://mlsanity.com/paper/2411.10109/) (2024) - [OR-Bench: An Over-Refusal Benchmark for Large Language Models](https://mlsanity.com/paper/2405.20947/) (2024) - [Multi-Agent Risks from Advanced AI](https://mlsanity.com/paper/2502.14143/) (2025) - [Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia](https://mlsanity.com/paper/2312.03664/) (2023) - [On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial](https://mlsanity.com/paper/2403.14380/) (2024) - [Gradual Disempowerment: Systemic Existential Risks from Incremental AI Development](https://mlsanity.com/paper/2501.16946/) (2025) - [Welfare Diplomacy: Benchmarking Language Model Cooperation](https://mlsanity.com/paper/2310.08901/) (2023) - [Society-in-the-Loop: Programming the Algorithmic Social Contract](https://mlsanity.com/paper/1707.07232/) (2017) - [AI Companions Reduce Loneliness](https://mlsanity.com/paper/2407.19096/) (2024) - [A theory of appropriateness with applications to generative artificial intelligence](https://mlsanity.com/paper/2412.19010/) (2024) - [A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings](https://mlsanity.com/paper/2106.09012/) (2021) - [Law Informs Code: A Legal Informatics Approach to Aligning Artificial Intelligence with Humans](https://mlsanity.com/paper/2209.13020/) (2022) - [Virtual Agent Economies](https://mlsanity.com/paper/2509.10147/) (2025) - [Computers as Bad Social Actors: Dark Patterns and Anti-Patterns in Interfaces that Act Socially](https://mlsanity.com/paper/2302.04720/) (2023) - [An Economy of AI Agents](https://mlsanity.com/paper/2509.01063/) (2025) - [Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online](https://mlsanity.com/paper/2408.07892/) (2024) - [Generative Ghosts: Anticipating Benefits and Risks of AI Afterlives](https://mlsanity.com/paper/2402.01662/) (2024) - [Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences](https://mlsanity.com/paper/2010.09054/) (2020) - [Characterizing and modeling harms from interactions with design patterns in AI interfaces](https://mlsanity.com/paper/2404.11370/) (2024) - [The Dynamics of Norm Change in the Cultural Evolution of Language](https://mlsanity.com/paper/1809.04328/) (2018) - [Should agentic conversational AI change how we think about ethics? Characterising an interactional ethics centred on respect](https://mlsanity.com/paper/2401.09082/) (2024) - [Multi-Actor Generative Artificial Intelligence as a Game Engine](https://mlsanity.com/paper/2507.08892/) (2025) - [Normative Disagreement as a Challenge for Cooperative AI](https://mlsanity.com/paper/2111.13872/) (2021) - [Can We Govern the Agent-to-Agent Economy?](https://mlsanity.com/paper/2501.16606/) (2025) ## Built on by (most cited first, 12 of 12) - [AI Identity: Standards, Gaps, and Research Directions for AI Agents](https://mlsanity.com/paper/2604.23280/) (2026) - [A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms](https://mlsanity.com/paper/2609.04170/) (2026) - [Post-AGI Economies: Autonomy and the First Fundamental Theorem of Welfare Economics](https://mlsanity.com/paper/2604.21216/) (2026) - [Memory as Ontology: A Constitutional Memory Architecture for Persistent Digital Citizens](https://mlsanity.com/paper/2603.04740/) (2026) - [Solipsistic Superintelligence is Unlikely to be Cooperative](https://mlsanity.com/paper/2606.03237/) (2026) - [Rethinking Psychometric Evaluation of LLMs: When and Why Self-Reports Predict Behavior](https://mlsanity.com/paper/2606.12730/) (2026) - [The Sentience Readiness Index: A Preliminary Framework for Measuring National Preparedness for the Possibility of Artificial Sentience](https://mlsanity.com/paper/2603.01508/) (2026) - [Distributed Legal Infrastructure for a Trustworthy Agentic Web](https://mlsanity.com/paper/2603.06884/) (2026) - [The Possibility of Artificial Intelligence Becoming a Subject and the Alignment Problem](https://mlsanity.com/paper/2604.14990/) (2026) - [Precautionary Governance of Autonomous AI: Legal Personhood as Functional Instrument](https://mlsanity.com/paper/2605.12505/) (2026) - [Appearing Legitimate is Not Enough: Interrogating Synthetic Agents in Representational Processes through a Participatory Design Lens](https://mlsanity.com/paper/2608.17099/) (2026) - [Tapes Together Strong: The Co-evolution of Computation and Cooperation](https://mlsanity.com/paper/2609.10817/) (2026) ## Abstract (arXiv) The emergence of agentic Artificial Intelligence (AI) is set to trigger a "Cambrian explosion" of new kinds of personhood. This paper proposes a pragmatic framework for navigating this diversification by treating personhood not as a metaphysical property to be discovered, but as a flexible bundle of obligations (rights and responsibilities) that societies confer upon entities for a variety of reasons, especially to solve concrete governance problems. We argue that this traditional bundle can be unbundled, creating bespoke solutions for different contexts. This will allow for the creation of practical tools -- such as facilitating AI contracting by creating a target "individual" that can be sanctioned -- without needing to resolve intractable debates about an AI's consciousness or rationality. We explore how individuals fit in to social roles and discuss the use of decentralized digital identity technology, examining both "personhood as a problem", where design choices can create "dark patterns" that exploit human social heuristics, and "personhood as a solution", where conferring a bundle of obligations is necessary to ensure accountability or prevent conflict. By rejecting foundationalist quests for a single, essential definition of personhood, this paper offers a more pragmatic and flexible way to think about integrating AI agents into our society.