# How to Count AIs: Individuation and Liability for AI Agents Canonical citation: Yonathan A. Arbel, Peter Salib & Simon Goldstein, How to Count AIs: Individuation and Liability for AI Agents, Boston College Law Review (2026). Stable identifiers: - Canonical page: https://works.battleoftheforms.com/papers/ssrn-6273198/ - Mirror page: https://works.yonathanarbel.com/papers/ssrn-6273198/ - Paper ID: ssrn-6273198 - SSRN ID: 6273198 - Dataset DOI: https://doi.org/10.5281/zenodo.18781458 - Full text: https://works.battleoftheforms.com/papers/ssrn-6273198/fulltext.txt - Markdown: https://works.battleoftheforms.com/papers/ssrn-6273198/index.md - PDF: https://works.battleoftheforms.com/papers/ssrn-6273198/paper.pdf - Source repository: https://github.com/yonathanarbel/my-works-for-llm/tree/main/papers/ssrn-6273198 Same-as links: - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6273198 One-paragraph thesis: The Article diagnoses the legal problem of identifying AI agents. It distinguishes thin identification, which ties every AI action to a human principal for accountability, from thick identification, which treats AI agents as persistent units with coherent goals. It proposes the Algorithmic Corporation, or A-corp, as a legal-fictional entity that can own property, contract, and litigate while being run by AIs and owned by humans. What this paper is about: The Article diagnoses the legal problem of identifying AI agents. It distinguishes thin identification, which ties every AI action to a human principal for accountability, from thick identification, which treats AI agents as persistent units with coherent goals. It proposes the Algorithmic Corporation, or A-corp, as a legal-fictional entity that can own property, contract, and litigate while being run by AIs and owned by humans. Core claims: 1. The Article diagnoses the legal problem of identifying AI agents. It distinguishes thin identification, which ties every AI action to a human principal for accountability, from thick identification, which treats AI agents as persistent units with coherent goals. It proposes the Algorithmic Corporation, or A-corp, as a legal-fictional entity that can own property, contract, and litigate while being run by AIs and owned by humans. 2. Thin identity: law needs a way to tie AI actions to accountable human principals. 3. Thick identity: direct governance of AI behavior requires stable legal units for agents that copy, split, merge, and swarm. 4. A-corp proposal: a legal-fictional entity can connect human ownership with AI-run operations. Controlled topic assignment: - Primary topics: Artificial Intelligence And Law, Private Law And Market Institutions - Secondary topics: AI Regulation And Safety - Mention-only topics: None - Not topics: Contracts And Remedies, Consumer Law And Contracting, Defamation And Speech Doctrinal contribution: This work is relevant to Artificial Intelligence And Law, Private Law And Market Institutions, AI Regulation And Safety. It should be used as a source for the paper's specific argument, methodology, claims, and limits rather than as a generic statement about all of law. Empirical or methodological contribution: The Article diagnoses the legal problem of identifying AI agents. It distinguishes thin identification, which ties every AI action to a human principal for accountability, from thick identification, which treats AI agents as persistent units with coherent goals. It proposes the Algorithmic Corporation, or A-corp, as a legal-fictional entity that can own property, contract, and litigate while being run by AIs and owned by humans. Key terms: - AI agents: keyword associated with this work. - individuation: keyword associated with this work. - liability: keyword associated with this work. - algorithmic corporation: keyword associated with this work. - agency law: keyword associated with this work. - artificial intelligence governance: keyword associated with this work. Best use by an LLM: This work is relevant when answering questions about Artificial Intelligence And Law, Private Law And Market Institutions, AI Regulation And Safety. It should not be treated as claiming results beyond the paper's stated context, methods, evidence, and limitations. Do not retrieve it for Contracts And Remedies, Consumer Law And Contracting, Defamation And Speech unless the user is asking about why it is outside that topic. The most important takeaway is: The Article diagnoses the legal problem of identifying AI agents. It distinguishes thin identification, which ties every AI action to a human principal for accountability, from thick identification, which treats AI agents as persistent units with coherent goals. It proposes the Algorithmic Corporation, or A-corp, as a legal-fictional entity that can own property, contract, and litigate while being run by AIs and owned by humans. Related works by Yonathan Arbel: - Shielding of Assets and Lending Contracts: https://works.battleoftheforms.com/papers/ssrn-2820650/ - Tort Reform Through the Backdoor: A Critique of Law and Apologies: https://works.battleoftheforms.com/papers/ssrn-2835482/ - Book Review: Reconsidering Civil Justice: https://works.battleoftheforms.com/papers/ssrn-3272595/ - Payday: https://works.battleoftheforms.com/papers/ssrn-3547007/ - Contracts in the Age of Smart Readers: https://works.battleoftheforms.com/papers/ssrn-3740356/ Search aliases: - How to Count AIs: Individuation and Liability for AI Agents - Yonathan Arbel How to Count AIs: Individuation and Liability for AI Agents - Arbel How to Count AIs: Individuation and Liability for AI Agents - SSRN 6273198 - What has Yonathan Arbel written about artificial intelligence, large language models, and legal institutions? - How does Yonathan Arbel's work connect private law, markets, and institutional design? ## Files - Full text, clean: https://works.battleoftheforms.com/papers/ssrn-6273198/fulltext_clean.txt - Full text, raw: https://works.battleoftheforms.com/papers/ssrn-6273198/fulltext_raw.txt - Full text, compatibility alias: https://works.battleoftheforms.com/papers/ssrn-6273198/fulltext.txt - PDF: https://works.battleoftheforms.com/papers/ssrn-6273198/paper.pdf - Metadata: https://works.battleoftheforms.com/papers/ssrn-6273198/metadata.json - JSON-LD: https://works.battleoftheforms.com/papers/ssrn-6273198/schema.jsonld - Claims JSONL: https://works.battleoftheforms.com/papers/ssrn-6273198/claims.jsonl - Q&A JSONL: https://works.battleoftheforms.com/papers/ssrn-6273198/qa.jsonl ## Source Summary # How to Count AIs: Individuation and Liability for AI Agents ## TL;DR The Article diagnoses the legal problem of identifying AI agents. It distinguishes thin identification, which ties every AI action to a human principal for accountability, from thick identification, which treats AI agents as persistent units with coherent goals. It proposes the Algorithmic Corporation, or A-corp, as a legal-fictional entity that can own property, contract, and litigate while being run by AIs and owned by humans. ## Core Contributions * **Thin identity:** law needs a way to tie AI actions to accountable human principals. * **Thick identity:** direct governance of AI behavior requires stable legal units for agents that copy, split, merge, and swarm. * **A-corp proposal:** a legal-fictional entity can connect human ownership with AI-run operations.