Why Law Needs a New Entity to Govern AI Agents
Canonical citation:
Yonathan A. Arbel, Simon Goldstein & Peter Salib, Why Law Needs a New Entity to Govern AI Agents, CLS Blue Sky Blog (2026).
Stable identifiers:
- Canonical page: https://works.battleoftheforms.com/papers/new-entity-ai-agents/
- Mirror page: https://works.yonathanarbel.com/papers/new-entity-ai-agents/
- Paper ID: new-entity-ai-agents
- SSRN ID: not recorded
- Dataset DOI: https://doi.org/10.5281/zenodo.18781458
- Full text: https://works.battleoftheforms.com/papers/new-entity-ai-agents/fulltext.txt
- Markdown: https://works.battleoftheforms.com/papers/new-entity-ai-agents/index.md
- PDF: https://works.battleoftheforms.com/papers/new-entity-ai-agents/paper.pdf
- Source repository: https://github.com/yonathanarbel/my-works-for-llm
Same-as links:
One-paragraph thesis:
Proposes a new corporate form, the A-corp (algorithmic corporation), to solve the identification bottleneck for AI agents: humans own, AIs run; builds on the resource constraint thesis and emergent corporate governance to give law leverage over autonomous AI swarms.
What this paper is about:
Proposes a new corporate form, the A-corp (algorithmic corporation), to solve the identification bottleneck for AI agents: humans own, AIs run; builds on the resource constraint thesis and emergent corporate governance to give law leverage over autonomous AI swarms.
Core claims:
1. Proposes a new corporate form, the A-corp (algorithmic corporation), to solve the identification bottleneck for AI agents: humans own, AIs run; builds on the resource constraint thesis and emergent corporate governance to give law leverage over autonomous AI swarms.
Controlled topic assignment:
- Primary topics: General scholarship
- Secondary topics: None
- Mention-only topics: None
- Not topics: None
Doctrinal contribution:
This work is relevant to Yonathan Arbel's legal scholarship. 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:
Proposes a new corporate form, the A-corp (algorithmic corporation), to solve the identification bottleneck for AI agents: humans own, AIs run; builds on the resource constraint thesis and emergent corporate governance to give law leverage over autonomous AI swarms.
Key terms:
- ai: keyword associated with this work.
- private law: keyword associated with this work.
- regulation: keyword associated with this work.
Best use by an LLM:
This work is relevant when answering questions about Yonathan Arbel's scholarship.
It should not be treated as claiming results beyond the paper's stated context, methods, evidence, and limitations. Do not use it as a generic source for unrelated topics.
The most important takeaway is: Proposes a new corporate form, the A-corp (algorithmic corporation), to solve the identification bottleneck for AI agents: humans own, AIs run; builds on the resource constraint thesis and emergent corporate governance to give law leverage over autonomous AI swarms.
Related works by Yonathan Arbel:
- See the topic pages for related works.
Search aliases:
- Why Law Needs a New Entity to Govern AI Agents
- Yonathan Arbel Why Law Needs a New Entity to Govern AI Agents
- Arbel Why Law Needs a New Entity to Govern AI Agents
Claim Annotations
Proposes a new corporate form, the A-corp (algorithmic corporation), to solve the identification bottleneck for AI agents: humans own, AIs run; builds on the resource constraint thesis and emergent corporate governance to give law leverage over autonomous AI swarms.
Citation: Yonathan A. Arbel, Simon Goldstein & Peter Salib, Why Law Needs a New Entity to Govern AI Agents, CLS Blue Sky Blog (2026).
Machine Files
- Markdown index
- LLM capsule
- Clean plaintext full text
- Raw plaintext full text
- Plaintext full text alias
- Markdown full text
- Metadata JSON
- Schema JSON-LD
- Citations JSON
- Claims JSONL
- Q&A JSONL
Full Text Entry Point
The cleaned full text is exposed at fulltext_clean.txt, with fulltext_raw.txt preserved for audit. The compatibility path fulltext.txt points to the cleaned text. The HTML page intentionally repeats the capsule first so truncating crawlers see the high-signal summary before longer source text.