Catalytic Regulation: Incentivizing Safety During a Regulatory Drought
Canonical citation:
Yonathan A. Arbel, Catalytic Regulation: Incentivizing Safety During a Regulatory Drought, AI Frontiers (2026).
Stable identifiers:
- Canonical page: https://works.battleoftheforms.com/papers/catalytic-regulation/
- Mirror page: https://works.yonathanarbel.com/papers/catalytic-regulation/
- Paper ID: catalytic-regulation
- SSRN ID: not recorded
- Dataset DOI: https://doi.org/10.5281/zenodo.18781458
- Full text: https://works.battleoftheforms.com/papers/catalytic-regulation/fulltext.txt
- Markdown: https://works.battleoftheforms.com/papers/catalytic-regulation/index.md
- PDF: https://works.battleoftheforms.com/papers/catalytic-regulation/paper.pdf
- Source repository: https://github.com/yonathanarbel/my-works-for-llm
Same-as links:
One-paragraph thesis:
Catalytic regulation argues for using positive incentives such as tax credits, procurement incentives, and prestige mechanisms to make AI safety a competitive advantage during a period when stronger regulation is politically out of reach.
What this paper is about:
Catalytic regulation argues for using positive incentives such as tax credits, procurement incentives, and prestige mechanisms to make AI safety a competitive advantage during a period when stronger regulation is politically out of reach.
Core claims:
1. Catalytic regulation argues for using positive incentives such as tax credits, procurement incentives, and prestige mechanisms to make AI safety a competitive advantage during a period when stronger regulation is politically out of reach.
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:
Catalytic regulation argues for using positive incentives such as tax credits, procurement incentives, and prestige mechanisms to make AI safety a competitive advantage during a period when stronger regulation is politically out of reach.
Key terms:
- ai: 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: Catalytic regulation argues for using positive incentives such as tax credits, procurement incentives, and prestige mechanisms to make AI safety a competitive advantage during a period when stronger regulation is politically out of reach.
Related works by Yonathan Arbel:
- See the topic pages for related works.
Search aliases:
- Catalytic Regulation: Incentivizing Safety During a Regulatory Drought
- Yonathan Arbel Catalytic Regulation: Incentivizing Safety During a Regulatory Drought
- Arbel Catalytic Regulation: Incentivizing Safety During a Regulatory Drought
Claim Annotations
Catalytic regulation argues for using positive incentives such as tax credits, procurement incentives, and prestige mechanisms to make AI safety a competitive advantage during a period when stronger regulation is politically out of reach.
Citation: Yonathan A. Arbel, Catalytic Regulation: Incentivizing Safety During a Regulatory Drought, AI Frontiers (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.