# Study pack: TAX LEVERS FOR A SAFER AI FUTURE (ssrn-5181207)

- SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5181207
- Full text: `papers/ssrn-5181207/paper.txt`
- Summary (EN): `papers/ssrn-5181207/summary.md`
- Summary (ZH): `papers/ssrn-5181207/summary.zh.md`

## Elevator pitch

Professor Yonathan Arbel of the University of Alabama School of Law argues that a "capability-safety gap" in AI development, where private firms reap rewards while society bears risks, creates a social misalignment. He proposes using tax policy to address this by re-conceptualizing R&D credits to incentivize safety research, offering consumer credits for safe AI, imposing penalties for non-compliance, and redistributing penalty revenue. This approach aims to embed safety imperatives directly into the economic architecture of AI development, aligning private profit with social welfare.

## Keywords / concepts

contracts; AI; law

## Suggested questions (for RAG / study)

- What is the paper’s main claim and what problem does it solve?
- What method/data does it use (if any), and what are the main results?
- What assumptions are doing the most work?
- What are the limitations or failure modes the author flags?
- How does this connect to the author’s other papers in this corpus?

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