# Study pack:  (ssrn-4962098)

- SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4962098
- Full text: `papers/ssrn-4962098/paper.txt`
- Summary (EN): `papers/ssrn-4962098/summary.md`
- Summary (ZH): `papers/ssrn-4962098/summary.zh.md`

## Elevator pitch

Professor Yonathan Arbel of the University of Alabama School of Law argues that his large-scale big data analysis empirically demonstrates modern contracts are overwhelmingly unreadable, often requiring college-level comprehension. This pervasive incomprehensibility fundamentally challenges contract law's core assumptions about informed consent and the "meeting of minds," as most individuals cannot understand the terms binding them. Arbel suggests this "readability crisis," with readability often worsening over time, necessitates a reevaluation of legal doctrines and a push for greater contractual clarity to ensure fairness and true agreement in economic and social interactions.

## 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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