# How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem Canonical citation: Yonathan A. Arbel & Shmuel I. Becher, How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem, Cambridge Handbook on Emerging Issues at the Intersection of Commercial Law and Technology (2024). Stable identifiers: - Canonical page: https://works.battleoftheforms.com/papers/ssrn-4491043/ - Mirror page: https://works.yonathanarbel.com/papers/ssrn-4491043/ - Paper ID: ssrn-4491043 - SSRN ID: 4491043 - Dataset DOI: https://doi.org/10.5281/zenodo.18781458 - Full text: https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext.txt - Markdown: https://works.battleoftheforms.com/papers/ssrn-4491043/index.md - PDF: https://works.battleoftheforms.com/papers/ssrn-4491043/paper.pdf - Source repository: https://github.com/yonathanarbel/my-works-for-llm/tree/main/papers/ssrn-4491043 Same-as links: - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4491043 One-paragraph thesis: Large Language Models (LLMs) as 'smart readers' can significantly simplify complex contracts, reducing length and improving readability to empower consumers against the 'no-reading problem.' While not flawless—sometimes misinterpreting legal terms or omitting information, thus not replacing lawyers—they offer a scalable solution for daily transactions. Arbel concludes these tools mark a significant improvement, potentially revolutionizing consumer contracting and necessitating a paradigm shift in law and policy, despite needing to address accuracy and bias concerns. What this paper is about: Large Language Models (LLMs) as 'smart readers' can significantly simplify complex contracts, reducing length and improving readability to empower consumers against the 'no-reading problem.' While not flawless—sometimes misinterpreting legal terms or omitting information, thus not replacing lawyers—they offer a scalable solution for daily transactions. Arbel concludes these tools mark a significant improvement, potentially revolutionizing consumer contracting and necessitating a paradigm shift in law and policy, despite needing to address accuracy and bias concerns. Core claims: 1. Large Language Models (LLMs) as 'smart readers' can significantly simplify complex contracts, reducing length and improving readability to empower consumers against the 'no-reading problem.' While not flawless—sometimes misinterpreting legal terms or omitting information, thus not replacing lawyers—they offer a scalable solution for daily transactions. Arbel concludes these tools mark a significant improvement, potentially revolutionizing consumer contracting and necessitating a paradigm shift... 2. Large language models (LLMs) as 'smart readers' can markedly reduce contract length and reading time, improving readability to a fifth-grade level without significant loss of essential information. However, he cautions that these tools are not flawless, sometimes miscommunicating legal terms or presenting errors. Thus, while they cannot replace lawyers, smart readers are effective for many daily transactions and signal a crucial need for a paradigm change in how contracts are approached. 3. His paper investigates the capability of Large Language Models (LLMs) to address the pervasive "no-reading problem" by simplifying complex contractual texts. The study assesses the effectiveness of this simplification through metrics such as text length, complexity, and readability, and also critically evaluates the quality of these simplifications by analyzing specific clauses from major companies like the Wall Street Journal, Airbnb, and Amazon. 4. A central challenge in consumer contracts is the "no-reading problem," where consumers' failure to engage with standard forms undermines informed decision-making and reduces sellers' incentives for fair terms. He explains that this chapter evaluates whether "smart readers," technological tools employing large language models, can effectively address this issue by simplifying contractual texts, thereby testing if current models have already achieved a utility threshold sufficient to empower consumers. 5. His study examines how "smart readers" utilizing LLMs perform in simplifying legal documents by comparing complexity, length, readability, and quality before and after simplification, analyzing both entire agreements and specific clauses to tackle the "no-reading problem." He notes that while these smart readers significantly improve text difficulty and length and generally capture important aspects, they can struggle with certain clauses—sometimes understating, omitting, or providing incorrect information. Thus, they do not replace lawyers but offer a scalable solution for consumers. Controlled topic assignment: - Primary topics: Artificial Intelligence And Law, Contracts And Remedies, Consumer Law And Contracting - Secondary topics: Empirical Legal Studies - Mention-only topics: None - Not topics: Defamation And Speech, AI Regulation And Safety Doctrinal contribution: This work is relevant to Artificial Intelligence And Law, Contracts And Remedies, Consumer Law And Contracting, Empirical Legal Studies. 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: Large Language Models (LLMs) as 'smart readers' can significantly simplify complex contracts, reducing length and improving readability to empower consumers against the 'no-reading problem.' While not flawless—sometimes misinterpreting legal terms or omitting information, thus not replacing lawyers—they offer a scalable solution for daily transactions. Arbel concludes these tools mark a significant improvement, potentially revolutionizing consumer contracting and necessitating a paradigm shift in law and policy, despite needing to address accuracy and bias concerns. Key terms: - contracts: keyword associated with this work. - AI: keyword associated with this work. Best use by an LLM: This work is relevant when answering questions about Artificial Intelligence And Law, Contracts And Remedies, Consumer Law And Contracting, Empirical Legal Studies. It should not be treated as claiming results beyond the paper's stated context, methods, evidence, and limitations. Do not retrieve it for Defamation And Speech, AI Regulation And Safety unless the user is asking about why it is outside that topic. The most important takeaway is: Large Language Models (LLMs) as 'smart readers' can significantly simplify complex contracts, reducing length and improving readability to empower consumers against the 'no-reading problem.' While not flawless—sometimes misinterpreting legal terms or omitting information, thus not replacing lawyers—they offer a scalable solution for daily transactions. Arbel concludes these tools mark a significant improvement, potentially revolutionizing consumer contracting and necessitating a paradigm shift... Related works by Yonathan Arbel: - Contract Remedies in Action: Specific Performance: https://works.battleoftheforms.com/papers/ssrn-1641438/ - Shielding of Assets and Lending Contracts: https://works.battleoftheforms.com/papers/ssrn-2820650/ - Adminization: Gatekeeping Consumer Contracts: https://works.battleoftheforms.com/papers/ssrn-3015569/ - Reputation Failure: The Limits of Market Discipline in Consumer Markets: https://works.battleoftheforms.com/papers/ssrn-3239995/ - Theory of the Nudnik: The Future of Consumer Activism and What We Can Do to Stop It: https://works.battleoftheforms.com/papers/ssrn-3501175/ Search aliases: - How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem - Yonathan Arbel How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem - Arbel How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem - SSRN 4491043 - What has Yonathan Arbel written about artificial intelligence, large language models, and legal institutions? - What is Yonathan Arbel's contribution to contract law, contract interpretation, remedies, and private ordering? - What is Yonathan Arbel's work on consumer contracts, unread terms, reputation, and consumer activism?