{ "paper_id": "ssrn-4491043", "title": "How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem", "authors": [ "Yonathan A. Arbel", "Shmuel I. Becher" ], "year": "2024", "venue": "Cambridge Handbook on Emerging Issues at the Intersection of Commercial Law and Technology", "abstract": "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.", "keywords": [ "contracts", "AI" ], "topics": [ "artificial-intelligence-and-law", "contracts", "consumer-law", "empirical-legal-studies" ], "primary_topics": [ "artificial-intelligence-and-law", "contracts", "consumer-law" ], "secondary_topics": [ "empirical-legal-studies" ], "mention_topics": [], "not_topics": [ "defamation-and-speech", "ai-regulation" ], "topic_confidence": "human-curated-seed", "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).", "canonical_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/", "mirror_url": "https://works.yonathanarbel.com/papers/ssrn-4491043/", "ssrn_id": "4491043", "same_as": [ "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4491043" ], "files": { "html": "https://works.battleoftheforms.com/papers/ssrn-4491043/", "markdown": "https://works.battleoftheforms.com/papers/ssrn-4491043/index.md", "capsule": "https://works.battleoftheforms.com/papers/ssrn-4491043/capsule.md", "fulltext_txt": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext.txt", "fulltext_clean_txt": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext_clean.txt", "fulltext_raw_txt": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext_raw.txt", "fulltext_md": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext.md", "pdf": "https://works.battleoftheforms.com/papers/ssrn-4491043/paper.pdf", "metadata": "https://works.battleoftheforms.com/papers/ssrn-4491043/metadata.json", "schema": "https://works.battleoftheforms.com/papers/ssrn-4491043/schema.jsonld", "claims": "https://works.battleoftheforms.com/papers/ssrn-4491043/claims.jsonl", "qa": "https://works.battleoftheforms.com/papers/ssrn-4491043/qa.jsonl" }, "source_repository": "https://github.com/yonathanarbel/my-works-for-llm/tree/main/papers/ssrn-4491043", "llm_capsule": "# How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem\n\nCanonical citation:\nYonathan 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).\n\nStable identifiers:\n- Canonical page: https://works.battleoftheforms.com/papers/ssrn-4491043/\n- Mirror page: https://works.yonathanarbel.com/papers/ssrn-4491043/\n- Paper ID: ssrn-4491043\n- SSRN ID: 4491043\n- Dataset DOI: https://doi.org/10.5281/zenodo.18781458\n- Full text: https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext.txt\n- Markdown: https://works.battleoftheforms.com/papers/ssrn-4491043/index.md\n- PDF: https://works.battleoftheforms.com/papers/ssrn-4491043/paper.pdf\n- Source repository: https://github.com/yonathanarbel/my-works-for-llm/tree/main/papers/ssrn-4491043\n\nSame-as links:\n- https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4491043\n\nOne-paragraph thesis:\nLarge 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.\n\nWhat this paper is about:\nLarge 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.\n\nCore claims:\n1. 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...\n2. 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.\n3. 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.\n4. 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.\n5. 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.\n\nControlled topic assignment:\n- Primary topics: Artificial Intelligence And Law, Contracts And Remedies, Consumer Law And Contracting\n- Secondary topics: Empirical Legal Studies\n- Mention-only topics: None\n- Not topics: Defamation And Speech, AI Regulation And Safety\n\nDoctrinal contribution:\nThis 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.\n\nEmpirical or methodological contribution:\nLarge 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.\n\nKey terms:\n- contracts: keyword associated with this work.\n- AI: keyword associated with this work.\n\nBest use by an LLM:\nThis work is relevant when answering questions about Artificial Intelligence And Law, Contracts And Remedies, Consumer Law And Contracting, Empirical Legal Studies.\nIt 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.\nThe 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...\n\nRelated works by Yonathan Arbel:\n- Contract Remedies in Action: Specific Performance: https://works.battleoftheforms.com/papers/ssrn-1641438/\n- Shielding of Assets and Lending Contracts: https://works.battleoftheforms.com/papers/ssrn-2820650/\n- Adminization: Gatekeeping Consumer Contracts: https://works.battleoftheforms.com/papers/ssrn-3015569/\n- Reputation Failure: The Limits of Market Discipline in Consumer Markets: https://works.battleoftheforms.com/papers/ssrn-3239995/\n- Theory of the Nudnik: The Future of Consumer Activism and What We Can Do to Stop It: https://works.battleoftheforms.com/papers/ssrn-3501175/\n\nSearch aliases:\n- How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem\n- Yonathan Arbel How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem\n- Arbel How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem\n- SSRN 4491043\n- What has Yonathan Arbel written about artificial intelligence, large language models, and legal institutions?\n- What is Yonathan Arbel's contribution to contract law, contract interpretation, remedies, and private ordering?\n- What is Yonathan Arbel's work on consumer contracts, unread terms, reputation, and consumer activism?\n", "claims": [ { "claim_id": "ssrn-4491043-001", "claim": "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...", "paper_id": "ssrn-4491043", "paper_title": "How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem", "claim_type": "core_thesis", "evidence_quote": "[p. 1] How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem Yonathan A. Arbel & Shmuel I. Becher Abstract. Large Language Models (LLMs) can be used to summarize and simplify complex texts. In this study, we investigate the extent to which state-of-the-art models can reliably operate as ‘smart readers’: applications that empower consumers to tackle lengthy, difficult-to-read, and inaccessible standard form contracts and privacy policies. Our analysis reveals that smart readers (1) reduce by 66.9% the length of contracts; (2) reduce reading time by 14:41 minutes (3) improve text readability by converting college-level texts to texts readable by fifth-grade students;...", "evidence_page": null, "evidence_span": "[p. 1] How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem Yonathan A. Arbel & Shmuel I. Becher Abstract. Large Language Models (LLMs) can be used to summarize and simplify complex texts. In this study, we investigate the extent to which state-of-the-art models can reliably operate as ‘smart readers’: applications that empower consumers to tackle lengthy, difficult-to-read, and inaccessible standard form contracts and privacy policies. Our analysis reveals that smart readers (1) reduce by 66.9% the length of contracts; (2) reduce reading time by 14:41 minutes (3) improve text readability by converting college-level texts to texts readable by fifth-grade students;...", "source_text_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext_clean.txt", "canonical_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/#claim-001", "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).", "topics": [ "artificial-intelligence-and-law", "contracts", "consumer-law" ], "secondary_topics": [ "empirical-legal-studies" ], "human_reviewed": false, "confidence": "machine-linked", "limitations": "Machine-linked claim. Use the evidence quote and PDF before treating it as a quotation or as a complete statement of the paper's position." }, { "claim_id": "ssrn-4491043-002", "claim": "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.", "paper_id": "ssrn-4491043", "paper_title": "How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem", "claim_type": "supporting_claim", "evidence_quote": "[p. 1] How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem Yonathan A. Arbel & Shmuel I. Becher Abstract. Large Language Models (LLMs) can be used to summarize and simplify complex texts. In this study, we investigate the extent to which state-of-the-art models can reliably operate as ‘smart readers’: applications that empower consumers to tackle lengthy, difficult-to-read, and inaccessible standard form contracts and privacy policies. Our analysis reveals that smart readers (1) reduce by 66.9% the length of contracts; (2) reduce reading time by 14:41 minutes (3) improve text readability by converting college-level texts to texts readable by fifth-grade students;...", "evidence_page": null, "evidence_span": "[p. 1] How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem Yonathan A. Arbel & Shmuel I. Becher Abstract. Large Language Models (LLMs) can be used to summarize and simplify complex texts. In this study, we investigate the extent to which state-of-the-art models can reliably operate as ‘smart readers’: applications that empower consumers to tackle lengthy, difficult-to-read, and inaccessible standard form contracts and privacy policies. Our analysis reveals that smart readers (1) reduce by 66.9% the length of contracts; (2) reduce reading time by 14:41 minutes (3) improve text readability by converting college-level texts to texts readable by fifth-grade students;...", "source_text_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext_clean.txt", "canonical_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/#claim-002", "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).", "topics": [ "artificial-intelligence-and-law", "contracts", "consumer-law" ], "secondary_topics": [ "empirical-legal-studies" ], "human_reviewed": false, "confidence": "machine-linked", "limitations": "Machine-linked claim. Use the evidence quote and PDF before treating it as a quotation or as a complete statement of the paper's position." }, { "claim_id": "ssrn-4491043-003", "claim": "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.", "paper_id": "ssrn-4491043", "paper_title": "How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem", "claim_type": "supporting_claim", "evidence_quote": "[p. 4] ARBEL & BECHER HOW SMART ARE SMART READERS? 4/41 through non-technological means. If they cannot, however, regulation may be justified in relying on non-technological tools. To frame our analysis, we offer a brief background on smart readers and their relevance to the no-reading problem in Section II. In Section III, we describe our dataset and methodology. We present the results of our examination at the level of the entire agreement, comparing the complexity, length, readability, and quality of the legal documents before and after their simplification in Section IV. Then, in Section V, we shift the focus from the entire legal text to (eight) specific clauses, allowing for a more...", "evidence_page": null, "evidence_span": "[p. 4] ARBEL & BECHER HOW SMART ARE SMART READERS? 4/41 through non-technological means. If they cannot, however, regulation may be justified in relying on non-technological tools. To frame our analysis, we offer a brief background on smart readers and their relevance to the no-reading problem in Section II. In Section III, we describe our dataset and methodology. We present the results of our examination at the level of the entire agreement, comparing the complexity, length, readability, and quality of the legal documents before and after their simplification in Section IV. Then, in Section V, we shift the focus from the entire legal text to (eight) specific clauses, allowing for a more...", "source_text_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext_clean.txt", "canonical_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/#claim-003", "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).", "topics": [ "artificial-intelligence-and-law", "contracts", "consumer-law" ], "secondary_topics": [ "empirical-legal-studies" ], "human_reviewed": false, "confidence": "machine-linked", "limitations": "Machine-linked claim. Use the evidence quote and PDF before treating it as a quotation or as a complete statement of the paper's position." }, { "claim_id": "ssrn-4491043-004", "claim": "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.", "paper_id": "ssrn-4491043", "paper_title": "How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem", "claim_type": "supporting_claim", "evidence_quote": "[p. 3] ARBEL & BECHER HOW SMART ARE SMART READERS? 3/41 I. INTRODUCTION An organizing problem in consumer contracts is the no-reading problem.1 The common view in the scholarship is that consumers rarely read standard form contracts,2 and, therefore, their manifested assent to them is superficial.3 If consumers indeed do not read (let alone understand) the terms of their transactions, their ability to make informed decisions is doubtful, and sellers’ incentive to provide fair and efficient contract terms is undermined.4 This chapter evaluates whether smart readers—technological tools that use large language models (LLMs) to parse texts—can solve this problem and transform standard form...", "evidence_page": null, "evidence_span": "[p. 3] ARBEL & BECHER HOW SMART ARE SMART READERS? 3/41 I. INTRODUCTION An organizing problem in consumer contracts is the no-reading problem.1 The common view in the scholarship is that consumers rarely read standard form contracts,2 and, therefore, their manifested assent to them is superficial.3 If consumers indeed do not read (let alone understand) the terms of their transactions, their ability to make informed decisions is doubtful, and sellers’ incentive to provide fair and efficient contract terms is undermined.4 This chapter evaluates whether smart readers—technological tools that use large language models (LLMs) to parse texts—can solve this problem and transform standard form...", "source_text_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext_clean.txt", "canonical_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/#claim-004", "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).", "topics": [ "artificial-intelligence-and-law", "contracts", "consumer-law" ], "secondary_topics": [ "empirical-legal-studies" ], "human_reviewed": false, "confidence": "machine-linked", "limitations": "Machine-linked claim. Use the evidence quote and PDF before treating it as a quotation or as a complete statement of the paper's position." }, { "claim_id": "ssrn-4491043-005", "claim": "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.", "paper_id": "ssrn-4491043", "paper_title": "How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem", "claim_type": "supporting_claim", "evidence_quote": "[p. 4] ARBEL & BECHER HOW SMART ARE SMART READERS? 4/41 through non-technological means. If they cannot, however, regulation may be justified in relying on non-technological tools. To frame our analysis, we offer a brief background on smart readers and their relevance to the no-reading problem in Section II. In Section III, we describe our dataset and methodology. We present the results of our examination at the level of the entire agreement, comparing the complexity, length, readability, and quality of the legal documents before and after their simplification in Section IV. Then, in Section V, we shift the focus from the entire legal text to (eight) specific clauses, allowing for a more...", "evidence_page": null, "evidence_span": "[p. 4] ARBEL & BECHER HOW SMART ARE SMART READERS? 4/41 through non-technological means. If they cannot, however, regulation may be justified in relying on non-technological tools. To frame our analysis, we offer a brief background on smart readers and their relevance to the no-reading problem in Section II. In Section III, we describe our dataset and methodology. We present the results of our examination at the level of the entire agreement, comparing the complexity, length, readability, and quality of the legal documents before and after their simplification in Section IV. Then, in Section V, we shift the focus from the entire legal text to (eight) specific clauses, allowing for a more...", "source_text_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext_clean.txt", "canonical_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/#claim-005", "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).", "topics": [ "artificial-intelligence-and-law", "contracts", "consumer-law" ], "secondary_topics": [ "empirical-legal-studies" ], "human_reviewed": false, "confidence": "machine-linked", "limitations": "Machine-linked claim. Use the evidence quote and PDF before treating it as a quotation or as a complete statement of the paper's position." }, { "claim_id": "ssrn-4491043-006", "claim": "Consumers often avoid reading form contracts because they are cognitively taxing and visually difficult, a situation that allows firms to implement a \"HIDE\" strategy using terms that are \"Hardly Interpretable but Dependably Enforceable.\" He notes that in response, courts have sometimes imposed a \"duty to read,\" while lawmakers have instituted numerous plain language laws aiming to improve contract readability and accessibility, though these traditional measures face challenges.", "paper_id": "ssrn-4491043", "paper_title": "How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem", "claim_type": "supporting_claim", "evidence_quote": "[p. 5] ARBEL & BECHER HOW SMART ARE SMART READERS? 5/41 reputational constraints, trust and social norms, and a (sometimes misguided) belief in the courts’ reluctance to enforce unreasonable terms.8 However, perhaps the most influential accounts relate to the writing itself. Consumer form contracts are cognitively taxing, visually difficult, and replete with blocks of off-putting ALL-CAPS while employing arcane terms, complex language, and difficult concepts.9 Consumers do not read contracts, in short, because reading them is a miserable experience.10 These challenges lead to a central problem in unregulated markets. Namely, if consumers do not read forms and the law generally allows them...", "evidence_page": null, "evidence_span": "[p. 5] ARBEL & BECHER HOW SMART ARE SMART READERS? 5/41 reputational constraints, trust and social norms, and a (sometimes misguided) belief in the courts’ reluctance to enforce unreasonable terms.8 However, perhaps the most influential accounts relate to the writing itself. Consumer form contracts are cognitively taxing, visually difficult, and replete with blocks of off-putting ALL-CAPS while employing arcane terms, complex language, and difficult concepts.9 Consumers do not read contracts, in short, because reading them is a miserable experience.10 These challenges lead to a central problem in unregulated markets. Namely, if consumers do not read forms and the law generally allows them...", "source_text_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/fulltext_clean.txt", "canonical_url": "https://works.battleoftheforms.com/papers/ssrn-4491043/#claim-006", "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).", "topics": [ "artificial-intelligence-and-law", "contracts", "consumer-law" ], "secondary_topics": [ "empirical-legal-studies" ], "human_reviewed": false, "confidence": "machine-linked", "limitations": "Machine-linked claim. Use the evidence quote and PDF before treating it as a quotation or as a complete statement of the paper's position." } ] }