{
  "paper_id": "ssrn-3740356",
  "title": "Contracts in the Age of Smart Readers",
  "authors": [
    "Yonathan A. Arbel",
    "Shmuel I. Becher"
  ],
  "year": "2022",
  "venue": "George Washington Law Review",
  "abstract": "What does it mean to have machines that can read, explain, and evaluate contracts? Recent advances in machine learning have led to a fundamental breakthrough in machine language models, portending a profound shift in the ability of machines to process text. Such a shift has far-reaching consequences for diverse areas of law, which are predicated on, and justified by, the existence of information barriers. Our object here is to provide a general framework for evaluating the legal and policy implications of employing language models as “smart readers”—tools that read, analyze, and assess contracts, disclosures, and privacy policies. Synthesizing state-of-the-art developments, we identify four core capabilities of smart readers. Based on real-world examples produced by new machine-learning models, we demonstrate that smart readers can: simplify complex legal language; personalize the contractual presentation to the user’s specific sociocultural identity; interpret the meaning of contractual terms; and benchmark and rank contracts based on their quality. Nevertheless, the implications of smart readers are more complex than initially meets the eye. Although smart readers can overcome traditional infor-",
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  "llm_capsule": "# Contracts in the Age of Smart Readers\n\nCanonical citation:\nYonathan A. Arbel & Shmuel I. Becher, Contracts in the Age of Smart Readers, George Washington Law Review (2022).\n\nStable identifiers:\n- Canonical page: https://works.battleoftheforms.com/papers/ssrn-3740356/\n- Mirror page: https://works.yonathanarbel.com/papers/ssrn-3740356/\n- Paper ID: ssrn-3740356\n- SSRN ID: 3740356\n- Dataset DOI: https://doi.org/10.5281/zenodo.18781458\n- Full text: https://works.battleoftheforms.com/papers/ssrn-3740356/fulltext.txt\n- Markdown: https://works.battleoftheforms.com/papers/ssrn-3740356/index.md\n- PDF: https://works.battleoftheforms.com/papers/ssrn-3740356/paper.pdf\n- Source repository: https://github.com/yonathanarbel/my-works-for-llm/tree/main/papers/ssrn-3740356\n\nSame-as links:\n- https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3740356\n\nOne-paragraph thesis:\nAI-powered \"smart readers\" represent a significant breakthrough in contract analysis, capable of simplifying, personalizing, and benchmarking terms for consumers. While offering profound benefits like increased understanding, improved market competition, and enhanced access to justice, these tools also introduce serious risks such as errors, bias, adversarial exploitation, and discrimination. Arbel calls for a new legal and regulatory framework to navigate these complex implications, as current doctrines are unprepared for this technological shift and its impact on contract law and consumer protection.\n\nWhat this paper is about:\nWhat does it mean to have machines that can read, explain, and evaluate contracts? Recent advances in machine learning have led to a fundamental breakthrough in machine language models, portending a profound shift in the ability of machines to process text. Such a shift has far-reaching consequences for diverse areas of law, which are predicated on, and justified by, the existence of information barriers. Our object here is to provide a general framework for evaluating the legal and policy implications of employing language models as “smart readers”—tools that read, analyze, and assess contracts, disclosures, and privacy policies. Synthesizing state-of-the-art developments, we identify four core capabilities of smart readers. Based on real-world examples produced by new machine-learning models, we demonstrate that smart readers can: simplify complex legal language; personalize the contractual presentation to the user’s specific sociocultural identity; interpret the meaning of contractual terms; and benchmark and rank contracts based on their quality. Nevertheless, the implications of smart readers are more complex than initially meets the eye. Although smart readers can overcome traditional infor-\n\nCore claims:\n1. What does it mean to have machines that can read, explain, and evaluate contracts? Recent advances in machine learning have led to a fundamental breakthrough in machine language models, portending a profound shift in the ability of machines to process text. Such a shift has far-reaching consequences for diverse areas of law, which are predicated on, and justified by, the existence of information barriers. Our object here is to provide a general framework for evaluating the legal and policy...\n2. AI-powered \"smart readers\" represent a significant breakthrough in contract analysis, capable of simplifying, personalizing, and benchmarking terms for consumers. While offering profound benefits like increased understanding, improved market competition, and enhanced access to justice, these tools also introduce serious risks such as errors, bias, adversarial exploitation, and discrimination. Arbel calls for a new legal and regulatory framework to navigate these complex implications, as current doctrines are unprepared for this technological shift and its impact on contract law and consumer protection.\n3. AI-powered \"smart readers\" are emerging from machine learning breakthroughs, poised to disrupt the \"dismal equilibrium\" where consumers ignore complex contract terms. these tools can simplify, personalize, interpret, and benchmark contracts, offering a technological solution to information barriers. His work explores their capabilities, potential uptake, and broad implications for contract law, including market competition, errors, access to justice, and discrimination, highlighting the need for new regulatory responses as current legal doctrines are unprepared for these advancements and their associated risks like bias and exploitation.\n4. Smart readers, powered by AI like GPT-3, possess core capabilities crucial for consumer empowerment: simplification of complex legal text, personalization to individual user needs (including linguistic and cognitive adaptations), construction of contractual meaning through explanations, and benchmarking contracts against market alternatives. these tools can make obscure clauses understandable, provide scores for privacy policies, and allow interactive questioning, offering advantages in cost, speed, and accessibility over human lawyers, thereby helping consumers comprehend fine print and understand market choices.\n5. Consumer uptake of smart readers, while potentially limited by reading aversion and cognitive biases, could significantly impact markets even with modest adoption by an \"informed minority,\" fostering term competition. these tools can act as behavioral nudges, countering cognitive overload by summarizing complex information, addressing myopia by highlighting risks like warranties, and helping consumers overcome price manipulations. The success or failure of uptake will offer insights into theories on why consumers don't read contracts, with quality, cost, and user experience being critical factors.\n\nControlled topic assignment:\n- Primary topics: Artificial Intelligence And Law, Contracts And Remedies, Consumer Law And Contracting\n- Secondary topics: Private Law And Market Institutions\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, Private Law And Market Institutions. 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:\nAI-powered \"smart readers\" represent a significant breakthrough in contract analysis, capable of simplifying, personalizing, and benchmarking terms for consumers. While offering profound benefits like increased understanding, improved market competition, and enhanced access to justice, these tools also introduce serious risks such as errors, bias, adversarial exploitation, and discrimination. Arbel calls for a new legal and regulatory framework to navigate these complex implications, as current doctrines are unprepared for this technological shift and its impact on contract law and consumer protection.\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, Private Law And Market Institutions.\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: AI-powered \"smart readers\" represent a significant breakthrough in contract analysis, capable of simplifying, personalizing, and benchmarking terms for consumers. While offering profound benefits like increased understanding, improved market competition, and enhanced access to justice, these tools also introduce serious risks such as errors, bias, adversarial exploitation, and discrimination. Arbel calls for a new legal and regulatory framework to navigate these complex implications, as...\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- Contracts in the Age of Smart Readers\n- Yonathan Arbel Contracts in the Age of Smart Readers\n- Arbel Contracts in the Age of Smart Readers\n- SSRN 3740356\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",
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      "evidence_quote": "[p. 49] \\\\jciprod01\\productn\\G\\GWN\\90-1\\GWN102.txt unknown Seq: 49 17-FEB-22 12:20 2022] CONTRACTS IN THE AGE OF SMART READERS 131 F. Nudging with Smart Readers Behavioral biases and cognitive constraints are said to undermine the ability of consumers to make prudent decisions.196 To counter some of these biases, behavioralists often recommend using various nudges that improve the decision-making environment.197 There are many different types of biases, and although smart readers do not address all of them, they do seem well poised to tackle a few major types. These include (1) cognitive overload, (2) myopia and risk discounting, and (3) price-related manipulations. Cognitive overload...",
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      "evidence_quote": "[p. 38] \\\\jciprod01\\productn\\G\\GWN\\90-1\\GWN102.txt unknown Seq: 38 17-FEB-22 12:20 120 THE GEORGE WASHINGTON LAW REVIEW [Vol. 90:83 benchmarks today evaluate language models on performance in this domain. Based on our experience using the models, we expect a large degree of error in the near future and a nontrivial improvement within a relatively short time. Critically, smart readers are useful even if they are not as accurate as their human counterparts, so long as they have a cost, consistency, and accessibility advantage over the alternatives. We already noted how, despite the potential for occasional error, firms stake billions of dollars on investment analyses produced by smart...",
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