{"id":23035,"date":"2019-08-02T08:30:28","date_gmt":"2019-08-02T15:30:28","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=23035"},"modified":"2019-08-03T09:53:42","modified_gmt":"2019-08-03T16:53:42","slug":"ai-for-legalese","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2019\/08\/02\/ai-for-legalese\/","title":{"rendered":"AI for Legalese"},"content":{"rendered":"\n<p>Have you ever signed a lengthy legal contract you didn&#8217;t fully read? Or have you every read a contract you didn&#8217;t fully understand? Contract review is a time-consuming and labor-intensive process for everyone concerned &#8212; including contract attorneys. Help is on the way. IBM researchers are exploring ways for AI to make tedious tasks like contract review easier, faster, and more accurate.&nbsp; &nbsp; <\/p>\n\n\n\n<p>A team from IBM Research-Almaden led by Yunyao Li demonstrated at the  57th Annual Meeting of the Association for Computational Linguistics  (ACL 2019) a new tool created in collaboration with researchers from the  University of Michigan called <a rel=\"noreferrer noopener\" aria-label=\"HEIDL (opens in a new tab)\" href=\"https:\/\/www.ibm.com\/blogs\/research\/2019\/07\/heidl-acl2019\/\" target=\"_blank\">HEIDL<\/a> (Human-in-the-loop linguistic  Expressions wIth Deep Learning). HEIDL is a natural language processing (NLP) tool that works with humans to both label training data and improve the machine-learned model. Details of the research are available in the paper &#8220;<a href=\"https:\/\/arxiv.org\/abs\/1907.11184\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop (opens in a new tab)\">HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop<\/a>.&#8221; The demo video below uses contract language labeled by IBM attorneys to illustrate how NLP can classify key terms and phrases with input from subject matter experts &#8212; bringing us one step closer to understanding both deep learning and contracts.&nbsp; <\/p>\n\n\n\n<figure class=\"wp-block-embed-youtube wp-block-embed is-type-video is-provider-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\"  id=\"_ytid_58283\"  width=\"480\" height=\"270\"  data-origwidth=\"480\" data-origheight=\"270\" src=\"https:\/\/www.youtube.com\/embed\/9tBdqRrbvXA?enablejsapi=1&#038;autoplay=0&#038;cc_load_policy=0&#038;cc_lang_pref=&#038;iv_load_policy=1&#038;loop=0&#038;modestbranding=0&#038;rel=1&#038;fs=1&#038;playsinline=0&#038;autohide=2&#038;theme=dark&#038;color=red&#038;controls=1&#038;\" class=\"__youtube_prefs__  epyt-is-override  no-lazyload\" title=\"YouTube player\"  allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen data-no-lazy=\"1\" data-skipgform_ajax_framebjll=\"\"><\/iframe>\n<\/div><\/figure>\n\n\n\n<p>While the role of humans is increasingly recognized in machine learning  community, representation of and interaction with models in current  <em>human-in-the-loop machine learning<\/em> (HITL-ML) approaches are too  low-level and far-removed from human&#8217;s conceptual models. The researchers demonstrate, a prototype HITL-ML system that exposes the machine-learned model through high-level, explainable linguistic expressions formed of predicates representing semantic structure of text. <\/p>\n\n\n\n<p>In HEIDL, the human&#8217;s role is elevated from simply evaluating model  predictions to interpreting and even updating the model logic directly  by enabling interaction with rule predicates themselves. Raising the  currency of interaction to such semantic levels calls for new  interaction paradigms between humans and machines that result in improved productivity for text analytics model development process. Moreover, by involving humans in the process, the human-machine co-created models generalize better to unseen data as domain experts are able to instill their expertise by extrapolating from what has been learned by automated algorithms from few labeled data. <\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"alignleft is-resized\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/insidebigdata.com\/wp-content\/uploads\/2018\/12\/Daniel_2018_pic.png\" alt=\"\" class=\"wp-image-21778\" width=\"117\" height=\"134\" srcset=\"https:\/\/insidebigdata.com\/wp-content\/uploads\/2018\/12\/Daniel_2018_pic.png 200w, https:\/\/insidebigdata.com\/wp-content\/uploads\/2018\/12\/Daniel_2018_pic-131x150.png 131w\" sizes=\"(max-width: 117px) 100vw, 117px\" \/><\/figure><\/div>\n\n\n\n<p><em>Contributed by Daniel D. Gutierrez, Managing Editor and Resident \nData Scientist for insideBIGDATA. In addition to being a tech \njournalist, Daniel also is a consultant in data scientist, author, \neducator and sits on a number of advisory boards for various start-up \ncompanies.&nbsp;<\/em><\/p>\n\n\n\n<p><em>Sign up for the free insideBIGDATA&nbsp;<a href=\"http:\/\/insidebigdata.com\/newsletter\/\" target=\"_blank\" rel=\"noreferrer noopener\">newsletter<\/a>.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Have you ever signed a lengthy legal contract you didn&#8217;t fully read? Or have you every read a contract you didn&#8217;t fully understand? Contract review is a time-consuming and labor-intensive process for everyone concerned &#8212; including contract attorneys. Help is on the way. IBM researchers are exploring ways for AI to make tedious tasks like contract review easier, faster, and more accurate.    <\/p>\n","protected":false},"author":37,"featured_media":22584,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[526,115,87,180,173,56,77,84,1],"tags":[437,324,264,283,784,635,95],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AI for Legalese - insideBIGDATA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/insidebigdata.com\/2019\/08\/02\/ai-for-legalese\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI for Legalese - insideBIGDATA\" \/>\n<meta property=\"og:description\" content=\"Have you ever signed a lengthy legal contract you didn&#039;t fully read? Or have you every read a contract you didn&#039;t fully understand? Contract review is a time-consuming and labor-intensive process for everyone concerned -- including contract attorneys. Help is on the way. IBM researchers are exploring ways for AI to make tedious tasks like contract review easier, faster, and more accurate.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/insidebigdata.com\/2019\/08\/02\/ai-for-legalese\/\" \/>\n<meta property=\"og:site_name\" content=\"insideBIGDATA\" \/>\n<meta property=\"article:publisher\" content=\"http:\/\/www.facebook.com\/insidebigdata\" \/>\n<meta property=\"article:published_time\" content=\"2019-08-02T15:30:28+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2019-08-03T16:53:42+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/insidebigdata.com\/wp-content\/uploads\/2019\/05\/Artificial_intelligence_SHUTTERSTOCK.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"300\" \/>\n\t<meta property=\"og:image:height\" content=\"203\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Daniel Gutierrez\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@AMULETAnalytics\" \/>\n<meta name=\"twitter:site\" content=\"@insideBigData\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Daniel Gutierrez\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/insidebigdata.com\/2019\/08\/02\/ai-for-legalese\/\",\"url\":\"https:\/\/insidebigdata.com\/2019\/08\/02\/ai-for-legalese\/\",\"name\":\"AI for Legalese - insideBIGDATA\",\"isPartOf\":{\"@id\":\"https:\/\/insidebigdata.com\/#website\"},\"datePublished\":\"2019-08-02T15:30:28+00:00\",\"dateModified\":\"2019-08-03T16:53:42+00:00\",\"author\":{\"@id\":\"https:\/\/insidebigdata.com\/#\/schema\/person\/2540da209c83a68f4f5922848f7376ed\"},\"breadcrumb\":{\"@id\":\"https:\/\/insidebigdata.com\/2019\/08\/02\/ai-for-legalese\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/insidebigdata.com\/2019\/08\/02\/ai-for-legalese\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/insidebigdata.com\/2019\/08\/02\/ai-for-legalese\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/insidebigdata.com\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"AI for Legalese\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/insidebigdata.com\/#website\",\"url\":\"https:\/\/insidebigdata.com\/\",\"name\":\"insideBIGDATA\",\"description\":\"Your Source for AI, Data Science, Deep Learning &amp; Machine Learning Strategies\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/insidebigdata.com\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/insidebigdata.com\/#\/schema\/person\/2540da209c83a68f4f5922848f7376ed\",\"name\":\"Daniel Gutierrez\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/insidebigdata.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/5780282e7e567e2a502233e948464542?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/5780282e7e567e2a502233e948464542?s=96&d=mm&r=g\",\"caption\":\"Daniel Gutierrez\"},\"description\":\"Daniel D. Gutierrez is a Data Scientist with Los Angeles-based AMULET Analytics, a service division of AMULET Development Corp. He's been involved with data science and Big Data long before it came in vogue, so imagine his delight when the Harvard Business Review recently deemed \\\"data scientist\\\" as the sexiest profession for the 21st century. Previously, he taught computer science and database classes at UCLA Extension for over 15 years, and authored three computer industry books on database technology. He also served as technical editor, columnist and writer at a major computer industry monthly publication for 7 years. 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Gutierrez is a Data Scientist with Los Angeles-based AMULET Analytics, a service division of AMULET Development Corp. He's been involved with data science and Big Data long before it came in vogue, so imagine his delight when the Harvard Business Review recently deemed \"data scientist\" as the sexiest profession for the 21st century. Previously, he taught computer science and database classes at UCLA Extension for over 15 years, and authored three computer industry books on database technology. He also served as technical editor, columnist and writer at a major computer industry monthly publication for 7 years. Follow his data science musings at @AMULETAnalytics.","sameAs":["http:\/\/www.insidebigdata.com","https:\/\/twitter.com\/@AMULETAnalytics"],"url":"https:\/\/insidebigdata.com\/author\/dangutierrez\/"}]}},"jetpack_featured_media_url":"https:\/\/insidebigdata.com\/wp-content\/uploads\/2019\/05\/Artificial_intelligence_SHUTTERSTOCK.jpg","jetpack_shortlink":"https:\/\/wp.me\/p9eA3j-5Zx","jetpack-related-posts":[{"id":22567,"url":"https:\/\/insidebigdata.com\/2019\/05\/04\/accelerating-training-for-ai-deep-learning-networks-with-chunking\/","url_meta":{"origin":23035,"position":0},"title":"Accelerating Training for AI Deep Learning Networks with \u201cChunking\u201d","date":"May 4, 2019","format":false,"excerpt":"At the International Conference on Learning Representations on May 6, IBM Research will share a deeper look around how chunk-based accumulation can speed the training for deep learning networks used for artificial intelligence (AI).","rel":"","context":"In &quot;AI Deep Learning&quot;","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/insidebigdata.com\/wp-content\/uploads\/2019\/05\/Deep_Learning_shutterstock_386816095.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":24721,"url":"https:\/\/insidebigdata.com\/2020\/07\/11\/research-highlights-exbert\/","url_meta":{"origin":23035,"position":1},"title":"Research Highlights: ExBERT","date":"July 11, 2020","format":false,"excerpt":"In the insideBIGDATA Research Highlights column we take a look at new and upcoming results from the research community for data science, machine learning, AI and deep learning. 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