[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117207-en":3,"doc-seo-117207-105":30,"detail-sidebar-cat-0-en-105":83},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117207,5909877438554,"Maeve","https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272",8,"Research & Report","Machine learning and law","Machine learning is presented as a rapidly maturing technology whose successes and everyday deployment can create exaggerated expectations about limitless automation, including in legal settings. The chapter explains that myths and misunderstandings shape debate on the regulation and application framework for machine learning, affecting discussion quality. It introduces a general overview of machine learning, then highlights selected legal-domain applications and related reviews. Finally, it details key widely discussed problems in machine learning and law, including (in)comprehensibility and lack of transparency.","| 27. Machine learning and law |\n| --- |\n| Andrzej Porębski1 |\n| 1. INTRODUCTION\u003Cbr>In recent years, machine learning has achieved several triumphs. These achievements are by no means limited to sensational events, such as the 2011 victory of the widely used machine learning system Watson on the Jeopardy! television quiz show (Ferrucci, 2012), the 2016 defeat of the masters of the extremely difficult game of Go by the deep-learning-based AlphaGo programme (Silver et al., 2017) or the 2022 approval of a conditionally autonomous (level 3, see: SAE International, 2021) Mercedes S-Class car by Germany (Harley, 2022). Above all, the achievement of machine learning is a general trend, which clearly indicates a rapid development of this class of technology (Maslej et al., 2023; Zhang et al., 2022; Pugliese, Regondi & Marini, 2021; Deloitte, 2019; Anthony, 2021). At the same time, the machine learning approach can be used in a wide range of fields (e.g. Sarker, 2021). Therefore, unsurprisingly, machine-learning-based solutions are increasingly being developed in the legal domain2 (Montelongo & Becker, 2020), both by legal scholars for academic purposes and by external companies for use by legal practitioners and law application institutions.\u003Cbr>Machine learning is, in fact, a vastly advantageous technology with enormous potential, as evidenced by both its sensational successes and its rapid deployment. Today, the products of machine learning algorithms are (often unknowingly) being used by almost everyone accessing search engines (Nayak, 2022) or taking photos with a smartphone (Morikawa et al., 2021; Tsai & Pandey, 2020). However, the high potential and widespread use of machine learning may give the misleading impression that the technology has almost unlimited possibilities and can quickly automate or improve various activities, including in the legal domain. A considerable number of myths, sometimes very far-fetched, have emerged around machine learning (see, [e.g. de](e.g. de) Saint Laurent, 2018; Floridi, 2020; Natale & Ballatore, 2020).3 These affect the quality of the ongoing discussion about the possibilities and framework of its application, the regulation of machine learning and other related issues. |\n\n1 This research was funded by the National Science Centre, Poland, and is the result of research project no. 2022/45/N/HS5/00871. The publication has been supported by a grant from the Doctoral School in the Social Sciences under the Strategic Programme Excellence Initiative at Jagiellonian University.  \n2 When I use the term “legal domain” in this chapter, I have in mind both legal scholarship and the practice of law in its broadest sense.  \n3 In this text, I will radically avoid the term “artificial intelligence”(except for the “eXplainable Artificial Intelligence” trend name) because of its vagueness, the heterogeneity in its definition and the problem related to its perception in non-technical janucircles: it bears more reference to science fiction and pop culture than the actual state of technological development. However, it is important to be aware that technologies referred to as artificial intelligence will very often be based on machine learning. The denotation of the term “machine learning” will either be subordinate to the denotation of the term“artificial intelligence” or crossed with it. Therefore, in practice, many of the myths about artificial intelligence will project themselves onto machine learning.  \nDownload4e0from  \nAndrzej Porębski - 9781803921327 [https://www.elgaronline.com/ at](https://www.elgaronline.com/ at) 12/14/2023 03:10:33PM  \nvia Open Access . Chapter 27 is available for free as Open Access from the  \nindividual product page at [www.elgaronline.com](www.elgaronline.com) under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International ([https://creativecommons.org/licenses/by-nc-nd/4.0/](https://creativecommons.org/licenses/by-nc-nd/4.0/) ) license.  \n[https://creativecommon","cbCaioMzp5OfFf4l","https://ap.wps.com/l/cbCaioMzp5OfFf4l","pdf",333409,1,18,"English","en",105,"# Introduction\n# Machine learning – An","[{\"question\":\"What specific issues related to machine learning and law are emphasized?\",\"answer\":\"The chapter focuses on (in)comprehensibility and lack of transparency as widely debated problems affecting how machine learning should be used and governed in legal contexts.\"}]","Machine learning and law | PDF",1785674416,45,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":78,"head_meta":80,"extra_data":82,"updated_unix":28},"machine-learning-and-law","",{"@graph":36,"@context":77},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-and-law/117207/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71],{"name":72,"@type":73,"acceptedAnswer":74},"What specific issues related to machine learning and law are emphasized?","Question",{"text":75,"@type":76},"The chapter focuses on (in)comprehensibility and lack of transparency as widely debated problems affecting how machine learning should be used and governed in legal contexts.","Answer","https://schema.org",{"og:url":52,"og:type":79,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":81,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":84},[85,89,93,97,102,107,112,115,120,123,127],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":86,"show_sort_weight":87,"slug":88},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":90,"show_sort_weight":91,"slug":92},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Exam",70,"exam",{"id":98,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},5,"Comic",60,"comic",{"id":103,"doc_module":4,"doc_module_name":46,"category_name":104,"show_sort_weight":105,"slug":106},6,"Technology",50,"technology",{"id":108,"doc_module":4,"doc_module_name":46,"category_name":109,"show_sort_weight":110,"slug":111},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":113,"slug":114},30,"research-report",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":46,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":98,"slug":130},19,"General","general"]