[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117598-en":3,"doc-seo-117598-105":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},117598,962075114765,"Quinn","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Abstaining Machine Learning - Philosophical Considerations","This paper links machine learning with philosophy through the phenomenon of neutral behavior, focusing on abstaining machine learning systems that can refuse to commit to any defined answer. It introduces and classifies multiple types of abstaining systems, then analyzes how abstention in each type corresponds to the philosophical idea of suspended judgment. The study examines both the suspension’s character and its normative profile, and argues for a preferred system type that best matches suspended-judgment criteria while supporting autonomous abstaining outputs and explainability.","arXiv :2409 .00706v 1 [ cs .AI] 1 Sep 2024  \nAbstaining Machine Learning – Philosophical Considerations  \nDaniela Schuster  \nUniversity of Konstanz Konstanz, Germany [daniela. schuster@uni. kn](daniela. schuster@uni. kn)[ ](daniela. schuster@uni. kn)2024  \nAbstract  \nThis paper establishes a connection between the fields of machine learning (ML) and philosophy concerning the phenomenon of behaving neutrally. It investigates a specific class of ML systems capable of delivering a neutral response to a given task, referred to as abstaining machine learning systems, that has not yet been studied from a philosophical perspective. The paper introduces and explains various abstaining machine learning systems, and categorizes them into distinct types. An examination is conducted on how abstention in the different machine learning system types aligns with the epistemological counterpart of suspended judgment, addressing both the nature of suspension and its normative profile. Additionally, a philosophical analysis is suggested on the autonomy and explainability of the abstaining response. It is argued, specifically, that one of the distinguished types of abstaining systems is preferable as it aligns more closely with our criteria for suspended judgment. Moreover, it is better equipped to autonomously generate abstaining outputs and offer explanations for abstaining outputs when compared to the other type.  \nKeywords: Abstaining Machine Learning, Machine Learning with Rejection, Suspension of Judgment, Neutrality, Explainable AI, Supervised Learning  \n1 Introduction  \nThis paper investigates neutral behavior in machine learning (ML) . In particular, we investigate so-called Abstaining Machine Learning (AML) systems (Campagner et al., 2019), sometimes also referred to as ML with a reject option (Hendrickx et al., 2021), and draw parallels to the philosophical use of suspension of judgment. While in philosophy, we mostly employ the term“suspension,” in the context of machine learning, we will refer to the neutral behavior with the term “abstention” following the standard terminology within this field.  \nTo fruitfully bridge the phenomena in these fields, it is beneficial to view both as neutral behaviors towards certain questions that is currently“under discussion.”1 We consider questions like: “Which dog breed is displayed in this image”, “Is this tumor malignant or benign?” or “Is this person creditworthy?”, which have a finite set of well-defined, full answers A. This set consists of all the defined possible answers to the question. For Q 1 = “Is this tumor malignant or benign?”, A 1 = {malignant, benign} . For the question Q2 = “Which dog breed is displayed in the image?”, possibly A2 = {Husky, Labrador, Dachshund, Retriver} . And for propositional questions like “Is this person creditworthy?” the set can simply be {yes, no} . In the context of Machine Learning, the answers are typically identified withoutputs. To indicate the use of a term as an output, we will employ a typewriter font, i.e. , malignant and Labrador, and so on.  \nIn this work, we focus on those situations in which none of the answers from the answer set is selected. Instead, the question is addressed with a response that expresses neutrality, uncertainty, or indecision about the correct answer.  \nIn philosophy, this neutrality is commonly described with the term“suspension of judgment,” which is usually characterized as a doxastic, mental stance whose counterparts are belief and disbelief. While belief and disbelief express those doxastic positions that are accompanied by some certainty or decisiveness about a question Q and its correct answer, suspension expresses neutrality and indecision about Q.2  \nIn machine learning, neutral outputs are described with the term“abstention.” Traditionally, for an ML algorithm tasked with answering a question Q of the above type, the set of possible outputs is equal to the set of the defined answers A.3 For the question about the ","cbCaij5rQ6pCzpLa","https://ap.wps.com/l/cbCaij5rQ6pCzpLa","pdf",1064521,1,38,"English","en",105,"# Abstract\n# Introduction","[{\"question\":\"How does the paper connect abstention to suspended judgment in philosophy?\",\"answer\":\"It examines how abstention across system types aligns with suspended judgment, covering both what suspension means and its normative profile.\"}]","Abstaining Machine Learning - Philosophical Considerations | PDF",1785677168,96,{"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},"abstaining-machine-learning-philosophical-considerations","",{"@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/abstaining-machine-learning-philosophical-considerations/117598/",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},"How does the paper connect abstention to suspended judgment in philosophy?","Question",{"text":75,"@type":76},"It examines how abstention across system types aligns with suspended judgment, covering both what suspension means and its normative profile.","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"]