[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119930-en":3,"doc-seo-119930-105":30,"detail-sidebar-cat-0-en-105":91},{"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},119930,4810365810221,"Aurora","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Machine Learning and the Ethics of Induction","This chapter analyzes the inferential structure of machine learning (ML) systems and explains how, beyond widely discussed algorithmic bias, ML can embed values in unexpected ways. It argues that inductive inference in ML relies on two components: the uniformity of nature (UoN) assumption and canons of inductive inference (CIIs) that constrain hypotheses. While ethics debates often target CIIs, the chapter shows how UoN can erode human agency.","Penultimate draft. Forthcoming in Philosophy of Science for Machine Learning: Core Issues and New Perspectives, edited by Juan Duran and Giorgia Pozzi, Synthese Library, Springer  \nMACHINE LEARNING AND THE ETHICS OF INDUCTION  \nEmanuele Ratti 1  \nUniversity of Bristol  \nAbstract. This chapter analyzes the inferential structure of machine learning (ML) systems, and showshow these can be value-laden in unexpected ways. ML systems follow an inductive inferential strategy, which is based on two components. First, there is the basic assumption that we are entitled to predict future events on the basis of past occurrences because the world will not drastically change. This assumption is called ‘uniformity of nature’(UoN) . Second, ‘canons of inductive inference’ (CIIs) are required to narrow down the set of possible hypotheses that one can generate from UoN. Debates on the ethics of ML have focused on CIIs. Here I show that UoN plays an important ethical role, in particular in eroding human agency.  \nKeywords: machine learning; induction; ethics of AI; AI ethics  \n1 INTRODUCTION  \nIn the past few years, there has been a growing concern about the problem of ‘algorithmic bias’in machine learning (ML) tools. In a general sense, ‘bias’ is understood as a systematic error due to a deviation from a norm or standard, where norms or standards can be statistical, moral, epistemic, etc (Danks and London 2017) . Research has shown that, because of the way they are designed, algorithmic systems incorporate plenty of biases – in particular social and moral biases – that cause harmful impacts, especially to minorities. Stemming from these works, several proposals on how to identify biases and design algorithmic systems that are less biased have been developed (Fazelpour and Danks 2021) . All in all, this rich literature is focused on how choices behind the design of algorithmic systems have repercussions on their outputs and impact individuals differently.  \nIn this chapter, I want to show how investigating ML tools from the point of view of their inferential structure can be fruitful. In particular, I will show that (supervised) ML tools follow an inductive inferential structure, and that considering different components at play in induction allows to make different types of ethical arguments about the nature of ML tools.  \nThe structure of the chapter is as follows. In Section 2, I will make the case that (supervised) ML tools follow an inductive strategy. In particular, this strategy is based on two components. First (2.1), there is the uniformity of nature (UoN) component, according to which we are allowed to infer future observations on the basis of similar past observations because of assumed uniformity between the past and the future. This principle is insufficient to ground any reliable inference, as the past and the future may look alike in an indefinite number of ways. UoN is supplemented by non-evidential background assumptions (that is, the second component), typically called ‘canons of inductive inference’ (CII) . CIIs make sure that the space of possible ways in which the past and future are similar is narrow enough to allow inference. I then show (2.2) how ML follows this particular strategy, where CIIs take the form of different choices that shape the final ML model, and elucidate (2.3) how debates in ethics  \n[1](1mnl.ratti@gmail.com)[mnl.ratti@gmail.com](1mnl.ratti@gmail.com)  \nof ML are mostly about CIIs [see Chapter 14 in this volume]. In Section 3, I turn to the analysis of UoN, first by describing the ‘harmless’ role that it plays in the natural sciences (3.1), and then (3.2) to show how, in the context where human agency is salient, UoN can actually erode human agency itself.  \n2 INDUCTION AND MACHINE LEARNING  \nLet me start by describing the main features of induction and inductive inferences, and in which sense ML systems are inductive.  \n2.1 Varieties of Induction and Machine Learning  \nHere I refer to ‘inductive inferen","cbCaivxyeYVWk0tv","https://ap.wps.com/l/cbCaivxyeYVWk0tv","pdf",290847,1,16,"English","en",105,"# Introduction\n# Induction and Machine Learning\n## Varieties of Induction and Machine Learning\n# Uniformity of Nature and Human Agency","[{\"question\":\"What inferential structure does the chapter claim supervised ML systems follow?\",\"answer\":\"Supervised ML systems follow an inductive inferential structure built on two components: the uniformity of nature (UoN) assumption and canons of inductive inference (CIIs).\"},{\"question\":\"What is the uniformity of nature (UoN) assumption in this framework?\",\"answer\":\"UoN licenses predicting future events from similar past observations by assuming past and future will not drastically differ. The chapter argues this principle alone cannot guarantee reliable inference.\"},{\"question\":\"How does the chapter connect ML to ethics and human agency?\",\"answer\":\"It claims ethics debates often focus on CIIs, but UoN has an important ethical role, especially in eroding human agency when human agency is salient.\"}]","Machine Learning and the Ethics of Induction | PDF",1785727053,40,{"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":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-and-the-ethics-of-induction","",{"@graph":36,"@context":85},[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-the-ethics-of-induction/119930/",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","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What inferential structure does the chapter claim supervised ML systems follow?","Question",{"text":75,"@type":76},"Supervised ML systems follow an inductive inferential structure built on two components: the uniformity of nature (UoN) assumption and canons of inductive inference (CIIs).","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is the uniformity of nature (UoN) assumption in this framework?",{"text":80,"@type":76},"UoN licenses predicting future events from similar past observations by assuming past and future will not drastically differ. The chapter argues this principle alone cannot guarantee reliable inference.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the chapter connect ML to ethics and human agency?",{"text":84,"@type":76},"It claims ethics debates often focus on CIIs, but UoN has an important ethical role, especially in eroding human agency when human agency is salient.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":29,"slug":118},7,"Healthcare","healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]