[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124931-en":3,"doc-seo-124931-105":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},124931,5909877438554,"Maeve","https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272",8,"Research & Report","The Immortal Science of ML - Machine Learning & the Theory-Free Ideal","This paper challenges the idea that machine learning (ML) can radically disrupt scientific knowledge and practice by enabling theory-free inductive inference. It introduces a theory-free ideal as a scientific meta-narrative that seeks to minimize, or eliminate, the influence of theory on knowledge production. Through two case studies, it argues that this ideal—along with its normative counterpart—undermines the epistemic standing of ML-based science.","The Immortal Science of ML: Machine Learning & the Theory-Free Ideal  \nMel Andrews  \nAugust 26, 2024  \nAbstract  \nThis paper contends with the widespread belief that the methods of machine learning (ML) have the capacity to radically disrupt the nature of scientific knowledge or practice on the grounds that these methods enable a form of theory-free inductive inference. Such views about scientific ML flow directly from what I term a theory-free ideal in science: a scientific meta-narrative according to which the influence of theory on scientific knowledge-production should be minimised, if not altogether eliminated.  \nBy means of two case studies, I argue that this theory-free ideal, like its normative corollary, has a deleterious effect on the epistemic standing of ML-based science.  \n1 Introduction  \nThe prospects of machine learning (ML) for science have opened wide in the last decade, in which time ML-based methods were adopted in the Large Hadron Collider at CERN for sorting the significance of particle collision events (Duarte et al., 2018) and DeepMind released its AlphaFold, AlphaFold 2.0, and AlphaFold 3.0 (Jumper et al., 2021), capable of predicting tertiary and quaternary protein structure from amino acid sequence data, effectively solving one of biology’s most complex and enduring open problems. The rapidity and ubiquity of machine learning uptake across all sectors of public life, in particular, science, has sparked an onslaught of speculation concerning its nature and the downstream consequences of its widespread use.  \nSuch speculation has issued from cultural commentators, journalists, and media personalities, from the researchers and engineers producing the tools of ML and the scientists deploying them and from philosophers, in both academic and popular venues. Responses focussed on the epistemic status of ML and its projected impact on science have echoed statements to the effect that machine learning differs radically from prevailing modelling, statistical, or scientific methods in ways that are projected to change the landscape of scientific discovery orthe nature of the epistemic fruits of scientific enterprise.  \nThese interlocutors predict that ML will instigate profound—even “revolutionary”—changes to the nature of science and the knowledge it produces (Anderson, 2008; Boge, 2022; Hey et al., 2009; Mayer-Sch¨onberger & Cukier, 2013; Society & Institute., 2019; Spinney, 2022; Sre´ckovi´c et al., 2022) . Call this view the disruption claim. According to this perspective, ML methods are seen as holding the potential to retire or else displace the role of theorising in science (Anderson, 2008; Mayer-Sch¨onberger & Cukier, 2013; Spinney, 2022; Sre´ckovi´cet al., 2022) . Desai et al. (2022) refer to this conception of an ML-enabled scientific paradigm as “the epistemically revolutionary new frontier raised by data science: the so-called ‘theory-free’ paradigm in scientific methodology.” Some of these statements regarding the scientific usage of ML echo proclamations that were once made of classical statistical method: that big data analytic tools promise to allow the raw data to “speak for themselves” (Levins & Lewontin, 1985) .  \nThese claims of disruption could be understood as instances of ML or AI hype—they issue from spokespeople swept up in a wave of drastically overselling the capabilities of presently existing ML techniques 1 . Indeed, Hansen & Quinon (2023) argue that AI hype is principally responsible for belief in the possibility of theory-free science. While cultural misapprehensions of AI no doubt play a role, I argue that the root of such beliefs runs far deeper, and is in fact grounded in a conception of scientific objectivity.  \nDating back to the first articulations of the modern scientific method, generally located in the writings of Francis Bacon (1878), the notion of objectivity has reigned supreme. Bacon advocated a kind of empiricism which, according to modern scholarship, sought to mini","cbCairvgw4koqNs2","https://ap.wps.com/l/cbCairvgw4koqNs2","pdf",258306,1,25,"English","en",105,"# Introduction\n## ML for science and the disruption claim\n## Objectivity, value-free ideals, and the theory-free ideal\n## Theory-freedom and its epistemic implications","[{\"question\":\"What does the paper mean by the “theory-free ideal” in science?\",\"answer\":\"It refers to a scientific meta-narrative that aims to minimize or eliminate the role of theory in knowledge production, treating ML-like inference as theory-free.\"},{\"question\":\"How does the paper connect the theory-free ideal to the epistemic standing of ML-based science?\",\"answer\":\"Using two case studies, it argues that the theory-free ideal and its normative counterpart damage how well ML-based approaches justify knowledge claims.\"},{\"question\":\"Why does the paper discuss AI hype and overselling ML capabilities?\",\"answer\":\"It treats many “disruption” predictions as driven by hype, and it argues that deeper assumptions about scientific objectivity motivate belief in theory-free science.\"}]","The Immortal Science of ML - Machine Learning & the Theory-Free Ideal | PDF",1785895451,63,{"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},"the-immortal-science-of-ml-machine-learning-the-theory-free-ideal","",{"@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/the-immortal-science-of-ml-machine-learning-the-theory-free-ideal/124931/",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","2026-08-05",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 does the paper mean by the “theory-free ideal” in science?","Question",{"text":75,"@type":76},"It refers to a scientific meta-narrative that aims to minimize or eliminate the role of theory in knowledge production, treating ML-like inference as theory-free.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the paper connect the theory-free ideal to the epistemic standing of ML-based science?",{"text":80,"@type":76},"Using two case studies, it argues that the theory-free ideal and its normative counterpart damage how well ML-based approaches justify knowledge claims.",{"name":82,"@type":73,"acceptedAnswer":83},"Why does the paper discuss AI hype and overselling ML capabilities?",{"text":84,"@type":76},"It treats many “disruption” predictions as driven by hype, and it argues that deeper assumptions about scientific objectivity motivate belief in theory-free science.","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},[93,97,101,105,110,115,120,123,128,131,135],{"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":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]