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It examines how notions of choice and freedom are reconfigured through post-truth, suggestion algorithms, and social media in ways suited to machine automation. It also revisits earlier histories of eugenics and racism within algorithmic and artificial intelligence rationalities, outlining challenges for political action and theorizing race and sex capitalism.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/orit-halpern-neural-freedoms-population-choice-and-machine-learning/124681/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/orit-halpern-neural-freedoms-population-choice-and-machine-learning/124681.png","ImageObject",300,407,{"name":92,"@type":93},"Finn","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-29","2026-08-05",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the lecture’s central focus on machine learning models?","Question",{"text":112,"@type":113},"The talk interrogates the histories of decision-making models and agency in machine learning and connects them to neo-liberal economic thought and finance.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the lecture relate algorithms and social media to “choice” and “freedom”?",{"text":117,"@type":113},"It argues that ideas of choice and freedom are recast in ways compatible with machine automation, alongside the dynamics of post-truth and suggestion algorithms on social media.",{"name":119,"@type":110,"acceptedAnswer":120},"Why does the lecture discuss earlier histories like eugenics and racism?",{"text":121,"@type":113},"It uses these histories to show an intersecting logic within algorithmic and artificial-intelligence rationalities, rather than treating them as a simple repetition of the past.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},124681,1785893879,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":8,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":81},549768064778,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","ICI Lecture Series Models – 27 March 2023, 19:30, In English  \nis talk interrogates the history of models of decision making and agency in machine learning, neo-liberal economic thought, and 􀀞 -nance in order to interrogate how reactionary politics, population and sex, and technology are being reformulated in our present. While the relationship between the Right, post-truth, suggestion algorithms, and social media has long been documented, rarely has there been extensive investigation of how ideas of choice and freedom become recast in a manner amenable to machine automation and to the particular brands of post-1970s alt-Right discourses. An analysis of this history demonstrates anew logic within algorithmic and arti􀀞cial intelligent rationalities that intersects with, but is also not merely a recursive repetition of, earlier histories of eugenics and racism. is situation provokes serious challenges to political action, but also to our theorization of histories of race and sex capitalism.  \nOrit Halpern is an Associate Professor at Concordia University in Montréal. Her work bridges the histories of science, computing, and cybernetics with design and art practice. She especially focusses on histories and practices of big data, interactivity, and ubiquitous computing. Her mostrecent publication, Beautiful Data: A History of Vision and Reason since 1945 (2015), is a genealogy of interactivity and contemporary obsessions with ‘big’ data and data visualization. Halpern is currently working on two book projects, e Smartness Mandate, a history and theory of ‘smartness’, environment, and ubiquitous computing, and Resilient Hope, examining how cybernetics and the environmental sciences merged to produce new concepts of ecology and habitat embodied within the discourse of ‘resilience’.  \nLecture Series Models: A model can be an object of admiration, a miniature or a prototype, an abstracted phenomenon or applied theory, a literary text—practically anything from a human body on a catwalk to a mathematical description of a system. It can elicit desire, provide understanding, guide action or thought. Despite the polysemy of the term, models across disciplines and 􀀞elds share a fundamental characteristic: their e􀀛ect depends on a speci-􀀞c relational quality. A model is always a model of or for something else, and the relation is reductive insofar as it is selective and considers only certain aspects of both object and model. Critical discussions of models o􀀚en revolve around their restrictive function. And yet models are less prescriptive and more ambiguous than codi􀀞ed rules or norms. What is the critical purchase of models and how does their generative potential relate to their constitutive reduction? What are the stakes in decreasing or increasing, altering or proliferating the reductiveness of models? How can one work with and on models in a creative, productive manner without disavowing power asymmetries and their exclusionary or limiting e􀀛ects?  \nOrit Halpern Neural ‘Freedoms’  \nPopulation, Choice, and Machine Learning  \nICI Berlin | Christinenstraße 18/19, Haus 8 | D – 10119 Berlin | U – Bhf. Senefelder Platz (U2) | +49 (0)30 473 72 91 10 | www.ici–[berlin.org](berlin.org)","cbCainRj9AoWSArD","https://ap.wps.com/l/cbCainRj9AoWSArD","pdf",591672,"English","# Lecture series theme\n## Models as reductive yet generative\n## Algorithms, post-truth, and social media\n## Politics, race, and sex capitalism","[{\"question\":\"What is the lecture’s central focus on machine learning models?\",\"answer\":\"The talk interrogates the histories of decision-making models and agency in machine learning and connects them to neo-liberal economic thought and finance.\"},{\"question\":\"How does the lecture relate algorithms and social media to “choice” and “freedom”?\",\"answer\":\"It argues that ideas of choice and freedom are recast in ways compatible with machine automation, alongside the dynamics of post-truth and suggestion algorithms on social media.\"},{\"question\":\"Why does the lecture discuss earlier histories like eugenics and racism?\",\"answer\":\"It uses these histories to show an intersecting logic within algorithmic and artificial-intelligence rationalities, rather than treating them as a simple repetition of the past.\"}]","Orit Halpern - Neural ‘Freedoms’ - Population, Choice, and Machine Learning | PDF"]