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Vzgojiti umetno inteligenco?
ID Fink, Andraž (Author), ID Krašovec, Primož (Mentor) More about this mentor... This link opens in a new window, ID Kroflič, Robert (Mentor) More about this mentor... This link opens in a new window, ID Prosen, Timotej (Comentor)

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Abstract
Delo obravnava vprašanje, ali je mogoče vzgojiti umetno inteligenco, osredinja pa se predvsem na velike jezikovne modele kot trenutno najrazvitejšo in najbolj množično razširjeno obliko generativne umetne inteligence. Temelji na enaktivistični teoriji udejanjenega postajanja in avtopoetski paradigmi vzgoje, ki jo predstavlja ob konceptu uravnavanja umetne inteligence. Delo temelji na konceptualni raziskavi s pomočjo narativnega pregleda literature, v katerega so bili vključeni viri s področij pedagogike, sociologije, filozofije, kognitivne znanosti in umetne inteligence. V delu predstavimo tri glavne ugotovitve. Zdajšnjih velikih jezikovnih modelov ni mogoče vzgajati, če vzgojo razumemo skozi dimenzije udejanjenega postajanja, jezikovanja, moralnega razsojanja in subjektifikacije. Procesa uravnavanja in vzgoje nikakor nista enakovredna. Prvi predstavlja optimizacijo k vnaprej določenemu cilju, drugi pa odprt dialoški proces postajanja subjekta. Vseeno pa lahko etični cilji vzgoje informirajo načrtovanje prihodnjih modelov umetne inteligence v smeri razvoja multimodalnih sistemov, ki bodo lahko vsaj deloma udejanjeni. Pojem vzgoje je za opis trenutnih procesov uravnavanja umetne inteligence neustrezen in ostaja vezan na specifične pogoje človeškega postajanja.

Language:Slovenian
Keywords:vzgoja, veliki jezikovni modeli, umetna inteligenca, udejanjeno postajanje, uravnavanje, jezikovanje
Work type:Master's thesis/paper
Organization:FF - Faculty of Arts
Year:2026
PID:20.500.12556/RUL-189027 This link opens in a new window
COBISS.SI-ID:293365763 This link opens in a new window
Publication date in RUL:01.10.2026
Views:311
Downloads:72
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Secondary language

Language:English
Title:Educating artificial intelligence?
Abstract:
This work examines the question of whether it is possible to educate artificial intelligence, focusing primarily on large language models as the currently most advanced and widely used form of generative artificial intelligence. It is based on the enactivist theory of embodied becoming and the autopoietic paradigm of education, which is presented alongside the concept of aligning artificial intelligence. The work is based on conceptual research using a narrative review of the literature, which included sources from the fields of pedagogy, sociology, philosophy, cognitive science and artificial intelligence. In this paper, we present three main findings. Current large language models cannot be educated if we understand education through the dimensions of embodied becoming, language formation, moral judgement and subjectification. The processes of alignment and education are by no means equivalent. The former represents optimisation towards a predetermined goal, whilst the latter is an open-ended, dialogical process of becoming a subject. Nevertheless, the ethical goals of education can inform the design of future artificial intelligence models towards the development of multimodal systems that will be at least partially embodied. The concept of education is inadequate for describing current processes of regulating artificial intelligence and remains tied to the specific conditions of human becoming.

Keywords:education, large language models, artificial intelligence, enactive becoming, alignment, languaging

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