Educational Perspective: AI, Deep Learning, and Creativity.
Can artificial intelligence (AI) teach and learn more creatively than humans? The article analyses deep learning theory, which follows a deterministic model of learning, since every intellectual procedure of an artificial agent is supported by concrete neural connections in an artificial neural netw...
| Publicado en: | Problems / Problemos Vol. 103; pp. 90 - 103 |
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| Autores principales: | , |
| Formato: | Artículo |
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Vilnius University
2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=163401433&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 163401433 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 13921126 3D4C jtl: Problems / Problemos issn: 13921126 maglogo: N pubinfo: dt: 2023 vid: 103 pid: 16037 pub: Vilnius University artinfo: ui: 163401433 10.15388/Problemos.2023.103.7 ppf: 90 ppct: 13 formats: fmt: @attributes: type: P size: 2.5MB tig: atl: Educational Perspective: AI, Deep Learning, and Creativity. aug: au: Dainys, Augustinas Jašinauskas, Linas affil: Vytauto Didžiojo universiteto Švietimo akademija. su: Artificial neural networks Bayes' theorem Deep learning Turing machines Apriori algorithm Artificial intelligence Creative thinking Creative ability sug: subj: Artificial neural networks Bayes' theorem Deep learning Turing machines Apriori algorithm Artificial intelligence Creative thinking Creative ability keyword: algorithm artificial intelligence Bayes’ theorem open probability algoritmas atviroji tikimybė Bayeso teorema dirbtinis intelektas ab: Can artificial intelligence (AI) teach and learn more creatively than humans? The article analyses deep learning theory, which follows a deterministic model of learning, since every intellectual procedure of an artificial agent is supported by concrete neural connections in an artificial neural network. Meanwhile, human creative reasoning follows a non-deterministic model. The article analyses Bayes’ theorem, in which a reasoning system makes judgments about the probability of future events based on events that have happened to it. Meillassoux’s open probability and M. A. Boden’s three types of creativity are discussed. A comparison is made between the a priori algorithm of the Turing machine and a playing child, who invents new a posteriori algorithms while playing. The Heideggerian perspective on the co-creativity of humans and thinking machines is analyzed. The authors conclude that humans have an open horizon for teaching and learning, and that makes them superior with respect to creativity in an educational perspective. Straipsnyje analizuojama giliojo mokymosi teorija, kuri laikosi deterministinio mokymosi modelio, nes kiekviena dirbtinio agento intelektinė procedūra yra palaikoma konkrečių dirbtinio neuronų tinklo neuroninių jungčių. Jų yra labai daug, todėl imamas apibendrintas vidutinis vaizdas. O žmogaus kūrybinis mąstymas vadovaujasi nedeterministiniu modeliu. Straipsnyje analizuojama Bayeso teorema, pagal kurią mąstanti sistema, remdamasi jai nutikusiais įvykiais, daro išvadas apie būsimų įvykių tikimybę. Analizuojama Meillassoux atviroji tikimybė ir M. A. Boden trys kūrybiškumo tipai. Lyginamas apriorinis Turingo mašinos algoritmas ir žaidžiantis vaikas, kuris žaisdamas išranda naujus aposteriorinius algoritmus. Analizuojama heidegeriška abipusio kūrybingumo tarp žmogaus ir techninių mąstančių mašinų perspektyva. Daroma išvada, kad dirbtinis intelektas mokosi pagal užprogramuotą algoritmą, o žmogus turi atvirą mokymo ir mokymosi horizontą. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Problems / Problemos is the property of Vilnius University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Problems / Problemos holder: Vilnius University dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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