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Neural Novelty — How Machine Learning Does Interactive Generative Literature
Malmö University, Faculty of Culture and Society (KS).
2020 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Every day, machine learning (ML) and artificial intelligence (AI) embeds itself further into domestic and industrial technologies. Interaction de- signers have historically struggled to engage directly with the subject, facing a shortage of appropriate methods and abstractions. There is a need to find ways though which interaction design practitioners might integrate ML into their work, in order to democratize and diversify the field. This thesis proposes a mode of inquiry that considers the inter- active qualities of what machine learning does, as opposed the tech- nical specifications of what machine learning is. A shift in focus from the technicality of ML to the artifacts it creates allows the interaction designer to situate its existing skill set, affording it to engage with ma- chine learning as a design material. A Research-through-Design pro- cess explores different methodological adaptions, evaluated through user feedback and an-in depth case analysis. An elaborated design experiment, Multiverse, examines the novel, non-anthropomorphic aesthetic qualities of generative literature. It prototypes interactions with bidirectional literature and studies how these transform the reader into a cybertextual “user-reader”. The thesis ends with a discussion on the implications of machine written literature and proposes a number of future investigations into the research space unfolded through the prototype.

Place, publisher, year, edition, pages
Malmö universitet/Kultur och samhälle , 2020. , p. 61
Keywords [en]
machine learning, generative literature, interaction design, cybertext, interactive literature, interactive machine learning, IML, ML, artificial intelligence, postmodern literature, gpt-2
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-21222Local ID: 32510OAI: oai:DiVA.org:mau-21222DiVA, id: diva2:1481128
Educational program
KS K3 Interaction Design (master)
Supervisors
Examiners
Available from: 2020-10-27 Created: 2020-10-27Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf