Anatomical Intelligence: Live coding as performative dissection.
This article describes the method of 'dissective' live coding, as developed through the artistic-research project Anatomies of Intelligence. In this work we investigate how live coding can be used as an approach for performative explorations of a data corpus and a machine learning algorithm operatin...
| Published in: | Organised Sound Vol. 28; no. 2; pp. 290 - 305 |
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| Main Authors: | , |
| Format: | Article |
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Cambridge University Press
Aug2023
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=173033655&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 173033655 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 13557718 G0N jtl: Organised Sound issn: 13557718 maglogo: N pubinfo: dt: Aug2023 vid: 28 iid: 2 pid: 15979 pub: Cambridge University Press artinfo: ui: 173033655 10.1017/S1355771823000481 ppf: 290 ppct: 15 formats: tig: atl: Anatomical Intelligence: Live coding as performative dissection. aug: au: Chicau, Joana Reus, Jonathan affil: Creative Computing Institute, University of Arts London, London, UK Sussex Humanities Lab, University of Sussex, Brighton, UK su: Computer programming Machine learning Artificial intelligence in music Audiovisual materials Computer music sug: subj: Computer programming Machine learning Artificial intelligence in music Audiovisual materials Computer music ab: This article describes the method of 'dissective' live coding, as developed through the artistic-research project Anatomies of Intelligence. In this work we investigate how live coding can be used as an approach for performative explorations of a data corpus and a machine learning algorithm operating on this corpus. The artistic framework of this project collides early Enlightenment-era anatomical epistemologies with contemporary machine learning, creating a fertile space for novel, embodied artistic methods to emerge. We engage audiences in an immersive, live-coded experience where image and sound are driven by our dissective approach, revealing the underlying rhythms and structures of a machine learning algorithm running live on an artist-made dataset. To support these performances we have developed a custom browser-based software, the Networked Theatre, used for both hybrid in-person/online audiovisual performances. In this article we describe this work and reflect on our experience as performers and audience feedback, which suggests that our dissective method of live coding, based on examining 'ready-made' algorithms, offers a unique experiential entryway into the bodies of machine learning and data corpi. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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