Aesthetics of Uncertainty

Rosemary Lee

Aesthetics of Uncertainty

Rosemary Lee

Digital Design

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

Abstract

Machine learning has a tendency to reveal inconsistencies which have transversal relevance bridging computer science with art and the humanities. Rather than purely situations of inconsistency, discrepancy, or malfunction, Derrida’s notion of aporia describes uncertainty as a precondition of dialectics. Expanding on Derrida’s line of thinking, this paper speculates that the internal frictions which can be found in artificial intelligence and machine learning systems may be understood in terms of a new kind of aesthetic informed by uncertainty.

Original language	English
Title of host publication	Proceedings of the Conference on Computation, Communication, Aesthetics & X
Number of pages	6
Volume	7
Publisher	Universidade de Porto, Portugal
Publication date	9 Oct 2019
Pages	256-262
ISBN (Electronic)	9789897462207
Publication status	Published - 9 Oct 2019
Event	Conference on Computation, Communication, Aesthetics & X (xCoAx) - Fabbrica del Vapore, Milan, Italy Duration: 3 Jul 2019 → 5 Jul 2019 Conference number: 7 http://2019.xcoax.org

Conference

Conference	Conference on Computation, Communication, Aesthetics & X (xCoAx)
Number	7
Location	Fabbrica del Vapore
Country/Territory	Italy
City	Milan
Period	03/07/2019 → 05/07/2019
Internet address	http://2019.xcoax.org

Keywords

machine learning
art
uncertainty
aesthetics
aporia
uncanny

Access to Document

Lee_Rosemary_xCoAx2019Final published version, 232 KBLicence: CC BY-NC-SA

1 Journal article

Uncertainties in the Algorithmic Image
Lee, R., 29 Dec 2019, In: Journal of Science and Technology of the Arts (CITAR). 11, 2
Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review

Open Access
File

Cite this

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title = "Aesthetics of Uncertainty",

abstract = "Machine learning has a tendency to reveal inconsistencies which have transversal relevance bridging computer science with art and the humanities. Rather than purely situations of inconsistency, discrepancy, or malfunction, Derrida{\textquoteright}s notion of aporia describes uncertainty as a precondition of dialectics. Expanding on Derrida{\textquoteright}s line of thinking, this paper speculates that the internal frictions which can be found in artificial intelligence and machine learning systems may be understood in terms of a new kind of aesthetic informed by uncertainty.",

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publisher = "Universidade de Porto, Portugal",

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N2 - Machine learning has a tendency to reveal inconsistencies which have transversal relevance bridging computer science with art and the humanities. Rather than purely situations of inconsistency, discrepancy, or malfunction, Derrida’s notion of aporia describes uncertainty as a precondition of dialectics. Expanding on Derrida’s line of thinking, this paper speculates that the internal frictions which can be found in artificial intelligence and machine learning systems may be understood in terms of a new kind of aesthetic informed by uncertainty.

AB - Machine learning has a tendency to reveal inconsistencies which have transversal relevance bridging computer science with art and the humanities. Rather than purely situations of inconsistency, discrepancy, or malfunction, Derrida’s notion of aporia describes uncertainty as a precondition of dialectics. Expanding on Derrida’s line of thinking, this paper speculates that the internal frictions which can be found in artificial intelligence and machine learning systems may be understood in terms of a new kind of aesthetic informed by uncertainty.

KW - machine learning

KW - art

KW - uncertainty

KW - aesthetics

KW - aporia

KW - uncanny

UR - http://2019.xcoax.org/xCoAx2019.pdf

M3 - Article in proceedings

VL - 7

SP - 256

EP - 262

BT - Proceedings of the Conference on Computation, Communication, Aesthetics & X

PB - Universidade de Porto, Portugal

T2 - Conference on Computation, Communication, Aesthetics & X (xCoAx)

Y2 - 3 July 2019 through 5 July 2019

ER -

Aesthetics of Uncertainty

Abstract

Conference

Keywords

Access to Document

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Research output

Uncertainties in the Algorithmic Image

Cite this