ITU

Uncertainties in the Algorithmic Image

Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

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The incorporation of algorithmic procedures into the automation of image production has been gradual, but has reached critical mass over the past century, especially with the advent of photography, the introduction of digital computers and the use of artificial intelligence (AI) and machine learning (ML). Due to the increasingly significant influence algorithmic processes have on visual media, there has been an expansion of the possibilities as to how images may behave, and a consequent struggle to define them. This algorithmic turn highlights inner tensions within existing notions of the image, namely raising questions regarding the autonomy of machines, author- and viewer- ship, and the veracity of representations. In this sense, algorithmic images hover uncertainly between human and machine as producers and interpreters of visual information, between representational and non-representational, and between visible surface and the processes behind it. This paper gives an introduction to fundamental internal discrepancies which arise within algorithmically produced images, examined through a selection of relevant artistic examples. Focusing on the theme of uncertainty, this investigation considers how algorithmic images contain aspects which conflict with the certitude of computation, and how this contributes to a difficulty in defining images.
Original languageEnglish
JournalJournal of Science and Technology of the Arts (CITAR)
Volume11
Issue number2
DOIs
Publication statusPublished - 29 Dec 2019
EventConference on Computation, Communication, Aesthetics & X (xCoAx) - Fabbrica del Vapore, Milan, Italy
Duration: 3 Jul 20195 Jul 2019
Conference number: 7
http://2019.xcoax.org

Conference

ConferenceConference on Computation, Communication, Aesthetics & X (xCoAx)
Number7
LocationFabbrica del Vapore
CountryItaly
CityMilan
Period03/07/201905/07/2019
Internet address

Bibliographical note

xCoAx 2019 - Special Issue

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    Research areas

  • algorithmic media, image, artificial intelligence, machine learning, art, aesthetics

Research outputs (1)

  1. Published

    Aesthetics of Uncertainty

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

ID: 84628267