Working paper Open Access

Curation and its Statistical Automation by means of Artificial 'Intelligence'

Hunger, Francis

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Hunger, Francis</dc:creator>
  <dc:description>The concept of post-AI curating discussed in this working paper explores curation as a knowledge-creation process, supported by pattern recognition and weighted networks as technical tools of artificial ‘intelligence’. The text discusses a number of concepts that build on each other, such as curating, curator, the curatorial, curatorial experimental research, post-human curating and post-AI curating.

It then examines several projects as case studies that approach curation using artificial ‘intelligence’: The Next Biennial Should Be Curated by a Machine from UBERMORGEN, Leonardo Impett and Joasia Krysa (2021) as a meta-artwork about curation and biennials; Tillmann Ohm’s project Artificial Curator (2020), which resulted in an automatically curated exhibition; and #Exstrange by Rebekah Modrak and Marialaura Ghidini et. al. (2017), which presents artworks as data objects on the eBay online platform.

Finally the text shifts to summarising embeddedness, big data infrastructures, spatiality and information model, solutionism and digital humanities, selection and similarity as instances of post-AI curating.</dc:description>
  <dc:description>Training the Archive Working Paper Series, Paper 3</dc:description>
  <dc:subject>Artificial Intelligence</dc:subject>
  <dc:subject>Media Art</dc:subject>
  <dc:title>Curation and its Statistical Automation by means of Artificial 'Intelligence'</dc:title>
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