## THE CULLING OF PHOTOGRAPHIC IMAGES

## Olga Goriunova

A  cull  of  images  is  coming,  an  automated  decimation,  which will  transform  the  ontology  of  the  image  once  again.  Google announced that from June 1, 2021, they will stop the free back up  of  compressed  'high'  quality  photos.  The  significance  of this  development  is  hard  to  overestimate.  At  this  point,  any connection of smartphone photographs to the original medium of photography and associated practices will finally be fully severed.

In the recent decade, substantial discussions about networked images  accounted  for  some  of  the  core  principles  of  image operations today 1 :

people took over a trillion photos in 2020, an amount that cannot possibly be processed by the human eye;

images changed their nature from being a cherished photograph or, in any case, an object bounded by the limitations of its medium, to a digital stream of imagery, co-produced by the technical apparatus and circulating in the networks;

the  material  of  images  is  a  continuum  formed  between photographs, 3D models, animations and environments, maps, layers of augmentation, and virtual production;

images  freed  from  sentimental,  artistic,  or  instrumental meaning  form  databases  used  to  train  machine  learning models to recognise and label images and derive conclusions and predictions about humans.

Nevertheless, services still print photographs, shops sell frames, and the media of desire, from design magazines to film, regularly feature photographs on the walls. The photograph in your phone, machine-assisted and -read, circulating in the network and readily informing data analysts on its host, was still -up until now -a photograph of a printable quality, lying in wait for a possible welcome into the  paper-based  world.  The  possibility  to  print, even if rarely used, still grounded image-taking in the originary photographic  processes,  whose  ontological  concern  was  the manufacturing of a material impression of the world. This faint connection, ontologically troubled by the materiality of digital media (electric impulses, Boolean algebra, discreteness), will now be completely removed.

When free backup is turned off, and memory cards fill up quickly, who will be able to afford life-long monthly payments for storage? What will happen to family photography? Will the relatives of the deceased keep paying for the family archives, growing more and more enormous with every year? A possibility to lose a life's-worth of photographs will arise. People will need to assess the value of every image they take and decide which ones to save. Although Google or Apple will help us decide, deleting images of 'poor quality,'  our  style  of  taking  photographs  perpetually,  formed by the availability of smartphone and network socialisation, is unlikely to change. Amazon and undoubtedly many others will provide cloud backup services, but an uninterrupted perpetual backup is a fantasy. We will have to accept that photographic images are no longer printable and their existence is confined by the strict bounds of resolution. The overflow of smartphone images  into  art  exhibitions  will  stop.  'Amateur'  smartphone photography, despite powerful cameras and intelligent software, will basically be confined to the status of thumbnails.

The  mass  culling  of  photographic  images  can  only  mean  one thing: the automation of image analysis does not require printable quality. Machine vision is modelled on human vision and there is no detectable interest in trying to liberate AI from the diktat of its limits and to explore what a non-human, truly computer vision could see. 2 It  is  the images made by humans that form training datasets, whose function is to prepare computational models to analyse more images made by humans. Such automation of imageprocessing is entirely human-centred because it aims to derive actionable insight on the human as the 'source of all possible cash'.

Clearly, unlimited data storage on the cloud is not ecologically sustainable. The concerns of preservationists of media art, net and software art archivists, battling with defunct software and hardware will now be everyone's preserve. Perhaps, photographic studios and family photography will come back. Perhaps, imagemaking  of  a  classical  type  will  be  resurrected  alongside  the increasingly ephemeral streams of images, pixelated shadows, which will still carry the substantial information for AI, marketing, policing,  the  management  of  the  population  and  individual consumers. Similarly to how facial biometrics is most concerned with the geometry of the cheekbones, nose and eyebrows, which form  the  'human  face'  for  the  assessing  program,  schematic images can emerge as a new genre. A dream of technocrats, keen to sort information into the categories of primary and secondary (and so on) importance, such future digital imagery of reduced resolution will carry minimal visual excess: just a little bit to titillate  the  social  networkers  and  enough  to  meet  a  machine learning model's specification.

OLGA GORIUNOVA is Professor at Royal Holloway University of London and author of Art Platforms (Routledge, 2012) and Bleak Joys (with M. Fuller, University of Minnesota Press, 2019). An editor of Fun and Software (Bloomsbury, 2014), she was a co-curator of software art platform Runme.org (2003) before the age of social platforms. She also wrote on new media idiocy, memes and lurkers. Her continuing interests are at the intersection of aesthetics, computation and subjectivation, and, more recently, ecology and plants.

- 1 Katrina Sluis, Daniel Rubinstein, 'The Digital Image in Photographic Culture: Algorithmic Photography and the Crisis of Representation.' In: M. Lister (ed.) The Photographic Image in Digital Culture , 2nd Ed. London: Routledge, 2013; Katrina Sluis, 'Beyond Representation? The database-driven image and the non-human spectator'. In: S. Bull (ed.) A Companion to Photography . London: Wiley-Blackwell, 2020; Nicolas Malevé, https://unthinking.photography/contributors/ nicolas-maleve.
- 2 Olga Goriunova, 'Humans Categorise Humans: on ImageNet Roulette and Machine Vision,' Donaufestival: Redefining Arts Catalogue , April 2020, accessed May 4, 2021, https://pure.royalholloway.ac.uk/portal/ files/41356875/ENG\_Olga\_Goriunova\_Human\_ Categories\_DonauFestival\_article.pdf.