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Invisible Images: Your Pictures Are Looking at You

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Abstract

What are the implications of computer vision in relation to machine learning and ‘artificial intelligence’? New York‐based artist and writer Trevor Paglen argues that autonomous image‐interpretation systems, from algorithms that analyse photos on Facebook to licence‐plate readers used by police, constitute a new kind of visuality which is paradoxically largely invisible to human eyes. What is more, this new ‘invisible visuality’ should be understood as a means of centralising power in the hands of the state and corporate actors who are able to deploy machine‐vision systems at scale.

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... I am intruded not only because the algorithm is prompting me to see specific parts of my past, but because the algorithm itself is seeing specific parts of my past: in telling me what to remember, the algorithm also sees me. Paglen (2016) delves into 'the invisible visual culture' of machine-images illegible to the human eye. There is a fundamental difference between analogously sharing a photo with your friends and sharing a photo on social media. ...
... And as I am watching the picture, the duration of my gaze, whether I share it, or if I delete it, are data to be extracted. The algorithmic systems generating my memory are perceptive, or as formulated by Paglen (2016): your pictures are looking at you. ...
... Coeckelbergh (2021) points out that the very data points that are stored do not change in real-time as soon as they enter the data set: we can change the algorithm, but the data on the past is stored in data points, spatialised in an eternal present. But these data points are illegible to us, or to use Paglen's (2016) formulationthey are invisible to usand the only way in which we can see them is through algorithms that evolve through time, showing us bits of our past when it is considered the 'right-time' (Bucher 2020;Jacobsen 2022b) to do so. ...
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This article is on algorithmically generated memories: data on past events that are stored and automatically ranked and classified by digital platforms, before they are presented to the user as memories. By mobilising Henri Bergson's philosophy, I centre my analysis on three of their aspects: the spatialisation and calculation of time in algorithmic systems, algorithmic remembrance, and algorithmic perception. I argue that algorithmically generated memories are a form of automated remembrance best understood as perception, and not recollection. Perception never captures the totality of our surroundings but is partial and the parts of the world we perceive are the parts that are of interest to us. When conscious beings perceive, our perception is always coupled with memory, which allows us to transcend the immediate needs of our body. I argue that algorithmic systems based on machine learning can perceive, but that they cannot remember. As such, their perception operates only in the present. The present they perceive in is characterised by immense amounts of data that are beyond human perceptive capabilities. I argue that perception relates to a capacity to act as an extended field of perception involves a greater power to act within what one perceives. As such, our memories are increasingly governed by a perception that operates in a present beyond human perceptual capacities, motivated by interests and needs that lie somewhat beyond interests of needs formulated by humans. Algorithmically generated memories are not only trying to remember for us, but they are also perceiving for us.
... Atisbamos un momento donde no existe ninguna estrategia visual proveniente de la cultura visual humana que permita intervenir de manera evidente en el contexto de la visión maquínica (Paglen, 2019). El carácter reproducible de la fotografía llevó a la imagen a abandonar el marco para interpelar al receptor, satisfaciendo así el deseo de las masas por aproximarse a las cosas, quitar la envoltura a cada objeto y triturar su aura (Benjamin, 2003). ...
... Hay un peculiar retorno de la experiencia de devolución de la mirada por parte de las imágenes, que Walter Benjamin consideraba que enfrentaba su decadencia con la reproducción técnica. Tus imágenes, advierte Trevor Paglen (2019), están mirándote, pero no para desplegar el juego entre cercanía y distancia propio del aura, sino para localizar, clasificar y decidir las formas de subjetividad y de socialización. Aquella afirmación de Paul Klee, cuando anunciaba que los objetos lo percibían, se vuelve, observó Paul Virilio (1998), objetiva y verídica. ...
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... Atisbamos un momento donde no existe ninguna estrategia visual proveniente de la cultura visual humana que permita intervenir de manera evidente en el contexto de la visión maquínica (Paglen, 2019). El carácter reproducible de la fotografía llevó a la imagen a abandonar el marco para interpelar al receptor, satisfaciendo así el deseo de las masas por aproximarse a las cosas, quitar la envoltura a cada objeto y triturar su aura (Benjamin, 2003). ...
... Hay un peculiar retorno de la experiencia de devolución de la mirada por parte de las imágenes, que Walter Benjamin consideraba que enfrentaba su decadencia con la reproducción técnica. Tus imágenes, advierte Trevor Paglen (2019), están mirándote, pero no para desplegar el juego entre cercanía y distancia propio del aura, sino para localizar, clasificar y decidir las formas de subjetividad y de socialización. Aquella afirmación de Paul Klee, cuando anunciaba que los objetos lo percibían, se vuelve, observó Paul Virilio (1998), objetiva y verídica. ...
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This article analyses some of the main lines of research in German image science (Bildwissenschaft) in the context of the transformations of digital culture and their impact on the contemporary status of the image. After a comparison between the approaches of Anglo-Saxon visual studies and Bildwissenschaft to visual culture and image, the approaches of three of the most prominent theorists in this field of study - Gottfried Boehm, Horst Bredekamp and Hans Belting - are summarized. Finally, the scope of the theoretical developments of these thinkers for dealing with digital visual culture is assessed, by addressing the questions of the concept of image, iconic agency, and media.
... To this end, Parisi points to an argument Trevor Paglen makes in 2016 about the growing culture of "invisible images," meaning invisible to humans. 60 Paglen notes that digital images in general are only actually readable to computers and cannot be seen by humans without computer aid, and, even with this aid, only under certain conditions. This change to visual culture is alarming, as Paglen and other scholars of visual culture have pointed out, for many reasons, including the fact that the invisibility of images "allows for the automation of vision on an enormous scale and, along with it, the exercise of power on dramatically larger and smaller scales than have ever been possible." ...
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Are render engines fascist? This article proposes a debate on the relationship between conservative and far-right politics and environmental visualization technologies. The argument works through a close reading of a patented texture mapping process owned by Google Earth and a related artistic project titled Postcards from Google Earth (2010-ongoing) by Clement Valla. These case studies surface the engineering choices that selectively edit and optimize what is seen by users, thus creating a very particular, and manipulable, framing of “environment.” On this basis the article makes two claims: one, that computer graphics play a part in the conservative, right, and far-right mobilizations of nature-as-metaphor that nourish fascist and populist imaginaries, and two, that computer graphics more broadly reshapes human visual culture in ways that amplify the central contradictions of liberalism that have historically been exploited by fascism, such as an anti-allegiance to fact and rationality. The article concludes that combining digital technologies with representations of environments can resurrect latent conservative politics of the environment, and furthermore, that these politics can be directly and critically assessed through canonical interrogations of landscape art.
... 54 The copy machine image, a self-generating mechanism, aspires to leave no trace, not unlike the "invisible plane" hidden from human vision in contemporary digital media. 55 As Thomas Keenan writes, the "ideal mode of reading [instrumental images] would be not to have to read them at all." 56 In the machine-produced image, we should not see the machine at all-a transparent process between the viewer and the viewed. These are topics that remain current in our contemporary algorithmic capitalism in which service labor is replaced by automated systems. ...
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... На тај начин настају машинско превођење (Делић и сар. 2019), синтеза говора, при чему је могуће реализовати дијалог човека и рачунара (Chiba et al. 2019), препознавање слика и текста (Paglen 2019), интелигентно адаптивно учење (Almohammadi et al. 2017), а могуће је реализовати и бројне акције (помоћу робота) (Khandelwal et al. 2017). Због наведених могућности дошло је до промене традиционалног образовања и поучавања (Yufei et al. 2020) чиме су школе и универзитети, а са њима и наставници, добили нове идеје и могућности за реформу наставе и образовања. ...
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... To sum up, what has changed in the photographic perception of the world with machine vision is not just that the viewer of the images is no longer human (Paglen, 2016), but rather that the photographic image itself can be described as nonhuman (Zylinska, 2017), being subject to a plethora of data operations involving fragmentation, extraction, reduction and elision that go beyond human intentionality and agency. Humans are still partly involved in these operations, not least in the foundational decisions about reducing objects to images and rich imagistic data to extractable and exchangeable sequences of features. ...
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... Second, the gaze withdraws itself. Because it is decentralised and inhuman, the gaze is almost impossible to locate and identify (Paglen 2016). Third, the gaze is able to gaze "deeply". ...
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... Trevor Paglen would go even further and state that images are mainly made for computers through the using of their meta-data or the feeding of artificial intelligence. These images are not for humans anymore because they are a constitutive part of the entanglement for controlling people by algorithmic means, as well as the modulation of their desire (Paglen 2016). Matteo Pasquinelli has been insisting on similar ideas, relating them as well with the history of algorithm-making, which he proposes that they are an ancient technology related to ritual practices (Pasquinelli 2019) and that "Machine intelligence is not anthropomorphic, but sociomorphic: it imitates and feeds on the condividual structures of society rather than the individual ones" (Pasquinelli 2016). ...
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... • Pages 227-238 help of image characteristics (Yılmaz et al., 2019). According to Paglen (2019), all cultures of the world must have a visual aspect; thus, this topic is increasingly getting the attention of significant researchers and scholars; therefore an increasing number of research studies are being conducting in this regard. In the context of visual culture practices incorporated into museums, the visual images are the component of the practices it focuses on how to see a particular object by making all the required arrangements (Serafini, 2022). ...
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... These images are in stark contrast with the "desert of the real" [20] and are widely available for comprehension. Paglen observes that the result of this automation of images on a grand scale is the generation of more power [21]. This reversal of visibility is reminiscent of Martin's paradoxical model, where the visible world (the matrix) is not related to representation but rather represents an absence [22]. ...
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